Relevant bibliographies by topics / Optimal control theory

Academic literature on the topic 'Optimal control theory'

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Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Optimal control theory"

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James, M. R. "Optimal Quantum Control Theory." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 343–67. http://dx.doi.org/10.1146/annurev-control-061520-010444.

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This article explains some fundamental ideas concerning the optimal control of quantum systems through the study of a relatively simple two-level system coupled to optical fields. The model for this system includes both continuous and impulsive dynamics. Topics covered include open- and closed-loop control, impulsive control, open-loop optimal control, quantum filtering, and measurement feedback optimal control.
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Werschnik, J., and E. K. U. Gross. "Quantum optimal control theory." Journal of Physics B: Atomic, Molecular and Optical Physics 40, no. 18 (September 4, 2007): R175—R211. http://dx.doi.org/10.1088/0953-4075/40/18/r01.

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Daund, Arvind, Shrihari Mahishi, and Nirnay Berde. "Synchronization of Parallel Dual Inverted Pendulums using Optimal Control Theory." SIJ Transactions on Advances in Space Research & Earth Exploration 2, no. 2 (April 11, 2014): 7–11. http://dx.doi.org/10.9756/sijasree/v2i2/0202520301.

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CHERRUAULT, Y., and J. GALLEGO. "INTRODUCTION TO OPTIMAL CONTROL THEORY." Kybernetes 14, no. 3 (March 1985): 151–56. http://dx.doi.org/10.1108/eb005712.

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Zelikin, M. I., D. D. Kiselev, and L. V. Lokutsievskiy. "Optimal control and Galois theory." Sbornik: Mathematics 204, no. 11 (November 30, 2013): 1624–38. http://dx.doi.org/10.1070/sm2013v204n11abeh004352.

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Martínez, Eduardo. "Reduction in optimal control theory." Reports on Mathematical Physics 53, no. 1 (February 2004): 79–90. http://dx.doi.org/10.1016/s0034-4877(04)90005-5.

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Yong, Jiongmin. "Infinite dimensional optimal control theory." IFAC Proceedings Volumes 32, no. 2 (July 1999): 2778–89. http://dx.doi.org/10.1016/s1474-6670(17)56473-3.

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FUKUSHIMA, Naoto, Syo OTA, Mehmet Selcuk ARSLAN, and Ichiro HAGIWARA. "B10 Energy Optimal Control Theory : An Optimal Control Theory Based on a New Framework of Control Problem." Proceedings of the Symposium on the Motion and Vibration Control 2009.11 (2009): 109–13. http://dx.doi.org/10.1299/jsmemovic.2009.11.109.

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Pant, D. K., R. D. Coalson, M. I. Hernandez, and J. Campos-Martinez. "Optimal control theory for the design of optical waveguides." Journal of Lightwave Technology 16, no. 2 (1998): 292–300. http://dx.doi.org/10.1109/50.661023.

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Herrmann, Avriel A., and Joseph Z. Ben-Asher. "Flight Control Law Clearance Using Optimal Control Theory." Journal of Aircraft 53, no. 2 (March 2016): 515–29. http://dx.doi.org/10.2514/1.c033517.

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Dissertations / Theses on the topic "Optimal control theory"

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Bellon, James. "Riccati Equations in Optimal Control Theory." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/math_theses/46.

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It is often desired to have control over a process or a physical system, to cause it to behave optimally. Optimal control theory deals with analyzing and finding solutions for optimal control for a system that can be represented by a set of differential equations. This thesis examines such a system in the form of a set of matrix differential equations known as a continuous linear time-invariant system. Conditions on the system, such as linearity, allow one to find an explicit closed form finite solution that can be more efficiently computed compared to other known types of solutions. This is done by optimizing a quadratic cost function. The optimization leads to solving a Riccati equation. Conditions are discussed for which solutions are possible. In particular, we will obtain a solution for a stable and controllable system. Numerical examples are given for a simple system with 2x2 matrix coefficients.
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Yiu, Ka Fai Cedric. "Aerodynamic design via optimal control theory." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317867.

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Zenios, Stefanos A. (Stefanos Andrea). "Health care applications of optimal control theory." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/11042.

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Silva, Francisco Jose. "Interior penalty approximation for optimal control problems. Optimality conditions in stochastic optimal control theory." Palaiseau, Ecole polytechnique, 2010. http://pastel.archives-ouvertes.fr/docs/00/54/22/95/PDF/tesisfjsilva.pdf.

