Relevant bibliographies by topics / Optimal dividend control problem

Academic literature on the topic 'Optimal dividend control problem'

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Published: 11 March 2023

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Journal articles on the topic "Optimal dividend control problem"

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Ekström, Erik, and Bing Lu. "The Optimal Dividend Problem in the Dual Model." Advances in Applied Probability 46, no. 3 (September 2014): 746–65. http://dx.doi.org/10.1239/aap/1409319558.

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We study de Finetti's optimal dividend problem, also known as the optimal harvesting problem, in the dual model. In this model, the firm value is affected both by continuous fluctuations and by upward directed jumps. We use a fixed point method to show that the solution of the optimal dividend problem with jumps can be obtained as the limit of a sequence of stochastic control problems for a diffusion. In each problem, the optimal dividend strategy is of barrier type, and the rate of convergence of the barrier and the corresponding value function is exponential.
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Ekström, Erik, and Bing Lu. "The Optimal Dividend Problem in the Dual Model." Advances in Applied Probability 46, no. 03 (September 2014): 746–65. http://dx.doi.org/10.1017/s0001867800007357.

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We study de Finetti's optimal dividend problem, also known as the optimal harvesting problem, in the dual model. In this model, the firm value is affected both by continuous fluctuations and by upward directed jumps. We use a fixed point method to show that the solution of the optimal dividend problem with jumps can be obtained as the limit of a sequence of stochastic control problems for a diffusion. In each problem, the optimal dividend strategy is of barrier type, and the rate of convergence of the barrier and the corresponding value function is exponential.
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Pérez, José-Luis, Kazutoshi Yamazaki, and Xiang Yu. "On the Bail-Out Optimal Dividend Problem." Journal of Optimization Theory and Applications 179, no. 2 (June 23, 2018): 553–68. http://dx.doi.org/10.1007/s10957-018-1340-3.

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Zhu, Jinxia. "OPTIMAL FINANCING AND DIVIDEND DISTRIBUTION WITH TRANSACTION COSTS IN THE CASE OF RESTRICTED DIVIDEND RATES." ASTIN Bulletin 47, no. 1 (October 5, 2016): 239–68. http://dx.doi.org/10.1017/asb.2016.29.

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AbstractWe consider the optimal financing (capital injections) and dividend payment problem for a Brownian motion model in the case of restricted dividend rates. The company has no obligation to inject capitals and therefore, the bankruptcy risk is present. Capital injections, if any, will incur both fixed and proportional transaction costs and dividend payments incur proportional transaction costs. The aim is to find the optimal strategy to maximize the expected present value of dividend payments minus the total cost of capital injections up to the time of bankruptcy. The problem is formulated as a mixed impulse-regular control problem. We address the problem via studying three cases of two auxiliary functions. We derive important analytical properties of the auxiliary functions and use them to study the value function and then identify the optimal control strategy. We show that the optimal dividend control is of threshold type and the optimal financing strategy prescribes to either never inject capitals or inject capitals only when the surplus reaches 0 with a fixed lump sum amount.
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Lindensjö, Kristoffer, and Filip Lindskog. "Optimal dividends and capital injection under dividend restrictions." Mathematical Methods of Operations Research 92, no. 3 (July 16, 2020): 461–87. http://dx.doi.org/10.1007/s00186-020-00720-y.

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AbstractWe study a singular stochastic control problem faced by the owner of an insurance company that dynamically pays dividends and raises capital in the presence of the restriction that the surplus process must be above a given dividend payout barrier in order for dividend payments to be allowed. Bankruptcy occurs if the surplus process becomes negative and there are proportional costs for capital injection. We show that one of the following strategies is optimal: (i) Pay dividends and inject capital in order to reflect the surplus process at an upper barrier and at 0, implying bankruptcy never occurs. (ii) Pay dividends in order to reflect the surplus process at an upper barrier and never inject capital—corresponding to absorption at 0—implying bankruptcy occurs the first time the surplus reaches zero. We show that if the costs of capital injection are low, then a sufficiently high dividend payout barrier will change the optimal strategy from type (i) (without bankruptcy) to type (ii) (with bankruptcy). Moreover, if the costs are high, then the optimal strategy is of type (ii) regardless of the dividend payout barrier. We also consider the possibility for the owner to choose a stopping time at which the insurance company is liquidated and the owner obtains a liquidation value. The uncontrolled surplus process is a Wiener process with drift.
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Sun, Shi Liang, Xiao Qian Huang, and Lu Lian. "Control Strategy of Proportional Reinsurance with Dividend Process." Applied Mechanics and Materials 488-489 (January 2014): 1301–5. http://dx.doi.org/10.4028/www.scientific.net/amm.488-489.1301.

