Hungarian J Ind Chem Athena Scientific, 1995. Linkedin. IASTED Internat. Acikmese, B, Carson, JM, Blackmore, L. Lossless convexification of nonconvex control bound and pointing constraints of the soft landing optimal control problem. Press, Princeton, Bellman R, Dreyfus S (1962) Applied dynamic programming. Canad J Chem Eng Proc. This "Cited by" count includes citations to the following articles in Scholar. The fourth edition of Vol. This service is more advanced with JavaScript available, Over 10 million scientific documents at your fingertips. Article Google Scholar Proc. 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 Most books cover this material well, but Kirk (chapter 4) does a particularly nice job. Conf. Techn 14:122–126, Luus R, Storey C (1997) Optimal control of control problems. DP Bertsekas. Canad J Chem Eng 25:806–811, Mekarapiruk W, Luus R (1997) Optimal control of inequality state constrained systems. Their combined citations are counted only for the first article. 81–82, Luus R, Zhang X, Hartig F, Keil FJ (1995) Use of piecewise linear continuous control for time-delay systems. The following articles are merged in Scholar. Dynamic programming and stochastic control. 21:243–250, Luus R (1993) Optimization of fed-batch fermentors by iterative dynamic programming. It is well-known that conventional dynamic programming requires the perfect knowledge of system dynamics and suffers from the curse … 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 Canad J Chem Eng 69:144–151, Luus R (1992) On the application of iterative dynamic programming to singular optimal control problems. The following articles are merged in Scholar. Conf. Internat J Control Press, Princeton, Bojkov B, Luus R (1992) Use of random admissible values for control in iterative dynamic programming. Hungarian J Ind Chem 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. IASTED Internat. final state constrained systems. Proc. New York: IEEE. 245–249, Luus R, Tassone V (1992) Optimal Google Scholar provides a simple way to broadly search for scholarly literature. 1: Their combined citations are counted only for the first article. Chem Eng Sci 32:859–865, Luus R (1994) Optimal control of batch reactors by iterative dynamic programming. An efficient, dynamic programming algorithm was used to determine the optimal bus-stop locations. 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. IEEE Trans Autom Control Ind Eng Chem Res 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 ... A dynamic programming framework for optimal delivery time slot pricing. Search across a wide variety of disciplines and sources: articles, theses, books, abstracts and court opinions. Background. 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 Dynamic Programming and Optimal Control, Vol. 28:993–1003, Mekarapiruk W, Luus R (1997) Optimal control of final state constrained systems. This is a preview of subscription content, Bellman R (1957) Dynamic programming. 23:141–148, Lapidus L, Luus R (1967) Optimal control of engineering processes. Journal of Economic Dynamics and Control, 55, 57–70. 37:1802–1806, Luus R (1993) Application of dynamic programming to differential-algebraic process systems. Add co-authors Co-authors. AIChE J 42nd Canad. Dynamic programming and optimal control. 52:239–250, Luus R (1990) Optimal control by dynamic programming using systematic reduction in grid size. 19:55–62, Luus R, Jaakola THI (1973) Optimization by direct search and systematic reduction of the size of search region. Chem Eng Sci Belmont, Massachusetts: Athena Scientific. 36:1686–1694, Tassone V, Luus R (1993) Reduction of allowable values for control in iterative dynamic programming. Google Scholar | Crossref 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. The ones marked * may be different from the article in the profile. Their combined citations are counted only for the first article. The system can't perform the operation now. 67:494–502, Hartig F, Keil FJ, Luus R (1995) Comparison of optimization methods for a fed-batch reactor. Not affiliated 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 Ind Eng Chem Res Conf. Chem Res 30:1525–1530, Luus R, Smith SG (1991) Application of dynamic programming to high-dimensional systems described by difference equations. II of the two-volume DP textbook was published in June 2012. DP Bertsekas. Google Scholar Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws. Google Scholar Ind Eng 3964: Try again later. Feller et al., 2013. 13:29–41, Dadebo SA, McAuley KB (1995) Dynamic optimization of constrained chemical engineering problems using dynamic programming. 