基于T-S模糊模型的非线性系统鲁棒采样控制

Robust sampled-data control for nonlinear systems based on T-S fuzzy model

使用模糊采样控制方法研究一类T-S(Takagi-Sugeno)模糊模型描述的非线性系统鲁棒镇定问题.首先,充分利用整个采样区间[tk,tk+1)的特征信息,构造出一个改进的双边时间相关Lyapunov泛函.然后,结合提出的Lyapunov泛函和自由矩阵不等式,导出了确保非线性系统渐近稳定的鲁棒镇定条件,并给出模糊采样控制器设计方法.最后,通过4个例子仿真验证了提出方法的有效性和优越性.

The problem of robust stabilization for a class of nonlinear systems,which is described as Takagi-Sugeno(T-S)fuzzy model,is investigated through the use of fuzzy sampled-data control method.Firstly,by taking full advantage of characteristic information on the whole sampling interval[tk,tk+1),a improved two-side time-dependent Lyapunov functional is constructed.Furthermore,with the presented Lyapunov functional and free-matrix-based inequality,a robust stabilization criterion is derived to guarantee the asymptotic stability for nonlinear systems,and the fuzzy sampled-data controller design approach is also proposed.Finally,four simulation examples are given to verify the effectiveness and superiority of the proposed method.