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This paper is concerned with the problem of proportional reinsurance control strategy with dividend process in insurance company. The existence of optimal control strategy is proved by variational inequality,and the specific construct of optimal control strategy and the explicit structure of optimal return function are derived.
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Chevalier, Etienne, Vathana Ly Vath, and Simone Scotti. "An Optimal Dividend and Investment Control Problem under Debt Constraints." SIAM Journal on Financial Mathematics 4, no. 1 (January 2013): 297–326. http://dx.doi.org/10.1137/120866816.

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Chen, Mi, Xiaofan Peng, and Junyi Guo. "Optimal dividend problem with a nonlinear regular-singular stochastic control." Insurance: Mathematics and Economics 52, no. 3 (May 2013): 448–56. http://dx.doi.org/10.1016/j.insmatheco.2013.02.010.

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De Angelis, Tiziano. "Optimal dividends with partial information and stopping of a degenerate reflecting diffusion." Finance and Stochastics 24, no. 1 (October 18, 2019): 71–123. http://dx.doi.org/10.1007/s00780-019-00407-1.

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Abstract We study the optimal dividend problem for a firm’s manager who has partial information on the profitability of the firm. The problem is formulated as one of singular stochastic control with partial information on the drift of the underlying process and with absorption. In the Markovian formulation, we have a two-dimensional degenerate diffusion whose first component is singularly controlled. Moreover, the process is absorbed when its first component hits zero. The free boundary problem (FBP) associated to the value function of the control problem is challenging from the analytical point of view due to the interplay of degeneracy and absorption. We find a probabilistic way to show that the value function of the dividend problem is a smooth solution of the FBP and to construct an optimal dividend strategy. Our approach establishes a new link between multidimensional singular stochastic control problems with absorption and problems of optimal stopping with ‘creation’. One key feature of the stopping problem is that creation occurs at a state-dependent rate of the ‘local time’ of an auxiliary two-dimensional reflecting diffusion.
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Albrecher, Hansjörg, Pablo Azcue, and Nora Muler. "Optimal dividend strategies for two collaborating insurance companies." Advances in Applied Probability 49, no. 2 (June 2017): 515–48. http://dx.doi.org/10.1017/apr.2017.11.

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Abstract We consider a two-dimensional optimal dividend problem in the context of two insurance companies with compound Poisson surplus processes, who collaborate by paying each other's deficit when possible. We study the stochastic control problem of maximizing the weighted sum of expected discounted dividend payments (among all admissible dividend strategies) until ruin of both companies, by extending results of univariate optimal control theory. In the case that the dividends paid by the two companies are equally weighted, the value function of this problem compares favorably with the one of merging the two companies completely. We identify the optimal value function as the smallest viscosity supersolution of the respective Hamilton–Jacobi–Bellman equation and provide an iterative approach to approximate it numerically. Curve strategies are identified as the natural analogue of barrier strategies in this two-dimensional context. A numerical example is given for which such a curve strategy is indeed optimal among all admissible dividend strategies, and for which this collaboration mechanism also outperforms the suitably weighted optimal dividend strategies of the two stand-alone companies.
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Dissertations / Theses on the topic "Optimal dividend control problem"

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Prezioso, Luca. "Financial risk sources and optimal strategies in jump-diffusion frameworks." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/254880.

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An optimal dividend problem with investment opportunities, taking into consideration a source of strategic risk is being considered, as well as the effect of market frictions on the decision process of the financial entities. It concerns the problem of determining an optimal control of the dividend under debt constraints and investment opportunities in an economy with business cycles. It is assumed that the company is to be allowed to accept or reject investment opportunities arriving at random times with random sizes, by changing its outstanding indebtedness, which would impact its capital structure and risk profile. This work mainly focuses on the strategic risk faced by the companies; and, in particular, it focuses on the manager's problem of setting appropriate priorities to deploy the limited resources available. This component is taken into account by introducing frictions in the capital structure modification process. The problem is formulated as a bi-dimensional singular control problem under regime switching in presence of jumps. An explicit condition is obtained in order to ensure that the value function is finite. A viscosity solution approach is used to get qualitative descriptions of the solution. Moreover, a lending scheme for a system of interconnected banks with probabilistic constraints of failure is being considered. The problem arises from the fact that financial institutions cannot possibly carry enough capital to withstand counterparty failures or systemic risk. In such situations, the central bank or the government becomes effectively the risk manager of last resort or, in extreme cases, the lender of last resort. If, on the one hand, the health of the whole financial system depends on government intervention, on the other hand, guaranteeing a high probability of salvage may result in increasing the moral hazard of the banks in the financial network. A closed form solution for an optimal control problem related to interbank lending schemes has been derived, subject to terminal probability constraints on the failure of banks which are interconnected through a financial network. The derived solution applies to real bank networks by obtaining a general solution when the aforementioned probability constraints are assumed for all the banks. We also present a direct method to compute the systemic relevance parameter for each bank within the network. Finally, a possible computation technique for the Default Risk Charge under to regulatory risk measurement processes is being considered. We focus on the Default Risk Charge measure as an effective alternative to the Incremental Risk Charge one, proposing its implementation by a quasi exhaustive-heuristic algorithm to determine the minimum capital requested to a bank facing the market risk associated to portfolios based on assets emitted by several financial agents. While most of the banks use the Monte Carlo simulation approach and the empirical quantile to estimate this risk measure, we provide new computational approaches, exhaustive or heuristic, currently becoming feasible, because of both new regulation and the high speed - low cost technology available nowadays.
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Furtado, Guilherme Phillips. "Formulation of impedance control strategy as an optimal control problem." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3152/tde-05022019-153033/.

