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In this paper, a model predictive controller for time delay capsubot system is presented. Linearized dynamics is used to predictive future system behavior and a control law is derived from a quadratic cost function penalizing the system tracking error and the control effort. It is noted that model predictive control has advantages over state feedback law because of consideration of constraints on...
This paper presents a modified R-learning according to the traditional average reward reinforcement learning algorithm. Reinforcement learning problems constitute an important class of learning and control problems faced by artificial intelligence systems. The general framework of reinforcement learning can be divided into two forms, discounted reward reinforcement learning and average reward reinforcement...
Aiming at Automated Guided Vehicle (AGV) dynamic model characteristics, a Variable Structure Control based on genetic algorithm (GA) and least square-support vector machine (LS-SVM) was designed. Parameters, predetermined by conventional reaching law, were regulated by LS-SVM online. It was shown that system shattering is eliminated. Simulation results indicated that this method possesses the advantages...
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