Dynamic analysis of scissor hydraulic lift platform has been performed to investigate the key factors which determine size and shape of the platform. By using MATLAB, the position of hydraulic cylinder has been optimi...Dynamic analysis of scissor hydraulic lift platform has been performed to investigate the key factors which determine size and shape of the platform. By using MATLAB, the position of hydraulic cylinder has been optimized to reduce jacking force of piston and the whole system. Thus structure deformation decreases which is beneficial to control accuracy. Additionally, a new proportion integration differentiation (PID) control mode based on BP neural network has been developed to improve the stability and accuracy for the position control in this system. Compared with existing PID tuning methods and fuzzy self-adjusted PID controllers, the proposed back propagation (BP) based PID controller can achieve better performance for a wide range of complex processes and realize self-tuning of parameters. It was confirmed that the performance of the lift platform regarding the force variation and position accuracy was greatly enhanced by optimizing of the system both in structure and control. Considerable economic benefit can also be achieved through the application of this intelligent PID system.展开更多
基金Foundation item: Project(2012M521538) supported by China Postdoctoral Science Foundation Project suppolted by Postdoctoral Science Foundation of Central South University
文摘Dynamic analysis of scissor hydraulic lift platform has been performed to investigate the key factors which determine size and shape of the platform. By using MATLAB, the position of hydraulic cylinder has been optimized to reduce jacking force of piston and the whole system. Thus structure deformation decreases which is beneficial to control accuracy. Additionally, a new proportion integration differentiation (PID) control mode based on BP neural network has been developed to improve the stability and accuracy for the position control in this system. Compared with existing PID tuning methods and fuzzy self-adjusted PID controllers, the proposed back propagation (BP) based PID controller can achieve better performance for a wide range of complex processes and realize self-tuning of parameters. It was confirmed that the performance of the lift platform regarding the force variation and position accuracy was greatly enhanced by optimizing of the system both in structure and control. Considerable economic benefit can also be achieved through the application of this intelligent PID system.