二次调节转速系统的自适应神经模糊PID控制

Self-adaptive Neural Fuzzy-PID Control for Secondary Regulation Speed System

阐述二次调节转速系统的原理并建立其数学模型。针对系统参数时变、非线性的特点,设计一种自适应神经模糊PID控制器,该控制器利用PID算法实现准确控制,通过神经模糊控制提高控制的自适应性。利用MATLAB模糊逻辑工具箱对系统进行仿真,并与传统PID控制进行比较。结果表明:采用自适应神经模糊PID控制,系统响应快、超调小、过渡时间短、能够较好地抑制干扰,具有良好的动态特性和稳定性。

The principles were presented and the mathematic model was established for the secondary regulation speed control system. Due to the characteristics of time-variability and nonlinearity, a self-adaptive neural fuzzy-PID controller was designed. In the controller, PID control method was used to ensure the accuracy and neural fuzzy control method was used to improve the speed and self-adaptability. Simulations were made by MATLAB fuzzy logic box. By compared with traditional PID controller, the simulation results indicate the self-adaptive neural fuzzy-PID controller has many advantages, such as quick response speed, small overshooting, short transition time and better anti-interference. System with the controller has good dynamic and static quality.