Predictive Sliding Mode Control to a Thermal Process for Batch Dyeing

The batch dyeing process is a typical nonlinear process with time-delay,where precise controlling of temperature plays a vital role on the dyeing quality.Because the accuracy and robustness of the commonly used proportion integration differentiation(PID) algorithm had been limited,a novel method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control(SMC) algorithm.Firstly,a special predictive sliding mode model was constructed according to the principle of generalized predictive control(GPC);secondly,an appropriate reference trajectory for SMC was designed based on the improved approaching law;finally,the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law.This method combined GPC and the SMC with their respective advantages,so it could be applied to time-delay process,making the control system more robust.Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.

The batch dyeing process is a typical nonlinear process with time-delay, where precise controlling of temperature plays a vital role on the dyeing quality. Because the accuracy and robustness of the commonly used proportion integration differentiation （PID） algorithm had been limited, a novd method was developed to precisely control the heating and cooling stages for batch dyeing process based on predictive sliding mode control （SMC） algorithm. Firstly, a special predictive sliding mode model was constructed according to the principle of generalized predictive control （ GPC ） ; secondly, an appropriate reference trajectory for SMC was designed based on the improved approaching law; finally, the predictive sliding mode model and the Diophantine equation were used to predict the output and then the optimized control law was derived using the generalized predictive law. This method combined GPC and the SMC with their respective advantages, so it could be applied to time-delay process, making the control system more robust. Simulation experiments show that this algorithm can well track the temperature variation for the batch dyeing process.