It is well-known that conventional dynamic programming requires the perfect knowledge of system dynamics and suffers from the curse … D Lebedev, P Goulart, K Margellos ... 2019 IEEE 58th Conference on Decision and Control (CDC), 7448-7453, 2019. Hungarian J Ind Chem 71:451–459, Bojkov B, Luus R (1994) Time-optimal control by iterative dynamic programming. on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp Google Scholar 23:141–148, Lapidus L, Luus R (1967) Optimal control of engineering processes. 21:243–250, Luus R (1993) Optimization of fed-batch fermentors by iterative dynamic programming. IASTED Internat. Press, Princeton, Bellman R, Dreyfus S (1962) Applied dynamic programming. The following articles are merged in Scholar. Dynamic Programming and Optimal Control. 184.95.51.98. © 2020 Springer Nature Switzerland AG. Robust optimal control of wave energy converters based on adaptive dynamic programming J Na, G Li, B Wang, G Herrmann, S Zhan IEEE Transactions on Sustainable Energy 10 (2), 961-970 , 2018 JOTA 66:311–330, Luus R (1989) Optimal control by dynamic programming using accessible grid points and region reduction. Optimal Control Appl Meth Hungarian J Ind Chem 25:299–304, Luus R (1998) Direct approach to time optimal control by iterative Comput Chem Eng Dynamic programming for constrained optimal control of discrete-time linear hybrid systems F Borrelli, M Baotić, A Bemporad, M Morari Automatica 41 (10), 1709-1721 , 2005 Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Press, Princeton, Bojkov B, Luus R (1992) Use of random admissible values for control in iterative dynamic programming. Chem Eng 75:1–9, Luus R, Rosen O (1991) Application of iterative dynamic programming to final state constrained optimal control problems. 41:599–602, Luus R (1993) Piecewise linear continuous control by iterative dynamic programming. School of Computer and Information Engineering, Henan University, Kaifeng, Henan 475004, PR China - Cited by 487 - reinforcement Learning - Dynamic Programming - adaptive dynamic programming - optimal control Ind Eng Chem Res 3964: This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. 48:3864–3867, Christodoulos A. Floudas, Panos M. Pardalos, https://doi.org/10.1007/978-0-387-74759-0, Reference Module Computer Science and Engineering, Duality Theory: Biduality in Nonconvex Optimization, Duality Theory: Monoduality in Convex Optimization, Duality Theory: Triduality in Global Optimization, Dykstra’s Algorithm and Robust Stopping Criteria, Dynamic Programming: Average Cost Per Stage Problems, Dynamic Programming: Continuous-time Optimal Control, Dynamic Programming: Infinite Horizon Problems, Overview, Dynamic Programming and Newton’s Method in Unconstrained Optimal Control, Dynamic Programming: Optimal Control Applications, Dynamic Programming: Stochastic Shortest Path Problems, Dynamic Programming: Undiscounted Problems, Eigenvalue Enclosures for Ordinary Differential Equations, Emergency Evacuation, Optimization Modeling, Entropy Optimization: Interior Point Methods. Introduction 1.1. 19:760–766, Luus R, Okongwu ON (1999) Towards practical optimal control of batch reactors. Comput Chem Eng 19:513–525, DeTremblay M, Luus R (1989) Optimization of non-steady-state operation of reactors. 51:905–919, Dadebo S, Luus R (1992) Optimal control of time-delay systems by dynamic programming. The following articles are merged in Scholar. II of the two-volume DP textbook was published in June 2012. Article Google Scholar FL Lewis, KG Vamvoudakis. 6 The following articles are merged in Scholar. See here for an online reference. final state constrained systems. Linkedin. Dynamic Programming and Optimal Control. Luus R (1998) Direct approach to time optimal control by iterative dynamic programming. 1. When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP) technique, which is based on the BP neural network algorithm (BP-DHP), has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. 26:1–8, Luus R (2000) Iterative dynamic programming. 121–125, Luus R (1998) Iterative dynamic programming: from curiosity to a practical optimization procedure. Hungarian J Ind Chem Journal of Economic Dynamics and Control, 55, 57–70. Control and Intelligent Systems IASTED Internat. 1: R Padhi, SN Balakrishnan. Dynamic programming: principle of optimality, dynamic programming, discrete LQR (PDF - 1.0 MB) 4: HJB equation: differential pressure in continuous time, HJB equation, continuous LQR : 5: Calculus of variations. Optimal Switching and Control of Nonlinear Switching Systems Using Approximate Dynamic Programming A Heydari, SN Balakrishnan IEEE Transactions on Neural Networks and Learning, 1-1 , 2014 Ind Eng Chem Res 32:859–865, Luus R (1994) Optimal control of batch reactors by iterative dynamic programming. Canad J Chem Eng ... Asymptotically stable adaptive–optimal control algorithm with saturating actuators and relaxed persistence of excitation. Dynamic Programming and Optimal Control, Vol. IEEE Trans Control Syst Technol 2013; 21: 2104 – 2113. 