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Optimal control using adaptive resonance theory and Q-learning

NEUROCOMPUTING 2019年 361卷 119-125页

作者： Kiumarsi, Bahare AlQaudi, Bakur Modares, Hamidreza Lewis, Frank L. Levine, Daniel S. Michigan State Univ E Lansing MI 48824 USA Univ Texas Arlington UTARI Arlington TX 76118 USA Yanbu Ind Coll Elect & Instrumentat Engn Technol Yanbu Alsinaiyah 41912 Saudi Arabia Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang Liaoning Peoples R China Univ Texas Arlington Dept Psychol Arlington TX 76019 USA

Motivated by recent advancement in neurocognitive in brain modeling research, a multiple model-based Q-learning structure is proposed for optimal tracking control problem of time-varying discrete-time systems. This is achieved by utilizing a multiple-model scheme combined with adaptive resonance theory (ART). The ART algorithm generates sub-models based on the match-based clustering method. A responsibility signal governs the likelihood of contribution of each sub-model to the Q-function. The Q-function is learned using the batch least-square algorithm. Simulation results are added to show the performance and the effectiveness of the overall proposed control method. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Neural network Reinforcement learning Adaptive algorithms multiple model control

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MIXING ADAPTIVE FAULT TOLERANT control OF QUADROTOR UAV

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ASIAN JOURNAL OF control 2017年第4期19卷 1441-1454页

作者： Buyukkabasakal, Kemal Fidan, Baris Savran, Aydogan Ege Univ Elect & Elect Engn Dept Izmir Turkey Univ Waterloo Dept Mech & Mechatron Engn Waterloo ON Canada

In this paper, a multiple model adaptive fault tolerant control scheme is proposed based on mixing of the control signals generated by a set of linear quadratic state feedback controllers. Each of these controllers are designed considering closed loop system performance for a particular range of fault. Stability analysis of the proposed scheme is provided. The paper further presents specific design and implementation for motion control of quadrotor unmanned aerial vehicles (UAVs). The designed mixing adaptive controller is tested via real-time experiments on Quanser Qball-X4 UAVs. The experimental results verify the efficiency of the proposed scheme.

关键词： Adaptive control fault tolerant control least squares multiple model control unmanned aerial vehicles

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Stability Analysis of Robust multiple model Adaptive control

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IFAC Proceedings Volumes 2011年第1期44卷 350-355页

作者： Vahid Hassani João Pedro Hespanha Michael Athans António M. Pascoal Institute for Systems and Robotics (ISR) Instituto Superior Técnico (1ST) Lisbon Portugal. Tel: (+351) 21 841 8054 Fax: (+351) 21 841 8291 Dept. of Electrical and Computer Eng. Univ. of California Santa Barbara CA 93106-9560 USA Michael Athans is also Professor of EECS (emeritus) M.I.T. USA

Abstract The Robust multiple model Adaptive control (RMMAC) methodology was first introduced in Fekri et al. [2006] for open-loop stable plants with parametric uncertainty and unmodeled dynamics subjected to external disturbances and measurement noise. This paper addresses the stability of RMMAC systems. We show, using concepts and analysis tools that borrow from Supervisory control, that all closed-loop signals in a RMMAC system are bounded. It is further shown that robust performance is recovered in steady state.

关键词： Robust Adaptive control multiple model control Supervisory control

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Improved switching for multiple model adaptive controller in noisy environment

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JOURNAL OF PROCESS control 2012年第2期22卷 390-396页

作者： Bashivan, Pouya Fatehi, Alireza KN Toosi Univ Technol Fac Elect & Comp Eng Adv Proc Automat & Control APAC Res Grp Tehran Iran

A new switching mechanism for multiple model adaptive controllers (MMAC) is suggested in this paper. The proposed method gives superior performance in comparison to the widely used method of switching based on performance function and hysteresis function in systems which experience high levels of measurement noise. This method acts as a complementary condition within the switching mechanism which checks the existence of excitation in system at every instant. The new method is evaluated by simulation studies on a nonlinear model of a pH neutralization plant. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Adaptive control multiple model control Stability Switching control Noise reduction control

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Switched Unfalsified Multicontroller 1

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2nd IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems

作者： Costa, Fernando Coito, Fernando Palma, Luis Univ Nova Lisboa Dept Engn Electrotecn Fac Ciencias & Tecnol P-2829516 Caparica Portugal

ISBN: (数字)9783642191701

ISBN: (纸本)9783642191701;9783642191695

In this paper, we present a controller design strategy for the implementation of a multicontroller structure for single-input single-output (SISO) plants. The overall control system can be viewed as a feedback interconnection of a SISO plant, a set of candidate controllers and a switched selection scheme that supervises the switching process among the candidate controllers. The switching scheme is designed without explicit assumptions on the plant model, based on the unfalsified control concept introduced by Safonov et al. [1, 2]. A switched multicontroller structure is implemented and experimental results are presented.

