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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xudong Wang Xianping Xie Xiaogang Wu Tengwei Yu |
| Copyright Year | 2008 |
| Description | Author affiliation: Coll. of Electr. & Electron. Eng., Harbin Univ. of Sci. & Technol., Harbin (Xudong Wang; Xianping Xie; Xiaogang Wu; Tengwei Yu) |
| Abstract | For automatic clutch control system, precise and quick position tracking is difficult on account of its nonlinear character. A new clutch actuating mechanism with a whirl spring was devised for torque compensation to reduce the load of DC actuator and improve the dynamic performance of clutch control system firstly, and then a neuron adaptive PID controller with feedforward and adjustable gain was designed. The feedforward can accelerate the response of controller, and the weights of neuron adjust automatically through self-learning function so as to obtain adaptive control character, furthermore, PSD (proportion, sum and differentiation) algorithm was proposed to adjust its gain. The experiment results show that the position tracking error is smaller than that of common controller; and the controller can adapt the nonlinear change of clutch load and target engaging speed. It indicates that the controller has good robustness and can meet position tracking control command of clutch. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 296302 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424418480 |
| DOI | 10.1109/VPPC.2008.4677409 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-03 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Automatic control Programmable control Adaptive control Neurons Three-term control DC motors Control systems Torque control Target tracking Nonlinear control systems PSD algorithm automatic clutch position tracking neuron PID control |
| Content Type | Text |
| Resource Type | Article |
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