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A formulation of impedance control for redundant manipulators is developed as a particular case of an optimal control problem. This formulation allows the planning and design of an impedance controller that benets from the stability and eficiency of an optimal controller. Moreover, to circumvent the high computational costs of computing an optimal controller, a sub-optimal feedback controller based on the state-dependent Ricatti equation (SDRE) approach is developed. This approach is then compared with the quadratic programming (QP) control formulation, commonly used to resolve redundancy of robotic manipulators. Numerical simulations of a redundant planar 4-DOF serial link manipulator show that the SDRE control formulation offers superior performance over the control strategy based QP, in terms of stability, performance and required control effort.
Uma formulação do controle de impedância para manipuladores redundantes é desenvolvida como um caso particular de um problema de controle ótimo. Essa formulação permite o planejamento e projeto de um controlador de impedância que se beneficia da estabilidade e eficiência de um controlador ótimo. Para evitar lidar com os elevados custos computacionais de se computar um controlador ótimo, um controlador em malha fechada sub-ótimo, baseado na abordagem das equações de Ricatti dependentes de estado (SDRE), é desenvolvido. Essa abordagem é comparada com a formulação de um controlador baseado em programação quadrática (QP), usualmente utilizado para resolver problemas de redundância em manipuladores robóticos. Simulações numéricas de um manipulador serial plano de quatro graus de liberdade mostram que o controlador baseado em SDRE oferece performance superior em relação a um controlador baseado em programação quadrática, em termos de estabilidade, performance e esforço de controle requerido do atuador.
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Losse, Philip. "The H_infinity Optimal Control Problem for Descriptor Systems." Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-83628.

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The H_infinity control problem is studied for linear constant coefficient descriptor systems. Necessary and sufficient optimality conditions as well as controller formulas are derived in terms of deflating subspaces of even matrix pencils for problems of arbitrary index. A structure preserving method for computing these subspaces is introduced. In combination these results allow the derivation of a numerical algorithm with advantages over the classical methods.
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Tadi, Mohsen. "An optimal control problem for a Timoshenko beam." Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/39868.

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Bondarenko, Oleksandr. "Optimal Control for an Impedance Boundary Value Problem." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/36136.

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We consider the analysis of the scattering problem. Assume that an incoming time harmonic wave is scattered by a surface of an impenetrable obstacle. The reflected wave is determined by the surface impedance of the obstacle. In this paper we will investigate the problem of choosing the surface impedance so that a desired scattering amplitude is achieved. We formulate this control problem within the framework of the minimization of a Tikhonov functional. In particular, questions of the existence of an optimal solution and the derivation of the optimality conditions will be addressed.
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Mukonoweshuro, Rumbidzai Ushendibaba. "The dividend behaviour of NYSE-listed banks within an optimal control theory framework." Thesis, University of Plymouth, 2008. http://hdl.handle.net/10026.1/382.

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Within the dividend policy literature there is no universally accepted model to explain dividend behaviour. The theoretical dividend policy literature contains a promising dynamic mathematical model based on optimal control theory formulated by Davidson (1980), in the spirit of the Modigliani-Brumberg-Yaari types of lifecyle hypothesis, but despite being published some time ago the model has not been tested empirically, possibly due to its complexity. It is the main purpose of this research study to investigate the dividend behaviour patterns of banks listed on the NYSE within this optimal control theory framework. This work unfolds in three stages as follows: initially the impacts of the different control planning horizons in determining dividend patterns are examined. Secondly, the factors that govern the control-theoretic dividend patterns are established. Finally the factors that are associated with out-performers of the control theory framework are identified. Appropriate and relevant data from NYSE banking corporations were obtained to test the effectiveness and efficiency of the control theory framework. The application of logistic regression analysis and logistic step-wise regression established the factors that govern the control-theoretic dividend patterns. The application of multiple regression analysis and step-wise regression analysis enabled this study to determine the factors that are associated with out-performers of the control theory framework. Research findings suggest that the long planning horizon model tends to be good explanator of observed dividends, suggesting that the dividend decision is not constrained by short or medium term predicted liquid asset levels. NYSE banks with control-theoretic dividend patterns were associated with the smaller banks, which perform financially well and display a strong share price record, as indicated by the high Tobin's Q ratio, strong dividend yield, a greater return on capital invested, higher leverage, and a smaller number of employees. The NYSE banks with observed dividends that out-perform the control theory framework are associated with banks that have higher profits, as indicated by the higher return on equity, and an implied expanding customer base, as suggested by the higher revenue growth rate. Outperfoming banks also have higher dividend yields, constrained by an implied internally imposed conservative retention policy, as indicated by lower payout ratios and they tend to be smaller in size. Further research in this area is required to investigate the dividend behaviour of organisations operating on other stock markets around the world, and should help to unlock the full potential that is offered by a control theory framework.
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Jaimoukha, Imad Mahmoud. "The two-block super-optimal distance problem in control." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/46363.