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Résumé français : Cette thèse est divisée en deux parties. Dans la première partie on s'intéresse aux problèmes de commande optimale déterministes et on étudie des approximations intérieures pour deux problèmes modèles avec des contraintes de non-négativité sur la commande. Le premier modèle est un problème de commande optimale dont la fonction de coût est quadratique et dont la dynamique est régie par une équation différentielle ordinaire. Pour une classe générale de fonctions de pénalité intérieure, on montre comment calculer le terme principal du développement ponctuel de l'état et de l'état adjoint. Notre argument principal se fonde sur le fait suivant: si la commande optimale pour le problème initial satisfait les conditions de complémentarité stricte pour le Hamiltonien sauf en un nombre fini d'instants, les estimations pour le problème de commande optimale pénalisé peuvent être obtenues à partir des estimations pour un problème stationnaire associé. Nos résultats fournissent plusieurs types de mesures de qualité de l'approximation pour la technique de pénalisation: estimations des erreurs de la commande , estimations des erreurs pour l'état et l'état adjoint et aussi estimations de erreurs pour la fonction valeur. Le second modèle est le problème de commande optimale d'une équation semi-linéaire elliptique avec conditions de Dirichlet homogène au bord, la commande étant distribuée sur le domaine et positive. L'approche est la même que pour le premier modèle, c'est-à-dire que l'on considère une famille de problèmes pénalisés, dont la solution définit une trajectoire centrale qui converge vers la solution du problème initial. De cette manière, on peut étendre les résultats, obtenus dans le cadre d'équations différentielles, au contrôle optimal d'équations elliptiques semi-linéaires. Dans la deuxième partie on s'intéresse aux problèmes de commande optimale stochastiques. Dans un premier temps, on considère un problème linéaire quadratique stochastique avec des contraintes de non-negativité sur la commande et on étend les estimations d'erreur pour l'approximation par pénalisation logarithmique. La preuve s'appuie sur le principe de Pontriaguine stochastique et un argument de dualité. Ensuite, on considère un problème de commande stochastique général avec des contraintes convexes sur la commande. L'approche dite variationnelle nous permet d'obtenir un développement au premier et au second ordre pour l'état et la fonction de coût, autour d'un minimum local. Avec ces développements on peut montrer des conditions générales d'optimalité de premier ordre et, sous une hypothèse géométrique sur l'ensemble des contraintes, des conditions nécessaires du second ordre sont aussi établies
Résumé anglais : This thesis is divided in two parts. In the first one we consider deterministic optimal control problems and we study interior approximations for two model problems with non-negativity constraints. The first model is a quadratic optimal control problem governed by a nonautonomous affine ordinary differential equation. We provide a first-order expansion for the penalized state an adjoint state (around the corresponding state and adjoint state of the original problem), for a general class of penalty functions. Our main argument relies on the following fact: if the optimal control satisfies strict complementarity conditions for its Hamiltonian, except for a set of times with null Lebesgue measure, the functional estimates of the penalized optimal control problem can be derived from the estimates of a related finite dimensional problem. Our results provide three types of measure to analyze the penalization technique: error estimates of the control, error estimates of the state and the adjoint state and also error estimates for the value function. The second model we study is the optimal control problem of a semilinear elliptic PDE with a Dirichlet boundary condition, where the control variable is distributed over the domain and is constrained to be non-negative. Following the same approach as in the first model, we consider an associated family of penalized problems, whose solutions define a central path converging to the solution of the original one. In this fashion, we are able to extend the results obtained in the ODE framework to the case of semilinear elliptic PDE constraints. In the second part of the thesis we consider stochastic optimal control problems. We begin withthe study of a stochastic linear quadratic problem with non-negativity control constraints and we extend the error estimates for the approximation by logarithmic penalization. The proof is based is the stochastic Pontryagin's principle and a duality argument. Next, we deal with a general stochastic optimal control problem with convex control constraints. Using the variational approach, we are able to obtain first and second-order expansions for the state and cost function, around a local minimum. This analysis allows us to prove general first order necessary condition and, under a geometrical assumption over the constraint set, second-order necessary conditions are also established
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Hunt, K. J. "Stochastic optimal control theory with application in self-tuning control." Thesis, University of Strathclyde, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382399.

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Shaikh, Mohammad Shahid. "Optimal control of hybrid systems : theory and algorithms." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85095.

