A Research On Improved Model Predictive Control And Its Applications On Thermal Process And Induction Motor

The Boiler Combustion System is a multi-variable system with strong coupling,fierce disturbance, multiple constraints and longtime delay. The control strategy plays an important part in the safety of thermal process, quality of production and economic performance of operation.In order to overcome the complex features of the boiler combustion system,such as multivariable, strong coupling, strong interference and long hysteresis, a new control algorithm combining predictive function control and PID is proposed in this paper, With introducing predictive output error, this algorithm forms the PID structure in the performance index function. In the control of boiler combustion system, by PID-PFC predictive models online, input values are constantly rolling optimized according to predictive models changes of the system. It can be testified that the new algorithm has the stability of closed-loop system, according to Lyapunov's second stability theorem. Simulation results indicate that PID-PFC control has better steady performance and high efficiency. The control strategy is significant to the practical application of the boiler combustion system.However, in contrast to the slow systems with long time-delay, induction motors,the typical fast systems, have such characteristics of fast time-varying, strong coupling and non-linearity, so theyre demanding for real-time performance of the controllers.In the paper, based on the study of the induction motor efficiency optimization problem, considering the conventional methods of inability to balance the efficiency optimization and response performance, it designs a new fractional order PI(FOPI)predictive functional control strategy. This strategy has the advantages of both dynamic efficiency and speed response of induction machine, which associates predictive functional control and FOPI. A multivariable predictive functional controller with proportion and integral characteristics is established, and it is applied in the current loop control for induction motor. By using forward and compensation decoupling technique, the two-input two-output system is decomposed into single-input single-output subsystems with measurable disturbance. The simulation experiment indicates not only high tracking precision, strong disturbances rejection and small steady-state errors, but also has good control performance because of the online identification of the parameters.