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Relevant bibliographies by topics / Nonlinear optimal control

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Academic literature on the topic 'Nonlinear optimal control'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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Journal articles on the topic "Nonlinear optimal control"

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Goncharenko, Borys, Larysa Vikhrova, and Mariia Miroshnichenko. "Optimal control of nonlinear stationary systems at infinite control time." Central Ukrainian Scientific Bulletin. Technical Sciences, no. 4(35) (2021): 88–93. http://dx.doi.org/10.32515/2664-262x.2021.4(35).88-93.

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The article presents a solution to the problem of control synthesis for dynamical systems described by linear differential equations that function in accordance with the integral-quadratic quality criterion under uncertainty. External perturbations, errors and initial conditions belong to a certain set of uncertainties. Therefore, the problem of finding the optimal control in the form of feedback on the output of the object is presented in the form of a minimum problem of optimal control under uncertainty. The problem of finding the optimal control and initial state, which maximizes the quality criterion, is considered in the framework of the optimization problem, which is solved by the method of Lagrange multipliers after the introduction of the auxiliary scalar function - Hamiltonian. The case of a stationary system on an infinite period of time is considered. The formulas that can be used for calculations are given for the first and second variations. It is proposed to solve the problem of control search in two stages: search of intermediate solution at fixed values of control and error vectors and subsequent search of final optimal control. The solution of -optimal control for infinite time taking into account the signal from the compensator output is also considered, as well as the solution of the corresponding matrix algebraic equations of Ricatti type.

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Fernández de la Vega, Constanza S., Richard Moore, Mariana Inés Prieto, and Diego Rial. "Optimal control problem for nonlinear optical communications systems." Journal of Differential Equations 346 (February 2023): 347–75. http://dx.doi.org/10.1016/j.jde.2022.11.050.

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Yang, J. N., F. X. Long, and D. Wong. "Optimal Control of Nonlinear Structures." Journal of Applied Mechanics 55, no. 4 (December 1, 1988): 931–38. http://dx.doi.org/10.1115/1.3173744.

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Three optimal control algorithms are proposed for reducing oscillations of flexible nonlinear structures subjected to general stochastic dynamic loads, such as earthquakes, waves, winds, etc. The optimal control forces are determined analytically by minimizing a time-dependent quadratic performance index, and nonlinear equations of motion are solved using the Wilson-θ numerical procedures. The optimal control algorithms developed for applications to nonlinear structures are referred to as the instantaneous optimal control algorithms, including the instantaneous optimal open-loop control algorithm, instantaneous optimal closed-loop control algorithm, and instantaneous optimal closed-open-loop control algorithm. These optimal algorithms are computationally efficient and suitable for on-line implementation of active control systems to realistic nonlinear structures. Numerical examples are worked out to demonstrate the applications of these optimal control algorithms to nonlinear structures. In particular, control of structures undergoing inelastic deformations under strong earthquake excitations are illustrated. The advantage of using combined passive/active control systems is also demonstrated.

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Akyurek, Alper Sinan, and Tajana Simunic Rosing. "Optimal Distributed Nonlinear Battery Control." IEEE Journal of Emerging and Selected Topics in Power Electronics 5, no. 3 (September 2017): 1045–54. http://dx.doi.org/10.1109/jestpe.2016.2645480.

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Kaczorek, Tadeusz. "Nonlinear and optimal control systems." Control Engineering Practice 5, no. 12 (December 1997): 1781. http://dx.doi.org/10.1016/s0967-0661(97)87397-2.

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Lu, Q., Y. Sun, Z. Xu, and T. Mochizuki. "Decentralized nonlinear optimal excitation control." IEEE Transactions on Power Systems 11, no. 4 (1996): 1957–62. http://dx.doi.org/10.1109/59.544670.

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Hualin Tan and W. J. Rugh. "Pseudolinearization and nonlinear optimal control." IEEE Transactions on Automatic Control 43, no. 3 (March 1998): 386–91. http://dx.doi.org/10.1109/9.661596.