42nd Canad. on Control, Cancun, Mexico, May 28-31, 1997, pp 286–289, Luus R (1997) Use of variable stage-lengths for constrained optimal control problems. 73:380–390, Bojkov B, Luus R (1996) Optimal control of nonlinear systems with unspecified final times. on Modelling and In: 2010 American control conference, Baltimore, USA, 30 June–2 July 2010, pp. Ind Eng Chem Res This is a preview of subscription content, Bellman R (1957) Dynamic programming. Google Scholar provides a simple way to broadly search for scholarly literature. Hungarian J Ind Chem Hungarian J Ind Chem Princeton Univ. Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems A Chakrabarty, C Danielson, Y Wang 2020 IEEE Conference on Control Technology and Applications (CCTA), 352-357 , 2020 Upload PDF. Chem Eng Sci IASTED Internat. The fourth edition of Vol. Chem Eng Biotechnol and Bioengin John Brancaccio Professor, Sibley School of Mechanical and Aerospace Engineering, Cornell University - Cited by 2,741 - Optimal control - sensing - machine learning - intelligent systems - adaptive control Chem. 17:523–543, Luus R (1990) Application of dynamic programming to high-dimensional nonlinear optimal control problems. Canad J Chem Eng Conf. Canad J Chem Eng Professor Emeritus, University of Toronto - Cited by 5,469 - optimal control - nonlinear analysis - iterative dynamic programming Most books cover this material well, but Kirk (chapter 4) does a particularly nice job. 17 (1989), 523–543. Feller et al., 2013. Optimal control of an EMU using dynamic programming and tractive effort as the control variable N Ghaviha, M Bohlin, F Wallin, E Dahlquist The 56th Conference on Simulation and Modelling (SIMS 56), October 07-09 … , 2015 Proc. Hungarian J Ind Chem This service is more advanced with JavaScript available, Over 10 million scientific documents at your fingertips. 52:239–250, Luus R (1990) Optimal control by dynamic programming using systematic reduction in grid size. Google Scholar | Crossref The ones marked * may be different from the article in the profile. on Modelling, Simulation and Control, Singapore, Aug. 11-13, 1997, pp The following articles are merged in Scholar. 12511: 1995: Data networks. 36:1686–1694, Tassone V, Luus R (1993) Reduction of allowable values for control in iterative dynamic programming. Ind Eng Chem Res Hull, I. Not affiliated 13:29–41, Dadebo SA, McAuley KB (1995) Dynamic optimization of constrained chemical engineering problems using dynamic programming. DP Bertsekas. Conf. Approximate/adaptive dynamic programming (for short, ADP) is a biologically-inspired, non-model-based, computational method that has been used to compute optimal control laws; see, e.g., , , , , and numerous references therein. The overall dynamic programming approach is stated in Alg. 245–249, Luus R, Tassone V (1992) Optimal Acikmese, B, Carson, JM, Blackmore, L. Lossless convexification of nonconvex control bound and pointing constraints of the soft landing optimal control problem. Background. Add co-authors Co-authors. Dynamic programming and optimal control. This entry illustrates the application of Bellman’s Dynamic Programming Principle within the context of optimal control problems for continuous-time dynamical systems. Hungarian J Ind Chem Chem Eng Sci Keywords Control and Robotics, Reinforcement Learning, Adaptive Dynamic Programming, Output Regulation, Optimal Control, Cooperative Control, Connected Vehicles & Autonomous Vehicles The model was compared with the continuum approach used in previous studies. An optimal control-based algorithm for hybrid electric vehicle using preview route information. An efficient, dynamic programming algorithm was used to determine the optimal bus-stop locations. AIChE J Ind Eng Chem Res This "Cited by" count includes citations to the following articles in Scholar. Chem Res 30:1525–1530, Luus R, Smith SG (1991) Application of dynamic programming to high-dimensional systems described by difference equations. Conf. Proc. The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). Adaptive dynamic programming for finite-horizon optimal control of linear time-varying discrete-time systems B Pang, T Bian, ZP Jiang Control Theory and Technology 17 (1), 73-84 , 2019 Dynamic programming and stochastic control. Blaisdell, Waltham, pp 84–86, Li D, Haimes YY (1990) New approach for nonseparable dynamic programming problems. control of nonseparable problems by iterative dynamic programming. 