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Many complex systems are hybrid in the sense that: (i) the state set possesses continuous and discrete components, and (ii) system evolution may occur in both continuous and discrete time. One important class of hybrid systems is that characterized by a feedback configuration of a set of continuous controlled low level systems and a high level discrete controller; such systems appear frequently in engineering and are particularly evident when a system is required to operate in a number of distinct modes. Other classes of hybrid systems are found in such diverse areas as (i) air traffic management systems, (ii) chemical process control, (iii) automotive engine-transmission systems, and (iv) intelligent vehicle-highway systems.
In this thesis we first formulate a class of hybrid optimal control problems (HOCPs) for systems with controlled and autonomous location transitions and then present necessary conditions for hybrid system trajectory optimality. These necessary conditions constitute generalizations of the standard Minimum Principle (MP) and are presented for the cases of open bounded control value sets and compact control value sets. These conditions give information about the behaviour of the Hamiltonian and the adjoint process at both autonomous and controlled switching times.
Such proofs of the necessary conditions for hybrid systems optimality which can be found in the literature are sufficiently complex that they are difficult to verify and use; in contrast, the formulation of the HOCP given in Chapter 2 of this thesis, together with the use of (i) classical variational methods and more recent needle variation techniques, and (ii) a local controllability condition, called the small time tubular fountain (STTF) condition, make the proofs in that chapter comparatively accessible. We note that the STTF condition is used to establish the adjoint and Hamiltonian jump conditions in the autonomous switchings case.
A hybrid Dynamic Programming Principle (HDPP) generalizing the standard dynamic programming principle to hybrid systems is also derived and this leads to hybrid Hamilton-Jacobi-Bellman (HJB) equation which is then used to establish a verification theorem within this framework. (Abstract shortened by UMI.)
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Nedeljković, Nikola. "The LORE computational method in optimal control theory." Thesis, Nedeljković, Nikola (1985) The LORE computational method in optimal control theory. PhD thesis, Murdoch University, 1985. https://researchrepository.murdoch.edu.au/id/eprint/51530/.

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A number of iterative algorithms for solving unconstrained continuous-time optimal control problems is developed. The method, named LORE is modelled locally on the linear quadratic problem and treats a whole family of algorithms in a unified manner, proposed approach is similar to the philosophy underlying Newton's, the Conjugate gradient and the quasi- Newton methods in the function minimization theory, The where the function being minimized is approximated locally by a quadratic function. In addition to the development of a unified theory of algorithms, the thesis contains several first-order implementable algorithms, the convergence speed of which is comparable to that of second-order methods. A proof of the reduction of the cost at each iterative step of the LORE algorithms, a convergence analysis in the Lm∞ space and a proof of the convergence in the space of relaxed controls are included. The power of the adopted approach lies in the use of the Riccati matrix differential equation which within the context of the LQRE method always has a bounded solution. Within the general framework of the analysis it is possible to obtain both first-order and second-order algorithms. The emphasis is however placed on the first-order LORE algorithms which are simpler and computationally less demanding per iterative step; their computational effectiveness is compared with the performance of known methods. There is a noticeable degree of similarity in the form of the differential equations used by the LORE algorithms and the differential equations in the well-known second order methods; in fact, it is possible to derive LORE variants of the second variation and differential dynamic programming methods. The LORE algorithms converge in one step on the linear quadratic problem and are well suited for solving nonlinear problems with linear constraints via the penalty Their application in the computation of the singular optimal control, by adding and subtracting a quadratic term to the cost, is suggested. function methods. The method has been extended to handle problems with terminal equality constraints, control constraints (LORE projection technique) and a class of state and control equality constraints (sequential LORE-restoration algorithm). The LORE method of discrete-time unconstrained systems has also been developed.
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Dal, Bianco Nicola. "Optimal control of road vehicles: theory and applications." Doctoral thesis, Università degli studi di Padova, 2017. http://hdl.handle.net/11577/3424690.

