Hou Zhongsheng, Jin Shangtai
Advanced Control Systems Laboratory of the School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China.
IEEE Trans Neural Netw. 2011 Dec;22(12):2173-88. doi: 10.1109/TNN.2011.2176141. Epub 2011 Nov 30.
In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.
本文针对一类一般的多输入多输出非线性离散时间系统，基于一种新的动态线性化技术（DLT）提出了一种数据驱动的无模型自适应控制（MFAC）方法，该技术具有一个名为伪偏导数的新概念。DLT包括紧凑形式动态线性化、部分形式动态线性化和全形式动态线性化。该方法的主要特点是控制器设计仅依赖于被控对象的测量输入/输出数据。分析和大量仿真表明，MFAC保证了有界输入有界输出稳定性和跟踪误差收敛。
