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It is proposed an approach to find in real time the best control strategy by optimizing the controllers' parameters of three control strategies for the various operating points of a non linear system.
The genetic algorithm is used to tune and optimize the controllers' parameters, penalizing the individuals of the control strategies that do not satisfy the problem's given performance, and then defining the best control strategy for each operating point of the system.
Hence, in this paper, inertia constant is tuned together with frequency droop coefficient of DERs and load frequency controllers' parameters.
The bacterial swarm optimization (BSO) algorithm is employed to search for optimal controllers parameters.
The Bacterial Foraging Optimization Algorithm (BFOA) is employed to search for optimal controllers parameters.
SSEs minimization assures optimal values of different fuzzy PID controllers' parameters.
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Decentralized control system design comprises the selection of a suitable control structure and controller parameters.
The controller parameters analyzed were prediction and control horizons, suppression factor, reference trajectory and integral factor.
Furthermore, equivalent control concept allows a straightforward tuning of the controller parameters.
Instead of designing animation in every scene, a sequence of motion-controllers parameters, which can finish a set of motions, are generated through a synthesis algorithm.
A parameter study presents the impact of selected controller parameters.
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