Research And Application Of Fractional-order PID Dynamic Matrix Control Algorithm Based On Time Domain

Model predictive control is a type of advanced control algorithms based on model after the typical control algorithm and the modern control algorithm. It has been widely used in industrial process control. The models in this algorithm are gained through experimental methods. The main ideas of the algorithm are "model predicting—feedback revising—rolling optimizing". By calculating the quadratic performance index of the system, the optimal control variable will be got. The typical algorithms of model predictive control are model algorithmic control (MAC), dynamic matrix control (DMC), generalized predictive control (GPC). In this paper, base on State Space description of DMC, our discussions mainly focus on improving and researching PIDDMC algorithm.The factional-order control is supplement and summary to the traditional integer-order control theory. It makes the traditional control theory better in simulation and robustness and makes the static and dynamic performs of the control system can be improved. What's more, the fractional-order controller can be designed within the frequency domain. Base on analyzing the two control algorithm, this paper derives Fractional-order PID Dynamic Matrix Control (FOPIDDMC) algorithm. This algorithm has not only the advantage of the fractional-order PID, which is reliable in operation and convenient in regulating parameters, but also the prediction function. Simulation results show that this algorithm is better than basic DMC algorithm and PIDDMC algorithm in many performances.At present, the algorithm applied in EPA control system and superheated temperature system of power plants is mainly traditional PID algorithm. In this paper, the improved FOPIDDMC algorithm is applied in EPA control system. The influence of FOPIDDMC controller parameter tuning on system performance is investigated in time domain, which lays a good foundation for future engineering practice.Most industrial processes have characteristic of time delay. The communication delay introduced by the networks can lead to performance degradation and even instability. To address network-induced delays, a time-stamped PID dynamic matrix control (TSPIDDMC) algorithm which uses a communication delay model to improve reliability over network control systems is proposed. The network-induced delays are measured by a time-stamp method, based on which the step response coefficients and control coefficients ate corrected in each sampling period and the algorithm derivation is given. Simulative validation of this new algorithm resulted in improved performance and stability over PIDDMC control.