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李澤康 and Chak-hong Lee. "Nonlinear time-delay optimal control problem: optimality conditions and duality." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31212475.

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Lee, Chak-hong. "Nonlinear time-delay optimal control problem : optimality conditions and duality /." [Hong Kong] : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B16391640.

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Chai, Qinqin. "Computational methods for solving optimal industrial process control problems." Thesis, Curtin University, 2013. http://hdl.handle.net/20.500.11937/1227.

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In this thesis, we develop new computational methods for three classes of dynamic optimization problems: (i) A parameter identification problem for a general nonlinear time-delay system; (ii) an optimal control problem involving systems with both input and output delays, and subject to continuous inequality state constraints; and (iii) a max-min optimal control problem arising in gradient elution chromatography.In the first problem, we consider a parameter identification problem involving a general nonlinear time-delay system, where the unknown time delays and system parameters are to be identified. This problem is posed as a dynamic optimization problem, where its cost function is to measure the discrepancy between predicted output and observed system output. The aim is to find unknown time-delays and system parameters such that the cost function is minimized. We develop a gradient-based computational method for solving this dynamic optimization problem. We show that the gradients of the cost function with respect to these unknown parameters can be obtained via solving a set of auxiliary time-delay differential systems from t = 0 to t = T. On this basis, the parameter identification problem can be solved as a nonlinear optimization problem and existing optimization techniques can be used. Two numerical examples are solved using the proposed computational method. Simulation results show that the proposed computational method is highly effective. In particular, the convergence is very fast even when the initial guess of the parameter values is far away from the optimal values.Unlike the first problem, in the second problem, we consider a time delay identification problem, where the input function for the nonlinear time-delay system is piecewise-constant. We assume that the time-delays—one involving the state variables and the other involving the input variables—are unknown and need to be estimated using experimental data. We also formulate the problem of estimating the unknown delays as a nonlinear optimization problem in which the cost function measures the least-squares error between predicted output and measured system output. This estimation problem can be viewed as a switched system optimal control problem with time-delays. We show that the gradient of the cost function with respect to the unknown state delay can be obtained via solving a auxiliary time-delay differential system. Furthermore, the gradient of the cost function with respect to the unknown input delay can be obtained via solving an auxiliary time-delay differential system with jump conditions at the delayed control switching time points. On this basis, we develop a heuristic computational algorithm for solving this problem using gradient based optimization algorithms. Time-delays in two industrial processes are estimated using the proposed computational method. Simulation results show that the proposed computational method is highly effective.For the third problem, we consider a general optimal control problem governed by a system with input and output delays, and subject to continuous inequality constraints on the state and control. We focus on developing an effective computational method for solving this constrained time delay optimal control problem. For this, the control parameterization technique is used to approximate the time planning horizon [0, T] into N subintervals. Then, the control is approximated by a piecewise constant function with possible discontinuities at the pre-assigned partition points, which are also called the switching time points. The heights of the piecewise constant function are decision variables which are to be chosen such that a given cost function is minimized. For the continuous inequality constraints on the state, we construct approximating smooth functions in integral form. Then, the summation of these approximating smooth functions in integral form, which is called the constraint violation, is appended to the cost function to form a new augmented cost function. In this way, we obtain a sequence of approximate optimization problems subject to only boundedness constraints on the decision variables. Then, the gradient of the augmented cost function is derived. On this basis, we develop an effective computational method for solving the time-delay optimal control problem with continuous inequality constraints on the state and control via solving a sequence of approximate optimization problems, each of which can be solved as a nonlinear optimization problem by using existing gradient-based optimization techniques. This proposed method is then used to solve a practical optimal control problem arising in the study of a real evaporation process. The results obtained are highly satisfactory, showing that the proposed method is highly effective.The fourth problem that we consider is a max-min optimal control problem arising in the study of gradient elution chromatography, where the manipulative variables in the chromatographic process are to be chosen such that the separation efficiency is maximized. This problem has three non-standard characteristics: (i) The objective function is nonsmooth; (ii) each state variable is defined over a different time horizon; and (iii) the order of the final times for the state variable, the so-called retention times, are not fixed. To solve this problem, we first introduce a set of auxiliary decision variables to govern the ordering of the retention times. The integer constraints on these auxiliary decision variables are approximated by continuous boundedness constraints. Then, we approximate the control by a piecewise constant function, and apply a novel time-scaling transformation to map the retention times and control switching times to fixed points in a new time horizon. The retention times and control switching times become decision variables in the new time horizon. In addition, the max-min objective function is approximated by a minimization problem subject to an additional constraint. On this basis, the optimal control problem is reduced to an approximate nonlinear optimization problem subject to smooth constraints, which is then solved using a recently developed exact penalty function method. Numerical results obtained show that this approach is highly effective.Finally, some concluding remarks and suggestions for further study are made in the conclusion chapter.
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Books on the topic "Optimal dividend control problem"