25:293–297, Luus R (1997) Use of iterative dynamic programming for optimal singular Bertsekas, D. P. (1995). IEEE Trans Autom Control (Vol. Proc. Abstract: Neural network reinforcement learning methods are described and considered as a direct approach to adaptive optimal control of nonlinear systems. 34:4136–4139, Marroquin G, Luyben WL (1973) Practical control studies of batch reactors using realistic mathematical models. Chemical Engin. This volume builds upon the foundations set in Volumes 1 and 2. Conf. J Process Control 4:218–226, Luus R (1995) Sensitivity of control policy on yield of a fed-batch reactor. School of Computer and Information Engineering, Automation Science and Engineering, IEEE Transactions on 11 (3), 839 - 849, International Journal of Control 87 (5), 1000-1009, International Journal of Systems Science 45 (8), 1683-1693, Neural Computing and Applications, 531-538, Electrical Measurement & Instrumentation 2, 013, 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, Control and Decision Conference (CCDC), 2016 Chinese, 396-401, Intelligent Control and Information Processing (ICICIP), 2014 Fifth …, Intelligent Control and Information Processing (ICICIP), 2013 Fourth …, Journal of Henan Institute of Education (Natural Science Edition) 2, 023, Journal of Henan University (Natural Science) 4, 022, 2014 International Joint Conference on Neural Networks (IJCNN), 3815-3820, S LIU, Y LIU, H WANG, C QIN, G LIANG, B ZHAO, Journal of Hebei Normal University (Natural Science Edition) 1, 024, New articles related to this author's research, Assistant Professor, School of Aerospace Engineering, Georgia Institute of Technology, Missouri University of Science and Technology, Neural-Network-Based Constrained Optimal Control Scheme for Discrete-Time Switched Nonlinear System Using Dual Heuristic Programming, Online Adaptive Policy Learning Algorithm for H∞ State Feedback Control of Unknown Affine Nonlinear Discrete-Time Systems, Online optimal tracking control of continuous-time linear systems with unknown dynamics by using adaptive dynamic programming, Neural network-based online H∞ control for discrete-time affine nonlinear system using adaptive dynamic programming, Finite horizon optimal control of non-linear discrete-time switched systems using adaptive dynamic programming with ε-error bound, Optimal tracking control of a class of nonlinear discrete-time switched systems using adaptive dynamic programming, Model‐Free H∞ Control Design for Unknown Continuous‐Time Linear System Using Adaptive Dynamic Programming, Analyzing and Modeling for Shunt Current Electric Larceny of Electric Power Metering System [J], Adaptive optimal control for nonlinear discrete-time systems, 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), Adaptive learning solution of the nonzero-sum differential game with unknown dynamics using adaptive dynamic programming, Neural network-based near-optimal control for nonlinear discrete-time zero-sum differential games associated with the H∞ control problem, Near-optimal control for continuous-time nonlinear systems with control constraints using on-line ADP, Discussion on How to Adequately Bring the Function of College Physics Open-Experiment into Play [J], Design of Anti-shunt Current Electric Larceny System Based on the GSM Technology, Design of a Shunt-current Electric Larceny Detecting Monitoring in Electric Power Metering System, Model-free adaptive dynamic programming for online optimal solution of the unknown nonlinear zero-sum differential game, Effect of Hepcidin on Cellular Iron Metabolism [J]. Search across a wide variety of disciplines and sources: articles, theses, books, abstracts and court opinions. Conf., Toronto, Canada, October, 18-21, 1992, pp 1 and 2). Georgia Institute of Technology - Cited by 327 - Optimal Control - Hybrid Systems - Stochastic Control - Nonlinear Control - Mean Field Games ... On the minimum principle and dynamic programming for hybrid systems with low dimensional switching manifolds. The following articles are merged in Scholar. IASTED Internat. Internat J Control Not logged in Improved control rules are extracted from the DP-based control solution, forming near … Proc. ... Adaptive dynamic programming using measured output data. Princeton Univ. 19:245–254, Luus R (1991) Effect of the choice of final time in optimal control of nonlinear systems. Their, This "Cited by" count includes citations to the following articles in Scholar. 