Design and Test on Fuzzy Neural Network of Constant Deceleration Braking of Hoist
One of the main reasons of lag in braking control technology of hoist exchange drag is that braking torque is not adjustable. And the braking torque of speed closedloop of fuzzy neural network controller (NNSOC) can not only ensure that deceleration in braking is constant, but also it can be regulated in the wider framework. The coil current of nozzle flapper valve of pressure closed-loop of NNSOC changes with the change of braking torque. Mze-I characteristic curve of the valve was simulated to obtain the braking torque expectation Mze). NNSOC adopted 3-layer structure of BP network, and network input / output samples were based on fuzzy rules and collected by simulation test. After doing repeated experiments, the experimental results show that that traingdx learning function and the best network structure can adjust network weights to memory and update the rules of NNSOC. The network testing results show that the response characteristics of NNSOC (braking torque and its overshoot of control current, network response time) can ensure that the braking deceleration is constant and the braking is smooth, safety, utility, energy-saving.
Hoist Constant deceleration braking speed and pressure of closed-loop NNSOC BP network Design and test
Lei Yongtao Yang Zhaojian Liu jimong
College of Mechanical Engineering of Taiyuan University of Technology Taiyuan, China
国际会议
长沙
英文
1637-1640
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）