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Shlomo, Ta'asan, and Institute for Computer Applications in Science and Engineering., eds. Multigrid one shot methods for optimal control problems, infinite dimensional control. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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The Ulam problem of optimal motion of line segments. New York: Optimization Software, Publications Division, 1985.

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Archibald, T. W. An optimal policy for a two depot inventory problem with stock transfer. Edinburgh: University of Edinburgh, Management School, 1994.

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C, Turner James, and Institute for Computer Applications in Science and Engineering., eds. Finite element approximation of an optimal control problem for the Von Karman equations. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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C, Turner James, and Institute for Computer Applications in Science and Engineering., eds. Finite element approximation of an optimal control problem for the Von Karman equations. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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Center, Langley Research, ed. Optimal control of unsteady stokes flow around a cylinder and the sensor/actuator placement problem. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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Center, Langley Research, ed. Optimal control of unsteady stokes flow around a cylinder and the sensor/actuator placement problem. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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1923-, Thompson Gerald Luther, ed. Optimal control theory: Applications to management science and economics. 2nd ed. Boston: Kluwer Academic Publishers, 2000.

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D, Moerder Daniel, Langley Research Center, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Two time scale output feedback regulation for ill-conditioned systems. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1986.

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A, Batterman, Sachs E. W, and Institute for Computer Applications in Science and Engineering., eds. Approximation of the Newton step by a defect correction process. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1999.

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Book chapters on the topic "Optimal dividend control problem"

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Thießen, Thore, and Jan Vahrenhold. "Klee’s Measure Problem Made Oblivious." In LATIN 2022: Theoretical Informatics, 121–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20624-5_8.

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AbstractWe study Klee’s measure problem — computing the volume of the union of n axis-parallel hyperrectangles in $$\mathbb {R}^d$$ R d — in the oblivious RAM (ORAM) setting. For this, we modify Chan’s algorithm [12] to guarantee memory access patterns and control flow independent of the input; this makes the resulting algorithm applicable to privacy-preserving computation over outsourced data and (secure) multi-party computation.For $$d = 2$$ d = 2 , we develop an oblivious version of Chan’s algorithm that runs in expected $$\mathcal {O}(n \log ^{5/3} n)$$ O ( n log 5 / 3 n ) time for perfect security or $$\mathcal {O}(n \log ^{3/2} n)$$ O ( n log 3 / 2 n ) time for computational security, thus improving over optimal general transformations. For $$d \ge 3$$ d ≥ 3 , we obtain an oblivious version with perfect security while maintaining the $$\mathcal {O}(n^{d/2})$$ O ( n d / 2 ) runtime, i. e., without any overhead.Generalizing our approach, we derive a technique to transform divide-and-conquer algorithms that rely on linear-scan processing into oblivious counterparts. As such, our results are of independent interest for geometric divide-and-conquer algorithms that maintain an order over the input. We apply our technique to two such algorithms and obtain efficient oblivious counterparts of algorithms for inversion counting and computing a closest pair in two dimensions.
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Aschepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Identification Problem." In Optimal Control, 101–6. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49781-5_8.

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Identification Problem." In Optimal Control, 101–5. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_8.

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Locatelli, Arturo. "The LQ problem." In Optimal Control, 21–90. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8328-3_3.

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Locatelli, Arturo. "The LQG problem." In Optimal Control, 91–123. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8328-3_4.

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Aschepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Minimum Time Problem." In Optimal Control, 63–75. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49781-5_5.

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Aschepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "The Observability Problem." In Optimal Control, 91–100. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49781-5_7.

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "The Observability Problem." In Optimal Control, 91–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_7.

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Minimum Time Problem." In Optimal Control, 63–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_5.

