In this paper, we propose a new robust selfbtuning control, called the generalized minimum variance a/-equivalent self- tuning control （GMVSTC-a/） for the linear timevarying （LTV） systems, which can be described b...In this paper, we propose a new robust selfbtuning control, called the generalized minimum variance a/-equivalent self- tuning control （GMVSTC-a/） for the linear timevarying （LTV） systems, which can be described by the discrete-time auto-regressive exogenous （ARX） mathematical model in the presence of unmodelled dynamics. The estimation of the parameters contained in this mathematical model is made on the basis of the proposed modified recursive least squares （m-RLS） parametric estimation algorithm with dead zone and forgetting factor. The stability analysis of the proposed parametric estimation algorithm m-RLS is treated on the basis of a Lyapunov function. A numerical simulation example is used to prove the performances and the effectiveness of the explicit scheme of the proposed robust self-tuning control GMVSTC-a/.展开更多
基金partially funded by the Australian Research Council(No.DP110102076)
文摘In this paper, we propose a new robust selfbtuning control, called the generalized minimum variance a/-equivalent self- tuning control （GMVSTC-a/） for the linear timevarying （LTV） systems, which can be described by the discrete-time auto-regressive exogenous （ARX） mathematical model in the presence of unmodelled dynamics. The estimation of the parameters contained in this mathematical model is made on the basis of the proposed modified recursive least squares （m-RLS） parametric estimation algorithm with dead zone and forgetting factor. The stability analysis of the proposed parametric estimation algorithm m-RLS is treated on the basis of a Lyapunov function. A numerical simulation example is used to prove the performances and the effectiveness of the explicit scheme of the proposed robust self-tuning control GMVSTC-a/.
