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