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Belov, Mikhail V., and Dmitry A. Novikov. "Enterprise Control Problem." In Optimal Enterprise, 71–118. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003128564-5.

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Conference papers on the topic "Optimal dividend control problem"

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Feng, Runhuan, Shuaiqi Zhang, and Chao Zhu. "Optimal dividend payment problems in piecewise-deterministic compound Poisson risk models." In 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6426672.

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Fabien, Brian C. "Implementation of an Algorithm for the Direct Solution of Optimal Control Problems." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48750.

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This paper presents the implementation of a numerical algorithm for the direct solution of optimal control and parameter identification problems. The problems may include differential equations that define the state, inequality constraints, and equality constraints at the initial and final times. The numerical method is based on transforming the infinite dimensional optimal control problem into a finite dimensional nonlinear programming problem. The transformation technique involves dividing the time interval of interest into a mesh that need not be uniform. In each subinterval of the mesh the control input is approximated using a piecewise polynomial. In particular, the control can be approximated using: (i) piecewise constant, (ii) piecewise linear, or (iii) piecewise cubic polynomials. The explicit Runge-Kutta method is used to obtain an approximate solution of the differential equations that define the state. With the approach used here the states do not appear in the nonlinear programming (NLP) problem. As a result the NLP problem is very compact relative to other numerical methods used to solve nonlinear optimal control problems. The NLP problem is solved using a sequential quadratic programming (SQP) technique. The SQP method is based on minimizing the L1 exact penalty function. Each major step of the SQP method solves a strictly convex quadratic programming problem. The paper also describes a simplified interface to the computer programs that implement the method. An example is presented to demonstrate the algorithm.
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Fung, E. H. K., and D. T. W. Yau. "Optimal Design and Control of a Rotating Flexible Arm With ACLD Treatment." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-41245.

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In this paper, the optimal design and control of a rotating clamped-free flexible arm with fully covered active constrained layer damping (ACLD) treatment are studied. The arm is rotating in a horizontal plane in which the gravitational effect and rotary inertia are neglected. The piezo-sensor voltage is fed back to the piezo-actuator via a PD controller. Finite element method (FEM) in conjunction with Hamilton’s principle is used to derive the governing equations of motion of the system which takes into account the effects of centrifugal stiffening due to the rotation of the beam. The damping behavior of the viscoelastic material (VEM) is modeled using the complex shear modulus method. The design optimization objective is to maximize the sum of the first three open-loop modal damping ratios divided by the weight of the damping treatment. A genetic algorithm, differential evolution (DE), combined with a gradient-based algorithm, sequential quadratic programming (SQP), is used to determine the optimal design variables such as the thickness and storage shear modulus of the VEM core. Next for the determined optimal design variables, the optimal control problem is performed to determine the optimal control gains which minimize a quadratic performance index. The control performance index is normalized with respect to the initial conditions and the optimal control problem is posed to solve a min-max optimization problem. The results of this study will be useful in the optimal design and control of adaptive and smart rotating structures such as rotorcraft blades or robotic arms.
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Nakhaie-Jazar, Gholamreza, A. H. Naghshineh-Poor, and K. Ravanbakhsh. "Energy Optimal Control Algorithm Based on Central Difference Approximation of Equation of Motion With Application to Robot Control." In ASME 1992 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/cie1992-0131.

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Abstract Optimal control of robotic manipulator has a complex nature. Many different control and optimal control algorithms have been developed. However, these algorithms are either based on simplified equation of motion or are tedious to implement to set up. In this work the equations of motion are approximated by central difference technic and Taylor series expansion, while path of motion is divided in finite segments. The motion is assumed to have zero velocity at beginning and at the end of the motion, without loss of generality. The whole time and path of motion is arbitrary, but fixed, after the option. The problem of energy optimal control is reduced to minimizing a scalar function of many but finite variables with equality and inequality constraints. By applying modified Hooke and Jeeves method, actuator torques at any time are calculated. The preparation time for problem set up and execution time are small, and programming efforts are reasonably low. The algorithm is implemented for a 2R and 3R robotic manipulator, and results are presented.
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Zomorodi Moghadam, Hesam, Robert G. Landers, and S. N. Balakrishnan. "Hierarchical Optimal Force–Position Control of Complex Manufacturing Processes." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7234.

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A hierarchical optimal controller is developed to regulate the cutting force and tool position, simultaneously, in a micro end milling process. The process is divided into two levels of decision making. The bottom level includes the measurable states, which in this work comprise the servomechanism positions. The top level includes the higher order objectives which can be derived from the bottom level objectives by an aggregation relationship. In this work the top level objective is concerned with cutting force regulation. The aggregation relations are linearized to fit into a linear optimal control problem to reduce the computational efforts. Reference velocity is calculated based on the force model, using the desired depth-of-cut and spindle speed. The proposed method is compared to a normal optimal controller without considering the top level objectives. Comparison between the two methods reveals the advantages of considering the top level objectives.
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Patel, Rushabh, Paolo Frasca, and Francesco Bullo. "Centroidal Area-Constrained Partitioning for Robotic Networks." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3742.

