Liu Yan-Jun, Tong Shao-Cheng, Wang Dan, Li Tie-Shan, Chen C L Philip
School of Sciences, Liaoning University of Technology, Jinzhou, China.
IEEE Trans Neural Netw. 2011 Aug;22(8):1328-34. doi: 10.1109/TNN.2011.2159865.
An adaptive output feedback control is studied for uncertain nonlinear single-input-single-output systems with partial unmeasured states. In the scheme, a reduced-order observer (ROO) is designed to estimate those unmeasured states. By employing radial basis function neural networks and incorporating the ROO into a new backstepping design, an adaptive output feedback controller is constructively developed. A prominent advantage is its ability to balance the control action between the state feedback and the output feedback. In addition, the scheme can be still implemented when all the states are not available. The stability of the closed-loop system is guaranteed in the sense that all the signals are semiglobal uniformly ultimately bounded and the system output tracks the reference signal to a bounded compact set. A simulation example is given to validate the effectiveness of the proposed scheme.
针对具有部分不可测状态的不确定非线性单输入单输出系统，研究了一种自适应输出反馈控制方法。在该方案中，设计了一个降阶观测器（ROO）来估计那些不可测状态。通过采用径向基函数神经网络并将ROO纳入一种新的反步设计中，构造性地开发了一种自适应输出反馈控制器。一个显著的优点是它能够在状态反馈和输出反馈之间平衡控制作用。此外，当所有状态都不可用时，该方案仍然可以实现。闭环系统的稳定性在所有信号都是半全局一致最终有界且系统输出跟踪参考信号到一个有界紧致集的意义上得到保证。给出了一个仿真例子来验证所提方案的有效性。
