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

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