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Loxton, Ryan, Qun Lin, and Kok Lay Teo. "Minimizing control variation in nonlinear optimal control." Automatica 49, no. 9 (September 2013): 2652–64. http://dx.doi.org/10.1016/j.automatica.2013.05.027.

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Hassanzadeh, Iraj, Ghasem Alizadeh, Naser Pourqorban Shirjoposht, and Farzad Hashemzadeh. "A New Optimal Nonlinear Approach to Half Car Active Suspension Control." International Journal of Engineering and Technology 2, no. 1 (2010): 78–84. http://dx.doi.org/10.7763/ijet.2010.v2.104.

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Esteve-Yagüe, Carlos, Borjan Geshkovski, Dario Pighin, and Enrique Zuazua. "Turnpike in Lipschitz—nonlinear optimal control." Nonlinearity 35, no. 4 (February 17, 2022): 1652–701. http://dx.doi.org/10.1088/1361-6544/ac4e61.

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Abstract We present a new proof of the turnpike property for nonlinear optimal control problems, when the running target is a steady control-state pair of the underlying system. Our strategy combines the construction of quasi-turnpike controls via controllability, and a bootstrap argument, and does not rely on analyzing the optimality system or linearization techniques. This in turn allows us to address several optimal control problems for finite-dimensional, control-affine systems with globally Lipschitz (possibly nonsmooth) nonlinearities, without any smallness conditions on the initial data or the running target. These results are motivated by applications in machine learning through deep residual neural networks, which may be fit within our setting. We show that our methodology is applicable to controlled PDEs as well, such as the semilinear wave and heat equation with a globally Lipschitz nonlinearity, once again without any smallness assumptions.

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Dissertations / Theses on the topic "Nonlinear optimal control"

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Zhu, Jinghao. "Some results on nonlinear optimal control." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-10042006-143910/.

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Zhang, Xiaohong. "Optimal feedback control for nonlinear discrete systems and applications to optimal control of nonlinear periodic ordinary differential equations." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/40185.

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Gavriel, Christos. "Higher order conditions in nonlinear optimal control." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9042.

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The most widely used tool for the solution of optimal control problems is the Pontryagin Maximum Principle. But the Maximum Principle is, in general, only a necessary condition for optimality. It is therefore desirable to have supplementary conditions, for example second order sufficient conditions, which confirm optimality (at least locally) of an extremal arc, meaning one that satisfies the Maximum Principle. Standard second order sufficient conditions for optimality, when they apply, yield the information not only that the extremal is locally minimizing, but that it is also locally unique. There are problems of interest, however, where minimizers are not locally unique, owing to the fact that the cost is invariant under small perturbations of the extremal of a particular structure (translations, rotations or time-shifting). For such problems the standard second order conditions can never apply. The first contribution of this thesis is to develop new second order conditions for optimality of extremals which are applicable in some cases of interest when minimizers are not locally unique. The new conditions can, for example, be applied to problems with periodic boundary conditions when the cost is invariant under time translations. The second order conditions investigated here apply to normal extremals. These extremals satisfy the conditions of the Maximum Principle in normal form (with the cost multiplier taken to be 1). It is, therefore, of interest to know when the Maximum Principle applies in normal form. This issue is also addressed in this thesis, for optimal control problems that can be expressed as calculus of variations problems. Normality of the Maximum Principle follows from the fact that, under the regularity conditions developed, the highest time derivative of an extremal arc is essentially bounded. The thesis concludes with a brief account of possible future research directions.

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Primbs, James A. Doyle John Comstock. "Nonlinear optimal control : a receding horizon approach /." Diss., Pasadena, Calif. : California Institute of Technology, 1999. http://resolver.caltech.edu/CaltechETD:etd-10172005-103315.

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Tigrek, Tuba. "Nonlinear adaptive optimal control of HVAC systems." Thesis, University of Iowa, 2001. https://ir.uiowa.edu/etd/3429.

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Chudoung, Jerawan. "Robust Control for Hybrid, Nonlinear Systems." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26983.