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In this thesis Optimal Control (OC) of road vehicles is studied especially focusing on minimum lap time simulations. The theory underlying the most used optimal control solving techniques is described, including both the Pontryagin Maximum Principle and the reduction to Nonlinear Programming. Direct and indirect methods for optimal control problems are presented and compared against minimum lap time simulations (LTS). Modelling of vehicles for OC-LTSs is studied in order to understand how different design choices can affect simulation outcomes. Novel multibody models of four wheeled vehicles - a GP2 car and a go-kart - for OC-LTSs are developed and validated thorough comparison with experimental data. Particular attention is dedicated to the simulation of tyre load dynamics, that is achieved by a proper modelling of the chassis and suspension motions and of the aerodynamic forces. OC-LTSs are applied to electric vehicles too, specifically to optimise the design of an electric motorbike taking part at the Tourist Trophy Zero competition. A concise yet effective model is proposed in order to perform reliable simulations on a 60km long road in a reasonable amount of time. Experimental data is used to validate the model. A direct full collocation transcription method for OCPs dealing with implicit differential equations and control derivatives is presented, moreover the structure of the resulting NLP problem is accurately described. The relationship between the first order necessary conditions and the Lagrange multipliers of the NLP and OC problems are derived under the adopted discretisation scheme. The presented transcription method is implemented into a software which is currently in use at the University of Padova to solve OC-LTSs.
In this thesis Optimal Control (OC) of road vehicles is studied especially focusing on minimum lap time simulations. The theory underlying the most used optimal control solving techniques is described, including both the Pontryagin Maximum Principle and the reduction to Nonlinear Programming. Direct and indirect methods for optimal control problems are presented and compared against minimum lap time simulations (LTS). Modelling of vehicles for OC-LTSs is studied in order to understand how different design choices can affect simulation outcomes. Novel multibody models of four wheeled vehicles - a GP2 car and a go-kart - for OC-LTSs are developed and validated thorough comparison with experimental data. Particular attention is dedicated to the simulation of tyre load dynamics, that is achieved by a proper modelling of the chassis and suspension motions and of the aerodynamic forces. OC-LTSs are applied to electric vehicles too, specifically to optimise the design of an electric motorbike taking part at the Tourist Trophy Zero competition. A concise yet effective model is proposed in order to perform reliable simulations on a 60km long road in a reasonable amount of time. Experimental data is used to validate the model. A direct full collocation transcription method for OCPs dealing with implicit differential equations and control derivatives is presented, moreover the structure of the resulting NLP problem is accurately described. The relationship between the first order necessary conditions and the Lagrange multipliers of the NLP and OC problems are derived under the adopted discretisation scheme. The presented transcription method is implemented into a software which is currently in use at the University of Padova to solve OC-LTSs.
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Seywald, Hans. "Optimal control problems with switching points." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-07282008-135220/.

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Guo, Chaoyang. "Some optimal control problems in mathematical finance." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0022/NQ39269.pdf.

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Books on the topic "Optimal control theory"

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Sethi, Suresh P. Optimal Control Theory. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91745-6.

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Sethi, Suresh P. Optimal Control Theory. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-98237-3.

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Ma, Zhongjing, and Suli Zou. Optimal Control Theory. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6292-5.

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Lewis, Frank L. Optimal control. 3rd ed. Hoboken: Wiley, 2012.

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1934-, Tikhomirov V. M., and Fomin S. V, eds. Optimal control. New York: Consultants Bureau, 1987.

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Optimal control. New York: Springer, 2010.

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Hull, David G. Optimal Control Theory for Applications. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-1-4757-4180-3.

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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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Speyer, Jason Lee. Primer on optimal control theory. Philadelphia: Society for Industrial and Applied Mathematics, 2010.

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H, Jacobson David, ed. Primer on optimal control theory. Philadelphia: Society for Industrial and Applied Mathematics, 2010.

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Book chapters on the topic "Optimal control theory"

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Extremals Field Theory." In Optimal Control, 185–201. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_14.

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Locatelli, Arturo. "The Hamilton-Jacobi theory." In Optimal Control, 9–19. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8328-3_2.

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Colonius, Fritz. "Optimization theory." In Optimal Periodic Control, 8–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0077933.

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Roy, Priti Kumar. "Optimal Control Theory." In Mathematical Models for Therapeutic Approaches to Control HIV Disease Transmission, 119–53. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-852-6_6.

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Kythe, Prem K. "Optimal Control Theory." In Elements of Concave Analysis and Applications, 233–50. Boca Raton, Florida : CRC Press, [2018]: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315202259-10.

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Longuski, James M., José J. Guzmán, and John E. Prussing. "Optimal Control Theory." In Optimal Control with Aerospace Applications, 19–38. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8945-0_2.

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Ziemann, Volker. "Optimal Control Theory." In Undergraduate Lecture Notes in Physics, 171–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63643-2_11.

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Heij, Christiaan, André C.M. Ran, and Frederik van Schagen. "Optimal Control." In Introduction to Mathematical Systems Theory, 65–80. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59654-5_5.

