Decentralized multi-objective robust control of interconnected fuzzy singular perturbed model with multiple perturbation parameters

This paper investigates the decentralized multi-objective robust control for the interconnected fuzzy singular perturbed model with multiple perturbation parameters. Some practical systems, such as the large power system, usually exhibits the characters of multiple time scale and interconnections among subsystems. Thus, the interconnected fuzzy singular perturbed model is proposed to model such industrial system. Additionally, the fuzzy singular perturbed model with multiple perturbation parameters can describe a nonlinear multiple time scale system more precisely than the one with a single perturbation param- eter. However, the concentrated control of interconnected fuzzy singular perturbed model can not achieve excellent performance due to the interconnection term. Sometimes the interconnection term, which can be regarded as the external disturbance, may even lead to divergence in the control system. Thus, in this paper, the decentralized multi-objective robust controller is proposed. On one hand, the control of the fuzzy singular perturbed model can achieve good results under the condition of cross-linking among the subsystems by using the decentralized controller. On the other hand, a multi-extreme optimization model is established considering the noise resistance level, dynamical performance and the control input amplitude comprehensively. The method of Estimation of Distribution Algorithms is utilized to solve this optimization model. Numerical Simulations demonstrate the effectiveness and superiority of the method proposed in this paper.