Dynamic Matrix Control Based on Support Vector Regressions Error Compensation

Dynamic matrix control builds predictive model with step response which is easy to obtain in engineering practice. As model mismatch, disturbance and noise inevitably involve the modeling error, this impacts the control performance. Considers to this kind of situation, an algorithm of dynamic matrix control based on support vector regressions error compensation is proposed. Namely, build error model on-line using support vector regressions and do one-step prediction to compensate the predictive model. Thus realize the compensation for model error and strength the robustness of the algorithm. The simulation results show that the algorithm has better control ability, and it has better anti-inference ability than conventional dynamic matrix control