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We develop the robust control theories of stopping-time nonlinear systems and switching-control nonlinear systems. We formulate a robust optimal stopping-time control problem for a state-space nonlinear system and give the connection between various notions of lower value function for the associated game (and storage function for the associated dissipative system) with solutions of the appropriate variational inequality (VI). We show that the stopping-time rule can be obtained by solving the VI in the viscosity sense. It also happens that a positive definite supersolution of the VI can be used for stability analysis. We also show how to solve the VI for some prototype examples with one-dimensional state space. For the robust optimal switching-control problem, we establish the Dynamic Programming Principle (DPP) for the lower value function of the associated game and employ it to derive the appropriate system of quasivariational inequalities (SQVI) for the lower value vector function. Moreover we formulate the problem in the <I>L</I><sub>2</sub>-gain/dissipative system framework. We show that, under appropriate assumptions, continuous switching-storage (vector) functions are characterized as viscosity supersolutions of the SQVI, and that the minimal such storage function is equal to the lower value function for the game. We show that the control strategy achieving the dissipative inequality is obtained by solving the SQVI in the viscosity sense; in fact this solution is also used to address stability analysis of the switching system. In addition we prove the comparison principle between a viscosity subsolution and a viscosity supersolution of the SQVI satisfying a boundary condition and use it to give an alternative derivation of the characterization of the lower value function. Finally we solve the SQVI for a simple one-dimensional example by a direct geometric construction.<br>Ph. D.

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Meum, Patrick. "Optimal Reservoir control using nonlinear MPC and ECLIPSE." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9610.

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<p>Recent years advances within well deployment and instrumentation technology offers huge potentials for increased oil recovery from reservoir production. Wells can now be equipped with controllable valves at reservoir depth, which may possibly alter the production profitability of the field completely, if the devices are used in an intelligent manner. This thesis investigates this potential by using model predictive control to maximize reservoir production performance and total oil production. The report describes an algorithm for nonlinear model predictive control, using a single shooting, multistep, quasi-Newton method, and implements it on an existing industrial MPC platform - Statoil's in-house MPC tool SEPTIC. The method is an iterative method, solving a series of quadratic problems analogous to sequential quadratic programming, to find the optimal control settings. An interface between SEPTIC and a commercial reservoir simulator, ECLIPSE, is developed for process modelling and predictions. ECLIPSE provides highly realistic and detailed reservoir behaviour and is used by SEPTIC to obtain numerical gradients for optimization. The method is applied to two reservoir examples, Case 1 and Case 2, and develops optimal control strategies for each of these. The two examples have conceptually different model structures. Case 1 is a simple introduction model. Case 2 is a benchmark model previously used in Yeten, Durlofsky and Aziz (2002) and models a North Sea type channelized reservoir. It is described by a set of different realizations, to capture a notion of model uncertainty. The report addresses each of the available realizations and shows how the value of an optimal production strategy can vary for equally probable realizations. Improvements in reservoir production performance using the model predictive control method are shown for all cases, compared to basic controlled references cases. For the benchmark example improvements range up to as much as 68% increase in one realization, and 30% on average for all realizations. This is an increase from the results previously published for the benchmark, with a 3% average. However, the level of improvement shows significant variation, and is only marginal for example Case 1. A thorough field analysis should therefore be performed before deciding to take the extra cost of well equipment and optimal control.</p>

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Dong, Wenjie. "Self-organizing and optimal control for nonlinear systems." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359894.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 82-87). Issued in print and online. Available via ProQuest Digital Dissertations.

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Blanchard, Eunice Anita. "Exact penalty methods for nonlinear optimal control problems." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/1805.

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Research comprised of developing solution techniques to three classes of non-standard optimal control problems, namely: optimal control problems with discontinuous objective functions arising in aquaculture operations; impulsive optimal control problems with minimum subsystem durations; optimal control problems involving dual-mode hybrid systems with state-dependent switching conditions. The numerical algorithms developed involved an exact penalty approach to transform the constrained problem into an unconstrained problem which was readily solvable by a standard optimal control software.

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Jorge, Tiago R., João M. Lemos, and Miguel Barão. "Optimal Control for Vehicle Cruise Speed Transfer." Bachelor's thesis, ACTAPRESS, 2011. http://hdl.handle.net/10174/4513.