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Boltyanski, Vladimir G. "Tent Method in Optimal Control Theory." In Optimal Control, 3–20. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_1.

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Sethi, Suresh P. "Stochastic Optimal Control." In Optimal Control Theory, 365–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98237-3_12.

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Conference papers on the topic "Optimal control theory"

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Robert, Grubbström,. "Optimal Lotsizing within Mrp Theory." In Information Control Problems in Manufacturing, edited by Bakhtadze, Natalia, Chair Dolgui, Alexandre and Bakhtadze, Natalia. Elsevier, 2009. http://dx.doi.org/10.3182/20090603-3-ru-2001.00002.

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"Optimal Control Theory and its Applications." In 2019 XXI International Conference Complex Systems: Control and Modeling Problems (CSCMP). IEEE, 2019. http://dx.doi.org/10.1109/cscmp45713.2019.8976795.

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Spindler, K. "Motion planning via optimal control theory." In Proceedings of 2002 American Control Conference. IEEE, 2002. http://dx.doi.org/10.1109/acc.2002.1023924.

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Gaur, Deepak, and Mani Shankar Prasad. "Orbit Transfer using Optimal Control Theory." In 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE). IEEE, 2019. http://dx.doi.org/10.1109/rdcape47089.2019.8979056.

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Zunino, Paolo, and Diego Mastalli. "Optimal control of peritoneal dialysis." In Control Systems: Theory, Numerics and Applications. Trieste, Italy: Sissa Medialab, 2006. http://dx.doi.org/10.22323/1.018.0018.

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Piccoli, Benedetto, and Filippo Castiglione. "Optimal control methods for immunotheraphy." In Control Systems: Theory, Numerics and Applications. Trieste, Italy: Sissa Medialab, 2006. http://dx.doi.org/10.22323/1.018.0027.

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Taur, Der-Ren, Jeng-Shing Chern, Der-Ren Taur, and Jeng-Shing Chern. "Optimal normalization scheme for computed quaternion using optimal regulator theory." In Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-3564.

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Menon, P. K. A., E. Kim, and V. H. L. Cheng. "Helicopter Trajectory Planning using Optimal Control Theory." In 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4789945.

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Thompson, David F., and Osita D. I. Nwokah. "Optimal Loop Synthesis in Quantitative Feedback Theory." In 1990 American Control Conference. IEEE, 1990. http://dx.doi.org/10.23919/acc.1990.4790808.

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PAN, LIPING, and QIHONG CHEN. "NEAR-OPTIMAL CONTROLS TO INFINITE DIMENSIONAL LINEAR-QUADRATIC OPTIMAL CONTROL PROBLEM." In Control Theory and Related Topics - In Memory of Professor Xunjing Li. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812790552_0022.

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Reports on the topic "Optimal control theory"

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Iyer, R. V., R. Holsapple, and D. Doman. Optimal Control Problems on Parallelizable Riemannian Manifolds: Theory and Applications. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada455175.

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Yeh, Edmund M. Theory, Design, and Algorithms for Optimal Control of wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada522224.

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Moin, Parviz, Jeremy A. Templeton, and Meng Wang. Wall Models for Large-Eddy Simulation Based on Optimal Control Theory. Fort Belvoir, VA: Defense Technical Information Center, June 2006. http://dx.doi.org/10.21236/ada451008.

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Jin, Dafeng, Peng Li, Yugong Ruo, Rui Chen, and Keqiang Li. The Study for the Regenerative Braking Strategy Based on the Optimal Control Theory. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0407.

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Ghandehari, Mostafa. An Optimal Control Formulation of the Blaschke-Lebesgue Theorem. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada200939.

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Andreasen, Eugenia, Sofía Bauducco, and Evangelina Dardati. Welfare Effects of Capital Controls. Inter-American Development Bank, June 2021. http://dx.doi.org/10.18235/0003307.

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This paper studies the effect of capital controls on misallocation and welfare in an economy with financial constraints. We build a general equilibrium model with heterogeneous firms, financial constraints and international trade and calibrate it to the Chilean economy. Since high-productivity and exporting firms need to borrow more to reach their optimal scale, capital controls that tax international borrowing hit them harder. As a result, misallocation increases relatively more for this group of firms, and for young firms that are still trying to reach their optimal scale. In terms of welfare, the model predicts a sizable aggregate loss of 2.39 percent when capital controls are introduced, with welfare decreasing twice as much for high-productivity firms. We empirically corroborate the main insights in terms of misallocation obtained from the model using Chilean manufacturing firm data from 1990 to 2007.
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7

Kularatne, Dhanushka N., Subhrajit Bhattacharya, and M. Ani Hsieh. Computing Energy Optimal Paths in Time-Varying Flows. Drexel University, 2016. http://dx.doi.org/10.17918/d8b66v.

