非线性离散动态系统优化与参数估计集成的多模型方法

在非线性系统分时段线性化多模型基础上,给出了非线性离散动态系统优化与参数估计集成的多模型方法,并论证了算法的最优性和收敛性.在存在模型-实际差异的情况下,从分时段线性化多模型出发通过迭代运算可得到实际非线性离散动态系统的真实最优解.仿真结果表明了算法的有效性和实用性.     

非线性不确定系统的鲁棒性研究

1　引言非线性不确定系统的鲁棒性研究 ,早期是以在匹配条件 (matching condition)和广义匹配条件下 ,设计控制器使闭环系统达到实际稳定 (practical stabitity)为主 [1～ 3 ] .近些年利用 H∞ 控制理论的结果 ,出现了对具有有界结构的非线性不确定系统的鲁棒性讨论 [4～ 9] .模有界结构条件下 ,非线性不确定系统的鲁棒性有可能达到使状态趋于平衡点 ,而非仅仅实际稳定 .在文献 [4]中所讨论的非线性系统 ,要求其非线性部分具有线性界 .文献 [5 ]首次将模有界结构条件引入到线性不确定系统的鲁棒性研究中 .文献 [6]进一步讨论了这一结构下的…     

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.     

一类非线性时滞系统的状态反馈镇定

The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.     

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model （GFHM）. Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.     

一类非线性离散系统模糊控制器的分析和设计

针对一类非线性离散不确定系统,在系统状态不可测的情况下,以T-S模型描述不同状态空间的局部动态区域,并通过中心平均反模糊化、乘积推理、单点模糊化方法得到全局模糊系统模型.基于李亚普诺夫理论和线性矩阵不等式,设计了一种基于观测器的鲁棒控制器,并对离散状态下的此类系统进行了稳定分析.最后通过M ATLAB仿真,证明了该方法的有效性.     

基于观测器的滑模控制非线性中立型时滞系统

针对一类状态不可测的非线性不确定中立型时滞系统,基于滑模控制理论,采用线性矩阵不等式的处理方法,提出了滑动模态鲁棒渐近稳定时滞相关的充分条件,设计了一类滑模观测器,同时给出了该观测器存在的充分条件;然后应用滑模控制的趋近率方法和基于观测器所得到的系统估计状态,综合了一类滑模控制器,该控制器同时保证了估计状态下滑模面和估计误差状态下滑模面的渐近可达性;最后通过数值实例证明了该控制方案的可行性.     

基于跟踪误差调节的非线性自适应模糊预测控制

将模糊逻辑系统引入预测控制,对一类非线性离散系统提出了直接自适应模糊预测控制的方法,此方法首先建立被控对象的预测模型;然后基于此模型直接利用模糊逻辑系统设计预测控制器,并基于跟踪误差对控制器参数中的未知向量进行自适应调整;最后证明了此方法可使跟踪误差收敛到原点的一个小邻域内。     

ON STABILITY AND PERFORMANCE OF INDUCTION MOTOR SPEED DRIVES WITH SLIDING MODE CURRENT CONTROL

A novel inner loop sliding mode current control scheme for induction motor speed drives is proposed in this paper. The controller design is based on the nonlinear mathematical model of an induction motor in a coordinate system oriented along the rotor flux. The parameters of the PI speed controller are taken into consideration in the inner loop sliding mode current control. Rigorous stability verification for the overall system is provided in this paper. The chattering in sliding mode control is attenuated using the reaching law design method. The experimental results show that the proposed approach exhibits robust tracking performance in the presence of motor parameter variations and load disturbances.