基于模糊模型的一类不确定非线性系统协调优化控制

Coordination optimization control of a class of uncertain nonlinear system based on fuzzy model

以典型的不确定非线性系统——发电单元机组为例,提出了基于模糊模型的协调优化控制新方案。首先建立该系统的模糊状态空间模型,然后依据此模糊模型和极点配置技术设计了具有渐进跟踪性能的状态反馈控制器。针对此系统的非线性、参数时变、多变量耦合等特征所导致的极点配置最佳参数难以确定的问题,提出了基于改进粒子群算法(PSO)的多目标优化极点配置参数新策略,进而实现了系统的协调优化控制。仿真研究表明:依据该方法设计的协调控制系统在大范围工况下具有良好的调节品质、抗干扰能力和对参数变化的鲁棒性。

Taking the typical uncertain nonlinear system as an example, a new scheme of Coordination Optimiza- tion Control based on fuzzy model is proposed. Firstly, a fuzzy state space model of boiler-turbine system was built. Then, based on the model and pole placement design, a state feedback controller with asymptotic tracking performance was proposed. Because the system had nonlinearity, multivariable coupling and parameter time- varying which made the optimum parameters of pole placement difficult to determine, a multi-objective optimiza- tion method for pole placement based on particle swarm optimization was given. And the coordination optimiza- tion control of the system was realized. Simulation results show that the system designed with the proposed method demonstrates satisfactory regulation quality, anti-interference ability and robustness against parameter variations within wide operating range.