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Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as to minimize energy usage for these vehicles. In this paper, we present two graph search based methods to compute energy optimal paths for AMVs in two-dimensional (2-D) time-varying flows. The novelty of the proposed algorithms lies in a unique discrete graph representation of the 3-D configuration space spanned by the spatio-temporal coordinates. This enables a more efficient traversal through the search space, as opposed to a full search of the spatio-temporal configuration space. Furthermore, the proposed strategy results in solutions that are closer to the global optimal when compared to greedy searches through the spatial coordinates alone. We demonstrate the proposed algorithms by computing optimal energy paths around the Channel Islands in the Santa Barbara bay using time-varying flow field forecasts generated by the Regional Ocean Model System. We verify the accuracy of the computed paths by comparing them with paths computed via an optimal control formulation.
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Mwamba, Isaiah C., Mohamadali Morshedi, Suyash Padhye, Amir Davatgari, Soojin Yoon, Samuel Labi, and Makarand Hastak. Synthesis Study of Best Practices for Mapping and Coordinating Detours for Maintenance of Traffic (MOT) and Risk Assessment for Duration of Traffic Control Activities. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317344.

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Maintenance of traffic (MOT) during construction periods is critical to the success of project delivery and the overall mission of transportation agencies. MOT plans may include full road closures and coordination of detours near construction areas. Various state DOTs have designed their own manuals for detour mapping and coordination. However, very limited information is provided to select optimal detour routes. Moreover, closures or detours should provide not only measurable consequences, such as vehicle operating costs and added travel time, but also various unforeseen qualitative impacts, such as business impacts and inconvenience to local communities. Since the qualitative aspects are not easily measurable they tend to be neglected in systematic evaluations and decision-making processes. In this study, the current practices obtained based on an extensive literature review, a nation-wide survey, as well as a series of interviews with INDOT and other state DOTs are leveraged to (1) identify a comprehensive set of Key Performance Indicators (KPIs) for detour route mapping, (2) understand how other state DOTs address the qualitative criteria, (3) identify how the involved risks during the planning, service time, and closure of the detour routes are managed, and (4) recommend process improvements for INDOT detour mapping guidelines. As demonstrated by two sample case studies, the proposed KPIs can be taken as a basis for developing a decision-support tool that enables decision-makers to consider both qualitative and quantitative aspects for optimal detour route mapping. In addition, the current INDOT detour policy can be updated based on the proposed process improvements.
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Stavenga, Doekele G. Charting the Visual Space of Insect Eyes - Delineating the Guidance, Navigation and Control of Insect Flight by Their Optical Sensor. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada607192.

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Morkun, Volodymyr, Natalia Morkun, Andrii Pikilnyak, Serhii Semerikov, Oleksandra Serdiuk, and Irina Gaponenko. The Cyber-Physical System for Increasing the Efficiency of the Iron Ore Desliming Process. CEUR Workshop Proceedings, April 2021. http://dx.doi.org/10.31812/123456789/4373.

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It is proposed to carry out the spatial effect of high-energy ultrasound dynamic effects with controlled characteristics on the solid phase particles of the ore pulp in the deslimer input product to increase the efficiency of thickening and desliming processes of iron ore beneficiation products. The above allows predicting the characteristics of particle gravitational sedimentation based on an assessment of the spatial dynamics of pulp solid- phase particles under the controlled action of high-energy ultrasound and fuzzy logical inference. The object of study is the assessment of the characteristics and the process of control the operations of thickening and deslaming of iron ore beneficiation products in the conditions of the technological line of the ore beneficiation plant. The subject of study is a cyber-physical system based on the use of high-energy ultrasound radiation pressure effects on iron-containing beneficiation products in the technological processes of thickening and desliming. The working hypothesis of the project is that there is a relationship between the physical-mechanical and chemical-mineralogical characteristics of the iron ore pulp solid- phase particles and their behavior in technological flows under the influence of controlled ultrasonic radiation, based on which the imitation modeling of the gravitational sedimentation process of the iron ore pulp solid-phase particles can be performed directly in the technological process. Also, the optimal control actions concerning the processes of thickening and desliming can be determined.
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