Constrained multiobjective PSO and T-S fuzzy models for predictive control

Abstract

Multiobjective optimization problems are still a challenging area in the field of control system engineering. Inthis context, the current study describes a new multivariable predictive control scheme formulated by using the T-S fuzzymodeling method and a new constrained multiobjective PSO algorithm. The T-S fuzzy modeling technique is appliedto forecast the behaviors of the nonlinear system. It also aims at establishing some conditions so that the proposedcontrol loop is asymptotically stable. The obtained experimental results show that the combination of the philosophy ofthe T-S fuzzy model and multiobjective PSO is very good in the controlling of nonlinear multivariable processes. Thesatisfactory tracking results with small values of MRE demonstrate the proof of capability of the proposed algorithmand the accuracy of the T-S modeling approach. Meanwhile, experimental results show that, compared with the onesobtained with standard MPC, the proposed method is of high effectiveness in term of the control increments optimizationand the errors in the presence of disturbances.