个人信息Personal Information
讲师
性别:女
毕业院校:韩国亚洲大学
学位:硕士
所在单位:软件学院、国际信息与软件学院
电子邮箱:yhan@dlut.edu.cn
Global convergence property of iterative learning control algorithm based on damped newton-method
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论文类型:期刊论文
发表时间:2014-10-15
发表刊物:Journal of Computational Information Systems
收录刊物:EI、Scopus
卷号:10
期号:20
页面范围:8813-8820
ISSN号:15539105
摘要:We develop a novel iterative learning control (ILC) algorithm for sampled nonlinear systems. Damped Newton-method proposed here is used to solve problems of local convergence algorithms in iterative learning control. According to a particular iteration-varying learning gain, iterative learning law is constructed to remove rigorous condition of initial value close enough to the unknown desired input. Furthermore, a detailed convergence analysis is given. And the choice of parameter is considered in algorithm realization. It is shown theoretically that this algorithm can be ensured to be convergent in quadratic convergence speed without additional initial requirement. With the aid of simulation results, effectiveness of the proposed algorithm is illustrated. 1553-9105/Copyright ? 2014 Binary Information Press