关键词： multiple model control adaptive control switched control

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A multiple model approach for predictive control of nonlinear hybrid systems

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JOURNAL OF PROCESS control 2008年第2期18卷 131-148页

作者： Nandola, Naresh N. Bhartiya, Sharad Indian Inst Technol Dept Chem Engn Bombay 400076 Maharashtra India

This paper presents modeling and control of nonlinear hybrid systems using multiple linearized models. Each linearized model is a local representation of all locations of the hybrid system. These models are then combined using Bayes theorem to describe the nonlinear hybrid system. The multiple models, which consist of continuous as well as discrete variables, are used for synthesis of a model predictive control (MPC) law. The discrete-time equivalent of the model predicts the hybrid system behavior over the prediction horizon. The MPC formulation takes on a similar form as that used for control of a continuous variable system. Although implementation of the control law requires solution of an online mixed integer nonlinear program, the optimization problem has a fixed structure with certain computational advantages. We demonstrate performance and computational efficiency of the modeling and control scheme using simulations on a benchmark three-spherical tank system and a hydraulic process plant. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： nonlinear hybrid system multiple model control model predictive control

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multiple model IDENTIFICATION AND control OF NEONATE INCUBATORS USING LAGUERRE BASIS

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IFAC Proceedings Volumes 2005年第1期38卷 289-294页

作者： Gustavo H.C. Oliveira Mardson F. Amorim Krzysztof J. Latawiec PPGEPS/CCET/PUCPR Curitiba/PR/Brazil – Zip Code 80215-901 PPGTS/CCET/PUCPR TUO Poland

This work is focused on temperature and humidity control problem of closed newborn incubators. Such incubator promotes a controlled micro-climate, with small heat transfer between the premature and the environment, leading to a healthful environment. In this context, a laboratory pilot plant (full scale) was built to evaluate control algorithms and this plant is presented here. Furthermore, some identification results based on the use of orthonormal basis functions are discussed and a control scheme is also proposed. This control law is based on multiple local models and predictive control ideas. Closed-loop control examples validates the proposed method.

关键词： predictive control multiple model control system identification orthonormal basis functions neonatal incubators

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Associative methods for d.c./d.c. power electronics control

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EPE JOURNAL 2007年第2期17卷 40-48页

作者： Alejo, D. Maussion, P. Faucher, J. L. Univ Toulouse LAPLACE CNRS INPTUPS F-31071 Toulouse 7 France

This paper describes two different control principles using simple combinations between basic control laws. The objective is to improve the performance (time response, overshoot, robustness...), without strongly increasing the complexity. These principles are tested on a d.c.-d.c. power converter Linear and/or non linear controllers are mixed depending on the optimisation objective and on the decision data. The basic idea is that in the world of control, as elsewhere, "unity is strength", i.e. complex functions could be carried out through basic object combinations. The first principle is based on the combination of two linear controllers. Only two models of the system are taken into account in this Multi model control (MMC) method. A new and specific procedure for model validity is put forward. It is based on the distance between two extreme models of the controlled system, with unknown severe disturbances. The second principle suggests the combination of a linear controller and a non-linear controller (a Bang Bang and an Integral and Proportional controller). This combination is created through the fuzzy fusion of state variables. The tuning of the fuzzy logic parameters is made through Hooke and Jeaves optimisation procedure. The performance is verified through experimental results on a d.c./d.c. converter application. They are significantly improved with respect to standard controllers, with only one voltage sensor and without any adaptive gains.

关键词： controller combination fuzzy control converter control multiple model control fusion d.c./d.c. converter

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multiple model control of a Buck dc/dc converter

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MATHEMATICS AND COMPUTERS IN SIMULATION 2003年第3-5期63卷 249-260页

作者： Alejo, D Maussion, P Faucher, J Ecole Natl Super Electrotech Elect Informat Hydra CNRS 5828 UMR INPTLab Electrotech & Elect Ind Toulouse F-31071 Toulouse 7 France

This paper describes a new method for algorithms commutation between two linear laws, for the voltage control of a dc/dc converter with variable loads. A multiple model control (MMC) is the generated, based upon the fusion of only two traditional IP controllers outputs. This strategy improves the performances of the step input responses and robustness. (C) 2003 Published by Elsevier B.V. on behalf of IMACS.

关键词： IP controllers fuzzy logic fusion multiple model control

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multiple model control of a Buck dc/dc converter

Multiple model control of a Buck dc/dc converter

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Electrimacs 2002 Meeting

作者： Alejo, D Maussion, P Faucher, J Ecole Natl Super Electrotech Elect Informat Hydra CNRS 5828 UMR INPTLab Electrotech & Elect Ind Toulouse F-31071 Toulouse 7 France

关键词： IP controllers fuzzy logic fusion multiple model control

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