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The contribution of this paper consists in a procedure to solve the optimal cruise control problem that consists in transferring the car velocity between two specified values, in a fixed interval of time, with minimum fuel consumption. The solution is obtained by applying a recursive numerical algorithm that provides an approximation to the condition provided by Pontryagin’s Optimum Principle. This solution is compared with the one obtained by using a reduced complexity linear model for the car dynamics that allows an exact (“analytical”) solution of the corresponding optimal control problem. This work has been performed within the framework of activity 2.4.1 – Smart drive control of project SE2A - Nanoelectronics for Safe, Fuel Efficient and Environment Friendly Automotive Solutions, ENIAC initiative.

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Books on the topic "Nonlinear optimal control"

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Grass, Dieter, Jonathan P. Caulkins, Gustav Feichtinger, Gernot Tragler, and Doris A. Behrens. Optimal Control of Nonlinear Processes. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-77647-5.

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Agrachev, Andrei A., A. Stephen Morse, Eduardo D. Sontag, Héctor J. Sussmann, and Vadim I. Utkin. Nonlinear and Optimal Control Theory. Edited by Paolo Nistri and Gianna Stefani. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-77653-6.

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1946-, Sussmann Hector J., ed. Nonlinear controllability and optimal control. New York: M. Dekker, 1990.

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Vincent, Thomas L. Nonlinear and optimal control systems. New York: Wiley, 1997.

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Wei, Qinglai, Ruizhuo Song, Benkai Li, and Xiaofeng Lin. Self-Learning Optimal Control of Nonlinear Systems. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-4080-1.

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P, Banks Stephen. Optimal control and stabilization for nonlinear systems. Sheffield: University of Sheffield, Dept. of Control Engineering, 1991.

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P, Banks Stephen. On the optimal control of nonlinear systems. Sheffield: University, Dept. of Control Engineering, 1985.

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Gunzburger, Max D. Finite dimensional approximation of a class of constrained nonlinear optimal control problems. Hampton, Va: Institute for Computer Applications in Science and Engineering, 1994.

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E, Helfrich Clifford, and United States. National Aeronautics and Space Administration., eds. Robust neighboring optimal guidance for the advanced launch system. [Austin, Tex.]: Guidance and Control Group, Dept. of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, 1993.

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Haldun, Direskeneli, Taylor Deborah B, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. A stochastic optimal feedforward and feedback control methodology for superagility. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Program, 1992.

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Book chapters on the topic "Nonlinear optimal control"

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Kagiwada, Harriet, Robert Kalaba, Nima Rasakhoo, and Karl Spingarn. "Optimal Control." In Numerical Derivatives and Nonlinear Analysis, 35–109. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-5056-9_3.

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Chernousko, Felix L., Igor M. Ananievski, and Sergey A. Reshmin. "Optimal control." In Control of Nonlinear Dynamical Systems, 11–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-70784-4_1.

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Andrei, Neculai. "Optimal Control." In Nonlinear Optimization Applications Using the GAMS Technology, 287–322. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-6797-7_12.

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Löber, Jakob. "Optimal Control." In Optimal Trajectory Tracking of Nonlinear Dynamical Systems, 79–118. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46574-6_3.

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Chernousko, Felix L. "Decomposition and Feedback Control of Nonlinear Dynamic Systems." In Optimal Control, 163–71. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_12.

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Tomás-Rodríguez, María, and Stephen P. Banks. "Optimal Control." In Linear, Time-varying Approximations to Nonlinear Dynamical Systems, 101–21. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-101-1_6.

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Arutyunov, Aram, Dmitry Karamzin, and Fernando Lobo Pereira. "General Nonlinear Impulsive Control Problems." In Optimal Impulsive Control, 153–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02260-0_7.

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Kupfer, F. S., and E. W. Sachs. "Reduced SQP Methods for Nonlinear Heat Conduction Control Problems." In Optimal Control, 145–60. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_11.

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Pervozvanskii, A. A., and V. G. Gaitsgori. "Nonlinear Optimal Control Problems." In Theory of Suboptimal Decisions, 306–67. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2833-6_6.

