Research On Some Problems Of Nonlinear Model Predictive Control

With the development of modern industry and progress of science technology, the process industry is changed to more complex and with strong nonlinear characteristics so that linear model predictive control (LMPC) may not always obtain satisfactory control results. Predictive control based nonlinear model (NMPC) has become an important research issue in the control engineering fields. Some problems of nonlinear predictive control are researched in this dissertation, and the main research works are as follows:(1) An improved nonlinear predictive control approach based on Wiener model is proposed for a class of nonlinear systems. Laguerre functions are used to describe control input of linear section of Wiener model, optimization solutions of the future control input sequences are converted into optimization of a set of immemorial Laguerre coefficients in prediction horizon. Fuzzy static model is used to approximate nonlinear section of Wiener model, optimization of nonlinear predictive control is converted into linear optimization problem. Simulation results of CSTR show that the proposed approach is feasible.(2) An adaptive fuzzy predictive functional control approach based on T-S model for multivariable nonlinear systems is proposed. The premise parameters of T-S fuzzy model are kept constant;the model consequent parameters are identified online by using the weighting recursive least square method in order to overcome the influence of model mismatch on the performance of the control system. T-S fuzzy model is linearized to be time-varying state space model in each sample point. Two major difficulties in nonlinear predictive control to obtain accurate prediction model and to solve nonlinear optimization online are effectively solved. Simulation results of pH neutralization process show that the proposed approach is an effective control strategy with excellent tracing ability and robustness.(3) An output feedback robust predictive control approach based on uncertain fuzzy models satisfying the sector bounds is proposed for a class of nonlinear systems. The system states don't need exactly measurable, only the measure outputs and the extreme values of the unmeasured states are used to determine the controller. Stability of the closed-loop system is demonstrated. Simulation results show that the proposed approach is valid.(4) An extended robust predictive control approach for discrete uncertain nonlinear systems with state time-delay is presented. The minimization problem of the 'worst-case' objective function is converted into the linear objective minimization problem involving linear matrix inequalities constraints (LMIs). The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability on robust performance index is given. Simulation results of CSTR process show that the proposedapproach is effective and feasible.(5) A particle swarm optimization (PSO)-based predictive control approach is proposed for input constrained nonlinear systems. The dual-mode control strategy and the invariant set theory are used. Outside the invariant set, predictive control law is solved by PSO algorithm. Inside the invariant set, the system states are stabilized gradually by linear state feedback control. Simulation results show that the optimal efficiency of the proposed approach is better than GA.(6) Aiming at the status of outlet temperature fluctuating greatness and thermal efficiency reduction based on conventional control, the advanced control system is designed and exploited for delayed coking furnace. Predictive functional control with little computing quantity and strong robustness is used as the core algorithm, in addition feedforward control and feedback control. CS3000 distributed control system (DCS) is used as the exploitation platform. All kinds of conventional control module, calculation module and logic module of DCS are used to make configuration of advanced control algorithm. The system is safe and credible, dispenses with appending new hardware. Since the system runs, outlet temperature and oxygen content of the furnace become much calmer, burning status is improved, and thermal efficiency is increased.