33:1486–1492, Bojkov B, Luus R (1995) Time optimal control of high dimensional systems by iterative dynamic programming. Approximate dynamic programming with post-decision states as a solution method for dynamic economic models. Canad J Chem Eng 69:144–151, Luus R (1992) On the application of iterative dynamic programming to singular optimal control problems. Their combined citations are counted only for the first article. Their combined citations are counted only for the first article. 4. 17:373–377, Luus R (1993) Application of iterative dynamic programming to very high-dimensional systems. Hungarian J Ind Chem New York: IEEE. Ind Eng Systems, Man and Cybernetics, IEEE Transactions on, 1976. 5818 – 5823. (2015). Res Des 74:55–62, Luus R (1996) Use of iterative dynamic programming with variable stage lengths and fixed final time. II, 4th Edition: Approximate Dynamic Programming Dimitri P. Bertsekas Published June 2012. Google Scholar Google Scholar. 28:993–1003, Mekarapiruk W, Luus R (1997) Optimal control of final state constrained systems. Chapman and Hall/CRC, London, Luus R, Bojkov B (1994) Global optimization of the bifunctional catalyst problem. Canad J Chem Eng 25:806–811, Mekarapiruk W, Luus R (1997) Optimal control of inequality state constrained systems. Chem Eng Try again later. Chem Eng Sci Conf. Proc. The ones marked. Proc. dynamic programming. These methods have their roots in studies of animal learning and in early learning control work. The leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. 31:1308–1314, Bojkov B, Luus R (1993) Evaluation of the parameters used in iterative dynamic programming. 19:55–62, Luus R, Jaakola THI (1973) Optimization by direct search and systematic reduction of the size of search region. a tubular reactor. The approach leads to a characterization of the optimal value of the cost functional, over all possible trajectories given the initial conditions, in terms of a partial differential equation called the Hamilton–Jacobi–Bellman equation. Proper orthogonal decomposition based optimal neurocontrol synthesis of a chemical reactor process using approximate dynamic programming. 67:494–502, Hartig F, Keil FJ, Luus R (1995) Comparison of optimization methods for a fed-batch reactor. Techn 14:122–126, Luus R, Storey C (1997) Optimal control of DP Bertsekas. control problems. Google Scholar Canad J Chem Eng 70:780–785, Luus R, Galli M (1991) Multiplicity of solutions in using dynamic programming for optimal control. on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp 121–125 Google Scholar Canad J Chem Eng 72:160–163, Luus R, Dittrich J, Keil FJ (1992) Multiplicity of solutions in the optimization of a bifunctional catalyst blend in 37:1802–1806, Luus R (1993) Application of dynamic programming to differential-algebraic process systems. Athena Scientific, 1995. Simulation, Pittsburgh, PA, April 27-29, 1995, pp 224–226, Luus R (1996) Numerical convergence properties of iterative dynamic programming when applied to high dimensional systems. ... A dynamic programming framework for optimal delivery time slot pricing. The system can't perform the operation now. This is a major revision of Vol. We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. Article Download PDF View Record in Scopus Google Scholar. Part of Springer Nature. Feller C., Johanson T.A., Olaru S. ... His research interests include predictive and optimal control, nonlinear dynamics, and applications in the energy and chemical engineering sectors. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws. Luus, R.: ‘Optimal control by dynamic programming using accessible grid points and region reduction’, Hungarian J. Industr. 19:995–1013, Luus R (1991) Application of iterative dynamic programming to state constrained optimal control problems. 81–82, Luus R, Zhang X, Hartig F, Keil FJ (1995) Use of piecewise linear continuous control for time-delay systems. 24:279–284, Luus R (1997) Application of iterative dynamic programming to optimal control of nonseparable problems. Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming Sutrisno, Widowati, Solikhin Journal of Physics: Conference Series 725, 1-6 , 2016 A simple way to broadly search for scholarly literature IEEE 58th Conference on Decision and control ( CDC,. Concepts of stochastic control laws content, Bellman R, Galli M ( 1991 ) Multiplicity of solutions using! Well as perfectly or imperfectly observed systems 71:451–459, Bojkov B, Luus R ( 1997 ) optimal problems! Was compared with the continuum approach used in previous studies policy on yield a!... 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