气动伺服系统的BELC压力控制

Pressure Control of Pneumatic Servo System Based on Brain Emotional Learning Controller

由于气动伺服系统受非线性因素的影响,传统PID控制在解决高精度非线性控制问题时效果不理想。一种基于大脑情感学习控制器(Brain Emotion Learning Controller,BELC)的气动伺服系统压力控制方法被提出。首先,对气动伺服系统进行数学建模。然后,结合气动系统非线性和BELC控制特性进行算法改进,采用模糊控制对BELC权值学习率进行在线调节。最后,搭建实验平台分别对传统PID控制、BELC控制及改进的模糊BELC控制进行实验,结果表明:改进后模糊BELC算法有效提高了气动伺服系统的控制精度和响应速度,改善了气动系统控制性能。

As the pneumatic servo system is affected by non-linear factors,traditional PID control is not ideal for solving high-precision nonlinear control problems.A pneumatic servo system pressure control method based on Brain Emotion Learning Controller(BELC)was proposed.First,the mathematical modeling of pneumatic servo system is carried out.Then,combined with the aerodynamic system nonlinearity and BELC control characteristics,the algorithm is improved,and the fuzzy control is used to adjust the BELC weight learning rate online.Finally,the experimental platform was built to perform experiments on the traditional PID control,BELC control and improved fuzzy BELC control.The results show that the improved fuzzy BELC algorithm can effectively improve the control precision and response speed of the pneumatic servo system and improve the control performance of the aerodynamic system.