Optimal Operational Feedback Control For A Class Of Industrial Processes

In order to overcome the influence on the operational process performance by the dynamic error of closed circuit control system, an optimal operational feedback control method is proposed in this paper for a class of industrial processes by minimising the quadratic performance index based on both the deviation between desired operational process index and actual value, and the tracking error between set-point and controlled plant output. This method employs two-layered control structure consisting of set-point feedback control in operation layer and set-point tracking control in device layer. A model predictive controller using LMI is designed to dynamically give the optimal set-points, an adjustable decay rate control using state feedback and error integral is employed for designing local controller. An example of flotation process is finally employed for simulated evaluation, and the experimental results show the effectiveness of the proposed method. The main work and contribution in this paper are as followsFirstly, considering the amplitude of controller output signal is limited by the physical conditions in engineering application, introduced the output errors of the controlled plant, a local controller is designed to guarantee the tracking performance of the plant using LMI method, and the convergence speed is adjustable; moreover, the closed loop stability analysis of device layer is given in detail.Secondly, considering the dynamic characteristic widely existing in the operation process, a set-point feedback control in operation layer is designed based on model predictive control, specifically, a sufficient condition to guarantee the asymptotic stability of the whole closed-loop system is given in this paper.Thirdly, we use flotation process as the background to make a lot simulation experiments in the MATLAB and operational optimal control experimental platform to validate the effectiveness of the proposed method.