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Tröltzsch, Fredi. "Semidiscrete Ritz-Galerkin Approximation of Nonlinear Parabolic Boundary Control Problems." In Optimal Control, 57–68. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_5.

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Conference papers on the topic "Nonlinear optimal control"

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McLain, Timothy W., and Randal W. Beard. "Nonlinear Optimal Control of a Hydraulically Actuated Positioning System." In ASME 1997 International Mechanical Engineering Congress and Exposition, 163–68. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-1297.

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Abstract In this paper, the nonlinear optimal control problem is formulated for the position control of an electrohydraulic servo system. The optimal control is given by the solution to the Hamilton-Jacobi-Bellman equation, which in this case cannot be solved explicitly. An alternative method, based upon successive Galerkin approximation, is used to obtain an approximate optimal solution. Preliminary simulation results, demonstrating the application of this approach to the position control of a hydraulically actuated device, are presented.

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Memon, Attaullah Y. "Optimal output regulation of minimum phase nonlinear systems." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334679.

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Nie, Yuanbo, and Eric C. Kerrigan. "Efficient Implementation of Rate Constraints for Nonlinear Optimal Control." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516847.

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Hu, Yi, Peng Zhang, Cibo Lou, Weiyu Huang, Jingjun Xu, and Zhigang Chen. "Optimal control of the ballistic trajectory of Airy beams." In Nonlinear Photonics. Washington, D.C.: OSA, 2010. http://dx.doi.org/10.1364/np.2010.ntuc30.

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Lu, Ping, and Frank Chavez. "Nonlinear Optimal Guidance." In AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-6079.

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Rigatos, G., and Masoud Abbaszadeh. "Nonlinear Optimal Control for a Cells Signaling Pathway Model Under Time-Delays." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516752.

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Best, M. C. "Nonlinear optimal control of vehicle driveline vibrations." In UKACC International Conference on Control (CONTROL '98). IEE, 1998. http://dx.doi.org/10.1049/cp:19980307.

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Haddad, W. M., V. S. Chellaboina, J. L. Fausz, and A. Leonessa. "Optimal nonlinear robust control for nonlinear uncertain cascade systems." In Proceedings of 16th American CONTROL Conference. IEEE, 1997. http://dx.doi.org/10.1109/acc.1997.611828.

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Haddad, W. M., V. S. Chellaboina, and J. L. Fausz. "Optimal nonlinear disturbance rejection control for nonlinear cascade systems." In Proceedings of 16th American CONTROL Conference. IEEE, 1997. http://dx.doi.org/10.1109/acc.1997.611838.

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Yao Li, William S. Levine, Yonghong Yang, and Chengqi He. "A nonlinear optimal human postural regulator." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5991184.

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Reports on the topic "Nonlinear optimal control"

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Oates, William S., and Ralph C. Smith. Nonlinear Optimal Control of Plate Structures Using Magnetostrictive Actuators. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada443741.

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Oates, William S., and Ralph C. Smith. Nonlinear Optimal Tracking Control of a Piezoelectric Nanopositioning Stage. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada443786.

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Kath, William L., and Gregory G. Luther. Modeling and Control of Nonlinear Optical Wavelength Conversion. Fort Belvoir, VA: Defense Technical Information Center, October 2001. http://dx.doi.org/10.21236/ada419572.

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Steel, Duncan G. The Coherent Nonlinear Optical Response and Control of Single Quantum Dots. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada437780.

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Steel, Duncan G. Nano-Optics: Coherent Nonlinear Optical Response and Control of Single Quantum Dots. Fort Belvoir, VA: Defense Technical Information Center, April 2002. http://dx.doi.org/10.21236/ada402598.

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Lambropoulos, P. [Coherent control of photoabsorption processes and calculation of nonlinear optical processes]. Final technical report. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/631276.

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Steel, Duncan G. Working Beyond Moore's Limit - Coherent Nonlinear Optical Control of Individual and Coupled Single Electron Doped Quantum Dots. Fort Belvoir, VA: Defense Technical Information Center, July 2015. http://dx.doi.org/10.21236/ad1003429.

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