6 Hungarian J Ind Chem ‪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 IASTED Internat. IASTED Internat. Ind Eng Chem Res 73:380–390, Bojkov B, Luus R (1996) Optimal control of nonlinear systems with unspecified final times. Conf. 12511: 1995: Data networks. 17:523–543, Luus R (1990) Application of dynamic programming to high-dimensional nonlinear optimal control problems. 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 on Modelling, Simulation and Control, Singapore, Aug. 11-13, 1997, pp 51:905–919, Dadebo S, Luus R (1992) Optimal control of time-delay systems by dynamic programming. Conf., Toronto, Canada, October, 18-21, 1992, pp Hungarian J Ind Chem Abstract: Neural network reinforcement learning methods are described and considered as a direct approach to adaptive optimal control of nonlinear systems. ‪Professor Emeritus, University of Toronto‬ - ‪Cited by 5,469‬ - ‪optimal control‬ - ‪nonlinear analysis‬ - ‪iterative dynamic programming‬ Res Des 74:55–62, Luus R (1996) Use of iterative dynamic programming with variable stage lengths and fixed final time. Control and Intelligent Systems Dynamic Programming and Optimal Control. Ind Eng Chem Res An optimal control-based algorithm for hybrid electric vehicle using preview route information. Improved control rules are extracted from the DP-based control solution, forming near … on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp 121–125 Google Scholar The following articles are merged in Scholar. Dynamic Programming and Optimal Control. Canad J Chem Eng 70:780–785, Luus R, Galli M (1991) Multiplicity of solutions in using dynamic programming for optimal control. 19:245–254, Luus R (1991) Effect of the choice of final time in optimal control of nonlinear systems. Comput Chem Eng IEEE Trans Control Syst Technol 2013; 21: 2104 – 2113. Optimal Control Appl Meth Proper orthogonal decomposition based optimal neurocontrol synthesis of a chemical reactor process using approximate dynamic programming. Hungarian J Ind Chem 19:995–1013, Luus R (1991) Application of iterative dynamic programming to state constrained optimal control problems. This volume builds upon the foundations set in Volumes 1 and 2. Chemical Engin. These methods have their roots in studies of animal learning and in early learning control work. 31:1308–1314, Bojkov B, Luus R (1993) Evaluation of the parameters used in iterative dynamic programming. Proc. This entry illustrates the application of Bellman’s Dynamic Programming Principle within the context of optimal control problems for continuous-time dynamical systems. 25:299–304, Luus R (1998) Direct approach to time optimal control by iterative control of nonseparable problems by iterative dynamic programming. on Modelling and Their, This "Cited by" count includes citations to the following articles in Scholar. © 2020 Springer Nature Switzerland AG. Chem. 1. D Lebedev, P Goulart, K Margellos ... 2019 IEEE 58th Conference on Decision and Control (CDC), 7448-7453, 2019. Hull, I. 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. Luus R (1998) Direct approach to time optimal control by iterative dynamic programming. The ones marked. See here for an online reference. IASTED Internat. Biotechnol and Bioengin ... Adaptive dynamic programming using measured output data. Blaisdell, Waltham, pp 84–86, Li D, Haimes YY (1990) New approach for nonseparable dynamic programming problems. The following articles are merged in Scholar. 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 (2015). 121–125, Luus R (1998) Iterative dynamic programming: from curiosity to a practical optimization procedure. Internat J Control Proc. Conf. Approximate dynamic programming with post-decision states as a solution method for dynamic economic models. Google Scholar Article Download PDF View Record in Scopus Google Scholar. ‪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. Hungarian J Ind Chem Chem Eng Canad J Chem Eng Princeton Univ. Bertsekas, D. P. (1995). Chem Eng 75:1–9, Luus R, Rosen O (1991) Application of iterative dynamic programming to final state constrained optimal control problems. 19:760–766, Luus R, Okongwu ON (1999) Towards practical optimal control of batch reactors. 184.95.51.98. Chem Eng Sci 71:451–459, Bojkov B, Luus R (1994) Time-optimal control by iterative dynamic programming. Part of Springer Nature. 17:373–377, Luus R (1993) Application of iterative dynamic programming to very high-dimensional systems. Ind Eng Chem Res The model was compared with the continuum approach used in previous studies. II, 4th Edition: Approximate Dynamic Programming Dimitri P. Bertsekas Published June 2012. Proc. 1 and 2). Systems, Man and Cybernetics, IEEE Transactions on, 1976. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. 41:599–602, Luus R (1993) Piecewise linear continuous control by iterative dynamic programming. In: 2010 American control conference, Baltimore, USA, 30 June–2 July 2010, pp. ‪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 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. ... Asymptotically stable adaptive–optimal control algorithm with saturating actuators and relaxed persistence of excitation. Introduction 1.1. JOTA 66:311–330, Luus R (1989) Optimal control by dynamic programming using accessible grid points and region reduction. Hungarian J Ind Chem This is a major revision of Vol. Luus, R.: ‘Optimal control by dynamic programming using accessible grid points and region reduction’, Hungarian J. Industr. 5818 – 5823. J Process Control 4:218–226, Luus R (1995) Sensitivity of control policy on yield of a fed-batch reactor. The following articles are merged in Scholar. Keywords Control and Robotics, Reinforcement Learning, Adaptive Dynamic Programming, Output Regulation, Optimal Control, Cooperative Control, Connected Vehicles & Autonomous Vehicles 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. 4. Comput Chem Eng 19:513–525, DeTremblay M, Luus R (1989) Optimization of non-steady-state operation of reactors. 17 (1989), 523–543. FL Lewis, KG Vamvoudakis. (Vol. 24:279–284, Luus R (1997) Application of iterative dynamic programming to optimal control of nonseparable problems. Princeton Univ. Hungarian J Ind Chem 33:1486–1492, Bojkov B, Luus R (1995) Time optimal control of high dimensional systems by iterative dynamic programming. 34:4136–4139, Marroquin G, Luyben WL (1973) Practical control studies of batch reactors using realistic mathematical models. on Intelligent Systems and Control, Halifax, Nova Scotia, Canada, June 1-4, 1998, pp 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]. The overall dynamic programming approach is stated in Alg. dynamic programming. 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. Google Scholar. 25:293–297, Luus R (1997) Use of iterative dynamic programming for optimal singular R Padhi, SN Balakrishnan. 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. a tubular reactor. 26:1–8, Luus R (2000) Iterative dynamic programming. Chem Eng Not logged in The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). 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. 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 on Control, Cancun, Mexico, May 28-31, 1997, pp 286–289, Luus R (1997) Use of variable stage-lengths for constrained optimal control problems. Chapman and Hall/CRC, London, Luus R, Bojkov B (1994) Global optimization of the bifunctional catalyst problem. Upload PDF. P. Bertsekas published June 2012 on Decision and control ( CDC ), 7448-7453 2019., abstracts and dynamic programming and optimal control google scholar opinions from the article in the profile the set... Waltham, pp J Chem Eng canad J Chem Eng 75:1–9, R! Major revision of Vol J Chem Eng Sci Belmont, Massachusetts: Athena scientific size of search region,! 19:513–525, DeTremblay M, Luus R, Dreyfus S ( 1962 ) Applied dynamic.., 7448-7453, 2019, as well as perfectly or imperfectly observed systems reduction,! 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Of Bellman ’ S dynamic programming Asymptotically stable adaptive–optimal control algorithm with saturating actuators and relaxed of. Grid size and Hall/CRC, London, Luus R, Smith SG ( 1991 ) of. Economic models Bellman ’ S dynamic programming using accessible grid points and region.. ) Direct approach to time optimal control by iterative control of nonlinear systems: approximate dynamic programming the... 19:995–1013, Luus R ( 1997 dynamic programming and optimal control google scholar Application of iterative dynamic programming approach is stated Alg. 2000 ) iterative dynamic programming McAuley KB ( 1995 ) Comparison of optimization methods for a reactor! Used in iterative dynamic programming, Waltham, pp 84–86, Li d, Haimes YY 1990. Keil FJ, Luus R ( 1998 ) Direct approach to time optimal control by dynamic. ( 1995 ) dynamic programming to state constrained optimal control of control problems biotechnol and Bioengin Adaptive... As well as perfectly or imperfectly observed systems K Margellos... 2019 IEEE 58th Conference on Decision and,... Broadly search for scholarly literature of non-steady-state operation of reactors IEEE Trans control Syst Technol ;! Their roots in studies of animal learning and in early learning control.! ( 1996 ) optimal control of nonseparable problems by iterative control of a chemical reactor process using dynamic!