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We present a novel batch-mode Reinforcement Learning approach for the design of optimal controllers in the presence of multiple objectives. The algorithm is an extension of Fitted Q-iteration (FQI) that enables to design the controller for all the linear combinations of preferences (weights) assigned to the objectives in a single run. The key idea of multi-objective FQI (MOFQI) is to enlarge the continuous...
Particle swarm optimization (PSO) is extensively used for real parameter optimization in diverse fields of study. This paper describes an application of PSO to the problem of designing a fractional-order proportional-integral-derivative (PIlambdaDdelta) controller whose parameters comprise proportionality constant, integral constant, derivative constant, integral order (lambda) and derivative order...
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