基于遗传算法论文.docVIP

模糊优化PID控制器的设计 摘要 PID控制是最早发展起来的控制策略其中之一，由于算法、鲁棒性及可靠性都不错，被广泛应用于工业过程控制，建立精确数学模型的确定性控制系统特别适合用此法。而非线性、时变不确定性存在于实际工业生产过程中，所以数学模型难以建立精确，所以想要达到理想效果就不能使用单纯的PID控制器；在实际生产现场中，因受限于参数整定方法烦杂，常规PID控制器参数常常整定不良、性能欠佳，对运行情况的适应性很差。采用模糊控制，过程的动态响应品质比常规PID控制好, 并切比较适应过程参数的变化。所以提出了用模糊方法优化PID控制器的设计。该方法先用MATLAB中的simulink仿真PID,用稳定边界法设定、、的初值，再根据比例、微分、积分的特性手动调节PID参数，使其动态性能更好，得到人工调节PID的经验，然后用模糊推理机根据人工经验设计模糊推理规则，再结合程序使PID控制器用MATLAB仿真出来的曲线动态性能更好，通过粗调和细调相结合的方法，使调整PID参数的次数减少。 关键词：PID控制器；模糊控制；MATLAB仿真；粗调和细调 Fuzzy Method Improve PID Controller Design Abstract PID control is the control strategy developed in the first one, due to algorithm, robustness and reliability are good, are widely used in industrial process control, to establish accurate mathematical model of the deterministic control system is particularly suitable for this method. The nonlinear, time-varying uncertainties exist in the actual industrial production process, so difficult to establish accurate mathematical model, so I want to achieve the desired result can not use a simple PID controller; in the actual production site, the parameters due to limited cumbersome tuning methods, the conventional PID controller parameter tuning is often poor, poor performance, poor adaptability to the operation. Fuzzy control, the process dynamic response than conventional PID control the quality and cut more compatible with the process parameters change. So with the proposed optimized fuzzy PID controller design. The method first used in the MATLAB simulink simulation PID, with a Stable Boundary setting , , of the initial value, then according to proportional, differential and integral characteristics of manual adjustment of PID parameters to better dynamic performance, are manual adjustment PID experience, and then use fuzzy inference engine based on human experience in the design of fuzzy inference rules, combined with the program MATLAB simulation of the PID controller with better performance out of the dynamic curve, by combination of coarse and