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We consider the problem of optimal coverage with area-constraints in a mobile multi-agent system. For a planar environment with an associated density function, this problem is equivalent to dividing the environment into optimal subregions such that each agent is responsible for the coverage of its own region. In this paper, we design a continuous-time distributed policy which allows a team of agents to achieve a convex area-constrained partition of a convex workspace. Our work is related to the classic Lloyd algorithm, and makes use of generalized Voronoi diagrams. We also discuss practical implementation for real mobile networks. Simulation methods are presented and discussed.
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Bahrami, Mohsen, and G. R. Nakhaie Jazar. "Robotic Manipulator Optimal Control Algorithm Based on Central Difference Approximation of Equation of Motion." In ASME 1991 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/cie1991-0170.

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Abstract The complex nature of robotic manipulator dynamic equations is well studied. Many different control algorithms have been developed; among them optimal control ones. However, most of them are either based on simplified equations of motion or are tedious to implement or set up. In this work equations of motion are approximated using central difference technics and Taylor series expansion, while path of motion is divided in finite segments. The motion is assumed to have zero velocity at the beginning and at the end of the motion without loss of generality. Showing that Pontryagin principle is applicable and the optimal controller is bang bang. Actuator torques, iscolines, and switching points, can be calculated. The preparation time, problem set up and execution time are relatively small, and programming efforts are reasonably low. The algorithm is implemented for a 2R planar robotic manipulator, and results are presented.
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Kapania, Nitin R., John Subosits, and J. Christian Gerdes. "A Sequential Two-Step Algorithm for Fast Generation of Vehicle Racing Trajectories." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9757.

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The problem of maneuvering a vehicle through a race course in minimum time requires computation of both longitudinal (brake and throttle) and lateral (steering wheel) control inputs. Unfortunately, solving the resulting nonlinear optimal control problem is typically computationally expensive and infeasible for real-time trajectory planning. This paper presents an iterative algorithm that divides the path generation task into two sequential subproblems that are significantly easier to solve. Given an initial path through the race track, the algorithm runs a forward-backward integration scheme to determine the minimum-time longitudinal speed profile, subject to tire friction constraints. With this speed profile fixed, the algorithm updates the vehicle’s path by solving a convex optimization problem that minimizes the resulting path curvature while staying within track boundaries and obeying affine, time-varying vehicle dynamics constraints. This two-step process is repeated iteratively until the predicted lap time no longer improves. While providing no guarantees of convergence or a globally optimal solution, the approach performs well when tested on the Thunderhill Raceway course in Willows, CA. The lap time reaches a minimum value after only three iterations, with each iteration over the full 5 km race course requiring only thirty seconds of computation time on a laptop computer. The resulting vehicle path and speed profile match very well with a nonlinear gradient descent solution and a path driven by a professional racecar driver, indicating that the proposed method is a viable option for online trajectory planning in the near future.
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Upadhyaya, B. R., S. R. P. Perillo, X. Xu, and F. Li. "Advanced Control Design, Optimal Sensor Placement, and Technology Demonstration for Small and Medium Nuclear Power Reactors." In 17th International Conference on Nuclear Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/icone17-75343.

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The efficient and safe performance of nuclear power plants of the future requires remote monitoring, control, and condition-based maintenance in order to maximize their capacity factor. Small and medium reactors, in the 50–500 MWe power range, may become commonplace for certain applications, with a design features for remote deployment. Such a reactor may be part of a smaller electrical grid, and deployed in areas with limited infrastructure. Typical applications include power generation, process heat for water desalination, and co-generation. There are other considerations in the deployment of these reactors: development of effective I&C to support nuclear fuel security monitoring, longer than normal fuel cycle length, and increased autonomy in plant operation and maintenance. A Model Predictive Controller (MPC) for the IRIS (International Reactor Innovative and Secure) system has been developed as a multivariate control strategy for reactor power regulation and the control of the helical coil steam generator (HCSG) used in IRIS. A MATLAB-SIMULINK model of the integral reactor was developed and used to demonstrate the design of the MPC. The two major control actions are the control rod reactivity perturbation and the steam control valve setting. The latter is used to regulate the set point value of the superheated steam. The MPC technique minimizes the necessity of on-line controller tuning, and is highly effective for remote and autonomous control actions. As an important part of the instrumentation & control (I&C) strategy, sensor placement in next generation reactors needs to be addressed for both control design and fault diagnosis. This approach is being applied to the IRIS system to enhance the efficiency of reactor monitoring that would assist in a quick and accurate identification of faults. This is achieved by solving the problem from the fault diagnosis perspective, rather than treating the sensor placement as a pure optimization problem. The solution to the problem of sensor placement may be broadly divided into two tasks: (1) fault modeling or prediction of cause-effect behavior of the system, generating a set of variables that are affected whenever a fault occurs, and (2) use of the generated sets to identify sensor locations based on various design criteria, such as observability, resolution, reliability, etc. The proposed algorithm is applied to the design of a sensor network for the IRIS system using multiple design criteria. This enables the designer to obtain a good preliminary design without extensive quantitative information about the process. The control technique will be demonstrated by application to a real process with actuators and associated device time delays. A multivariate flow control loop has been developed with the objective of demonstrating digital control implementation using proportional-integral controllers for water level regulation in coupled tanks. The controller implementation includes self-tuning, control mode selection under device or instrument fault, automated learning, on-line fault monitoring and failure anticipation, and supervisory control. The paper describes the integration of control strategies, fault-tolerant control, and sensor placement for the IRIS system, and demonstration of the technology using an experimental control loop.
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Li, Li-Li, Jinghai Feng, and Lixin Song. "On the Optimal Dividend Problem for the Dual Jump-Diffusion Model." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.2418.

