Particle Swarm Optimization-based design of control systems with reduced sensitivity

This paper proposes two new optimization algorithms for the optimal design of PI controllers dedicated to a class of second-order plants with integral component and variable parameters. The sensitivity analysis with respect to the parametric variations of the controlled plant is supported by the derivation of sensitivity models. Several objective functions are defined based on the augmentation of the output sensitivity functions over the widely used integral of absolute error criterion. The new algorithms are focused on particle swarm optimization algorithms. One case study associated with several analyses proves the advantages of the proposed algorithm.