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This work deals with the optimal controller synthesis against high‐level multiple requirements using evolutionary computation. Indeed, such stochastic algorithms are interesting to solve problems based on complex industrial specifications and so seem to be particularly well suited to optimal robust controller synthesis. Using the H∞ loop‐shaping framework, the optimal weights/controller tuning without...
This paper proposes to revisit the μ-synthesis problem with a recent and efficient meta-heuristic called Quantum Particle Swarm Optimization (QPSO). This algorithm allows optimizing dynamic (or static) D-scalings without fitting them, which leads to robust performance controllers. This method has been applied successfully to a classical flexible plant control problem with a reasonable computation...
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