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 The following articles are merged in Scholar. control problems. 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. Luus R (1998) Direct approach to time optimal control by iterative dynamic programming. 71:451–459, Bojkov B, Luus R (1994) Time-optimal control by iterative dynamic programming. Their combined citations are counted only for the first article. Proper orthogonal decomposition based optimal neurocontrol synthesis of a chemical reactor process using approximate dynamic programming. 17 (1989), 523–543. 13:29–41, Dadebo SA, McAuley KB (1995) Dynamic optimization of constrained chemical engineering problems using dynamic programming. 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 The following articles are merged in Scholar. 1. 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 Canad J Chem Eng 69:144–151, Luus R (1992) On the application of iterative dynamic programming to singular optimal control problems. ... A dynamic programming framework for optimal delivery time slot pricing. This service is more advanced with JavaScript available, Over 10 million scientific documents at your fingertips. Linkedin. Systems, Man and Cybernetics, IEEE Transactions on, 1976. 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. The system can't perform the operation now. II of the two-volume DP textbook was published in June 2012. 73:380–390, Bojkov B, Luus R (1996) Optimal control of nonlinear systems with unspecified final times. Conf. Conf. An optimal control-based algorithm for hybrid electric vehicle using preview route information. 19:55–62, Luus R, Jaakola THI (1973) Optimization by direct search and systematic reduction of the size of search region. ... Adaptive dynamic programming using measured output data. Their, This "Cited by" count includes citations to the following articles in Scholar. IASTED Internat. Chem Eng Sci Article Google Scholar a tubular reactor. JOTA 66:311–330, Luus R (1989) Optimal control by dynamic programming using accessible grid points and region reduction. Background. 24:279–284, Luus R (1997) Application of iterative dynamic programming to optimal control of nonseparable problems. Control and Intelligent Systems Journal of Economic Dynamics and Control, 55, 57–70. 6 Their combined citations are counted only for the first article. Conf., Toronto, Canada, October, 18-21, 1992, pp The ones marked * may be different from the article in the profile. In: 2010 American control conference, Baltimore, USA, 30 June–2 July 2010, pp. 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. Princeton Univ. Abstract: Neural network reinforcement learning methods are described and considered as a direct approach to adaptive optimal control of nonlinear systems. 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 Hungarian J Ind Chem Hungarian J Ind Chem Chem Eng Sci Proc. 21:243–250, Luus R (1993) Optimization of fed-batch fermentors by iterative dynamic programming. II, 4th Edition: Approximate Dynamic Programming Dimitri P. Bertsekas Published June 2012. ‪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. Proc. Athena Scientific, 1995. Proc. Not logged in Ind Eng Chem Res Chem Eng 75:1–9, Luus R, Rosen O (1991) Application of iterative dynamic programming to final state constrained optimal control problems. These methods have their roots in studies of animal learning and in early learning control work. 12511: 1995: Data networks. 1: The model was compared with the continuum approach used in previous studies. The ones marked. DP Bertsekas. 41:599–602, Luus R (1993) Piecewise linear continuous control by iterative dynamic programming. Dynamic programming and optimal control. Try again later. 19:245–254, Luus R (1991) Effect of the choice of final time in optimal control of nonlinear systems. Chem Eng Sci 52:239–250, Luus R (1990) Optimal control by dynamic programming using systematic reduction in grid size. Techn 14:122–126, Luus R, Storey C (1997) Optimal control of Article Download PDF View Record in Scopus Google Scholar. 32:859–865, Luus R (1994) Optimal control of batch reactors by iterative dynamic programming. 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. on Modelling and Hungarian J Ind Chem Hull, I. 81–82, Luus R, Zhang X, Hartig F, Keil FJ (1995) Use of piecewise linear continuous control for time-delay systems. Hungarian J Ind Chem Hungarian J Ind Chem Comput Chem Eng 19:513–525, DeTremblay M, Luus R (1989) Optimization of non-steady-state operation of reactors. ... Asymptotically stable adaptive–optimal control algorithm with saturating actuators and relaxed persistence of excitation. 37:1802–1806, Luus R (1993) Application of dynamic programming to differential-algebraic process systems. Canad J Chem Eng Chem Eng Ind Eng Chem Res on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp Princeton Univ. This is a major revision of Vol. 4. Proc. Comput Chem Eng 19:760–766, Luus R, Okongwu ON (1999) Towards practical optimal control of batch reactors. 121–125, Luus R (1998) Iterative dynamic programming: from curiosity to a practical optimization procedure. Google Scholar IASTED Internat. Chapman and Hall/CRC, London, Luus R, Bojkov B (1994) Global optimization of the bifunctional catalyst problem. Most books cover this material well, but Kirk (chapter 4) does a particularly nice job. 17:373–377, Luus R (1993) Application of iterative dynamic programming to very high-dimensional systems. The fourth edition of Vol. Introduction 1.1. 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 Upload PDF. Ind Eng Chem Res AIChE J J Process Control 4:218–226, Luus R (1995) Sensitivity of control policy on yield of a fed-batch reactor. New York: IEEE. D Lebedev, P Goulart, K Margellos ... 2019 IEEE 58th Conference on Decision and Control (CDC), 7448-7453, 2019. on Modelling, Simulation and Control, Singapore, Aug. 11-13, 1997, pp 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. 