Scheduled Robust Model Predietive Control With Soft Constraints For Industfial Systems With Large Operating Regions

Many complex industrial systems has the characteristics of large operation region, which has become a great problem for its process control system. In this paper, we propose a novel Robust Model Predictive control strategy based on Linear Matrix Inequalities and improve the control algorithm by scheduled switching strategy, conservatism reduce, introducing soft constraints to deal with the industrial process with wide operating regions.Firstly piece-wised linear time varying system with polytopic uncertainty is built to better approximate the industrial systems. Systems with wide operating regions can be expressed as a series of the linear time-varying systems around the operating point of. Then we can bulid local robust model predictive control with region of feasibility, so we get a serious of region of feasibility nested with each other. Lastly for the online part, by scheduled switching strategy, we optimize the scheduled RMPC over the entire feasibility region.As a typical case of the complex industrial process with wide operating regions, we apply previous control strategy on the U-tueb Steam Generator in the nuclear power plant, which demonstrates the engineering practical value of schedule robust model predictive control with large operating region.