Monotonic convergence conditions in PD type iterative learning control

Reza-Alikhani, Hamid-Reza; Madady, Ali

doi:10.1109/med.2011.5982987

2011 19th Mediterranean Conference on Control &Amp; Automation (MED) 2011

DOI: 10.1109/med.2011.5982987

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Monotonic convergence conditions in PD type iterative learning control

Hamid-Reza Reza-Alikhani

Ali Madady

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2016

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Monotonically convergent hybrid ILC for uncertain discrete-time switched systems with state delay

Wang

Luo

2016

Transactions of the Institute of Measurement and Control

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This paper is mainly devoted to a monotonically convergent iterative learning control (ILC) design for a class of uncertain discrete-time switched systems with state delay (UDTSDSs). By taking advantage of output error and state information, a hybrid ILC law for a class of UDTSDSs is proposed. After the ILC process is transformed into a 2D system, sufficient conditions in terms of linear matrix inequalities (LMIs) are derived by using a multiple Lyapunov–Krasovskii-like functional approach and a quadratic performance function. It is shown that if certain LMIs are met, the tracking error 2-norm converges monotonically to zero along the iteration direction, while the learning gains could be determined directly by solving the LMIs. The simulation results are provided to illustrate the theoretical analysis.

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Monotonically convergent hybrid ILC for uncertain discrete-time switched systems with state delay

Wang

Luo

2016

Transactions of the Institute of Measurement and Control

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show abstract

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Monotonic convergence conditions in PD type iterative learning control

Cited by 1 publication

References 16 publications

Monotonically convergent hybrid ILC for uncertain discrete-time switched systems with state delay

Monotonically convergent hybrid ILC for uncertain discrete-time switched systems with state delay

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