Global Stabilization of a Class of Inherently Nonlinear Systems under Sampled-data Control
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摘要: 针对一类含不确定参数的本质非线性系统,基于非光滑控制技术,提出了 一种基于采样控制的全局非光滑镇定方案. 首先,基于加幂积分技术和递归设计方法,提出了一类采样状态反馈控制器构造性设计方法.然后,通过合理地构造Lyapunvo泛函,严格地证明了存在一个最大采样周期 可以保证闭环系统的全局渐近稳定性. 由于控制器是离散形式的,所以在实际中易于用计算机来实现. 仿真结果验证了该方法的有效 性.Abstract: For a class of inherently nonlinear systems with uncertain parameters, the global stabilization problem via sampled-data control is investigated in this paper. First of all, based on the technique of adding a power integrator and a recursive argument, a class of sampled-data state feedback controllers are proposed. Then under the proposed controller, by using a suitable Lyapunov functional, it is shown that there is a maximum allowable sampling period which can guarantee the global asymptotical stability of the closed-loop system. Since the proposed controller is discrete-time, it can be easily implemented by computers. Finally, an example is given to verify the efficiency of the proposed method.
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