Fuzzy predictive control of multivariable process based on Alopex evolutionary optimization algorithm

An optimization algorithm is presented in this paper by using Alopex based PSO evolutionary optimization algorithm to the constrained T-S model fuzzy predictive controller. The T-S model is firstly established for nonlinear systems and its sequence parameters of fuzzy rules are identified by local recursive least square method. Then the generalized predictive control can be adopted to realize the nonlinear system adaptive predictive control. The application on cement rotary kiln control was discussed in detail as an example. The rotary kiln calcination is the most important part of cement production including complicated physical and chemical reaction processes with large inertia, pure hysteresis, nonlinearity and strong coupling characteristics and multi-variables. The main control system structure includes three control loops as the pressure control loop, the burning zone control loop and the back-end of kiln temperature control loop. The simulation results show the effectiveness of the optimization and control schemes with satisfied performance on response time.