Zhiguo Wang^*, Fangqing Gao, Fei Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 343-355, 2023, DOI:10.32604/cmes.2022.020569 - 24 August 2022

Abstract In this paper, an improved high-order model-free adaptive iterative control (IHOMFAILC) method for a class of nonlinear discrete-time systems is proposed based on the compact format dynamic linearization method. This method adds the differential of tracking error in the criteria function to compensate for the effect of the random disturbance. Meanwhile, a high-order estimation algorithm is used to estimate the value of pseudo partial derivative (PPD), that is, the current value of PPD is updated by that of previous iterations. Thus the rapid convergence of the maximum tracking error is not limited by the initial More >

Xiaoxin Yang¹, Saleem Riaz^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 605-626, 2022, DOI:10.32604/cmes.2022.020412 - 15 June 2022

Abstract An iterative learning control algorithm based on error backward association and control parameter correction has been proposed for a class of linear discrete time-invariant systems with repeated operation characteristics, parameter disturbance, and measurement noise taking PD type example. Firstly, the concrete form of the accelerated learning law is presented, based on the detailed description of how the control factor is obtained in the algorithm. Secondly, with the help of the vector method, the convergence of the algorithm for the strict mathematical proof, combined with the theory of spectral radius, sucient conditions for the convergence of More >