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Based on the decomposition of singular system, we propose a P-type iterative learning control law with initial state to track the desired output trajectory of the singular impulsive system. Then the convergence conditions of the open-loop iterative learning schemes is presented.
Based on a dynamic decomposition standard form of discrete singular systems, we propose a closed-loop PD-type iterative learning control algorithm to study the problem of the state tracking in this paper. Furthermore, we put forward the convergence conditions of the algorithm and prove the convergence of the algorithm theoretically. The effectiveness of the closed-loop PD-type iterative learning control...
In this paper, a fast online parameter estimation scheme with sinusoidal d-axis current injection is introduced. Compared to the existing parameter estimation strategies, the proposed estimation scheme has relative faster convergence time and is feasible in the transient operation. This estimation scheme is realized by the recursive least square algorithm based on different operating points of the...
LMS algorithm has low computation complexity; however, its convergence rate is slow. In this paper, a novel implementation scheme for LMS algorithm is proposed to form a modified LMS algorithm. The scheme is similar to the structure of turbo decoder, which consists of one feedback module called as converse-speediness module, two LMS algorithm modules, and one speediness module which connects two LMS...
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