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Reports on the topic "Optimal dividend control problem"

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Chi, Hongmei, and Yanzhao Cao. Numerical Solution of Optimal Control Problem under SPDE Constraints. Fort Belvoir, VA: Defense Technical Information Center, October 2011. http://dx.doi.org/10.21236/ada564030.

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Molotylnikova, Vira. MODERN TYPES OF BODY RELAXATION METHODS AFTER INTENSE PHYSICAL EXERTION. Intellectual Archive, November 2022. http://dx.doi.org/10.32370/iaj.2748.

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The article presents varieties and variants of relaxation techniques advisable to use after intense physical exertion. The concept of "relaxation" and understanding of its role in physical education to maintain health and harmonious development of youth are considered. Considering the fact that one of the main trends in sports remains the increase in the intensity of training and the need to improve the results of competitions, the problem of restoring the athlete's performance capacity after physical exertion is extremely relevant today. Understanding the causes of fatigue and the physiological mechanisms of recovery, control over the relevant processes, the rational use of modern methods of body relaxation and means of recovery are important for assessing the impact of physical stress on the body, the effectiveness of training programs, identifying overtraining, determining the optimal rest time after physical exercises, and therefore, are necessary to improve the athlete's training and achieving high results.
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Lagutin, Andrey, and Tatyana Sidorina. SYSTEM OF FORMATION OF PROFESSIONAL AND PERSONAL SELF-GOVERNMENT AMONG CADETS OF MILITARY INSTITUTES. Science and Innovation Center Publishing House, December 2020. http://dx.doi.org/10.12731/self-government.

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When carrying out professional activities, officers of the VNG of the Russian Federation are often in difficult, stressful, emotionally stressful situations associated with the use of weapons as a particularly dangerous means of destruction. The right to use a weapon by an officer makes him responsible for its use. And therefore requires the officer to make a balanced optimal decision, which is associated with the risk and transience of events, and in which no mistake can be made, since the price of it can be someone's life. It is at such a moment that it is important that the officer has stable skills in making a decision on the use of weapons, and this requires skills not only in managing subordinates or the situation,but in managing himself. The complication of the military-professional activity, manifested in the need to develop the ability to quickly and accurately make command decisions, exacerbating the problem of social responsibility of an officer who has the management of unit that leads to an understanding of his singular personal and professional responsibility, as the ability to govern themselves makes it possible to achieve a positive result of the Department for the DBA. This characterizes the need for a commander to have the ability to manage himself, as a "system" that manages others. Forming skills of self-control, patience, compassion, having mastered algorithms of making managerial decisions, the cycle of implementing managerial functions, etc., a person comes to the belief: "before effectively managing others, it is necessary to learn how to manage yourself." The required level of personal and professional maturity can be formed in a person as a result of purposeful self-management, which determines the special role of professional and personal self-management in the training of future officers.
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An Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0741.

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Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form. The output non-linearities can be approximated using a quadratic model, which creates a problem in the linear-quadratic framework. This facilitates the direct application of linear control approaches such as LQR control, predictive control, or Model Predictive Control (MPC). The paper demonstrates the approach using the ELectrified Vehicle library for sImulation and Optimization (ELVIO). It is an open-source MATLAB/Simulink library designed for the quick and easy simulation and optimization of different powertrain and drivetrain architectures. It follows a modelling methodology that combines backward-facing and forward-facing signal path, which means that no driver model is required. The results show that the approximated solution provides a performance that is very close to the solution of the original problem except for extreme parts of the operating range (in which case the solution tends to be driven by constraints anyway).
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