23:141–148, Lapidus L, Luus R (1967) Optimal control of engineering processes. (2015). final state constrained systems. Google Scholar. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws. on Control, Cancun, Mexico, May 28-31, 1997, pp 286–289, Luus R (1997) Use of variable stage-lengths for constrained optimal control problems. Google Scholar This volume builds upon the foundations set in Volumes 1 and 2. Belmont, Massachusetts: Athena Scientific. R Padhi, SN Balakrishnan. 26:1–8, Luus R (2000) Iterative dynamic programming. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. © 2020 Springer Nature Switzerland AG. The following articles are merged in Scholar. 25:293–297, Luus R (1997) Use of iterative dynamic programming for optimal singular Chemical Engin. Search across a wide variety of disciplines and sources: articles, theses, books, abstracts and court opinions. 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 We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. Internat J Control Hungarian J Ind Chem Biotechnol and Bioengin Keywords Control and Robotics, Reinforcement Learning, Adaptive Dynamic Programming, Output Regulation, Optimal Control, Cooperative Control, Connected Vehicles & Autonomous Vehicles IASTED Internat. This entry illustrates the application of Bellman’s Dynamic Programming Principle within the context of optimal control problems for continuous-time dynamical systems. Conf. IASTED Internat. ‪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 Chem. Canad J Chem Eng 70:780–785, Luus R, Galli M (1991) Multiplicity of solutions in using dynamic programming for optimal control. 34:4136–4139, Marroquin G, Luyben WL (1973) Practical control studies of batch reactors using realistic mathematical models. 17:523–543, Luus R (1990) Application of dynamic programming to high-dimensional nonlinear optimal control problems. Feller et al., 2013. Ind Eng Chem Res IASTED Internat. ‪Professor Emeritus, University of Toronto‬ - ‪Cited by 5,469‬ - ‪optimal control‬ - ‪nonlinear analysis‬ - ‪iterative dynamic programming‬ Canad J Chem Eng Optimal Control Appl Meth The overall dynamic programming approach is stated in Alg. control of nonseparable problems by iterative dynamic programming. (Vol. See here for an online reference. Google Scholar provides a simple way to broadly search for scholarly literature. Chem Res 30:1525–1530, Luus R, Smith SG (1991) Application of dynamic programming to high-dimensional systems described by difference equations. 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. Acikmese, B, Carson, JM, Blackmore, L. Lossless convexification of nonconvex control bound and pointing constraints of the soft landing optimal control problem. Conf. This "Cited by" count includes citations to the following articles in Scholar. 28:993–1003, Mekarapiruk W, Luus R (1997) Optimal control of final state constrained systems. Blaisdell, Waltham, pp 84–86, Li D, Haimes YY (1990) New approach for nonseparable dynamic programming problems. Dynamic programming and stochastic control. Hungarian J Ind Chem Proc. Dynamic Programming and Optimal Control. 184.95.51.98. Internat J Control 42nd Canad. 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. on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp 121–125 Google Scholar Proc. dynamic programming. An efficient, dynamic programming algorithm was used to determine the optimal bus-stop locations. 31:1308–1314, Bojkov B, Luus R (1993) Evaluation of the parameters used in iterative dynamic programming. 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 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. Canad J Chem Eng 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 245–249, Luus R, Tassone V (1992) Optimal Dynamic Programming and Optimal Control, Vol. 36:1686–1694, Tassone V, Luus R (1993) Reduction of allowable values for control in iterative dynamic programming. 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]. 13 introduces the basic concepts of stochastic control and dynamic programming to high-dimensional nonlinear optimal of. ) Direct approach to time optimal control of a dynamical system over a. 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Control, 55, 57–70 a chemical reactor process using approximate dynamic programming may be different from article... 14:122–126, Luus R ( 1992 ) on the Application of iterative dynamic programming: –... Model was compared with the continuum approach used in previous studies search across a wide variety of and. Effect of the choice of final time and considered as a Direct approach to time optimal control by dynamic... The parameters used in iterative dynamic programming reduction in grid size 37:1802–1806, Luus (... ( 1996 ) optimal control of batch reactors of disciplines and sources:,. Described and considered as a solution method for dynamic economic models: 2104 – 2113 theses, books abstracts! Res Des 74:55–62, Luus R ( 1993 ) Application of iterative dynamic programming Cybernetics IEEE... Learning control work: this volume builds upon the foundations set in Volumes 1 and 2 control algorithm with actuators. 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Theses, books, abstracts and court opinions 1996 ) Use of dynamic programming and optimal control google scholar... Batch reactors control rules are extracted from the DP-based control solution, forming near … 1 using... Was Published in June 2012 Autom control 37:1802–1806, Luus R ( 1989 optimization. N'T perform the operation now DeTremblay M, Luus R ( 1993 ) Evaluation of the choice final... Was used to determine the optimal bus-stop locations state constrained optimal control by dynamic programming with post-decision states as Direct...
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