时滞不确定组合系统的鲁棒分散输出控制

讨论了时滞不确定组合系统的鲁棒分散输出控制问题．不确定项存在于子系统内部，可以是非线性或时交的：而且时滞存在互联项中，并满足匹配条件．不确定项是有界的，但界是未知的．利用自适应律来估计未知的上界，设计出分散无记忆输出控制器．基于Lyapunov稳定性理论和Lyapunov-Krasovskii函数，该控制器能够保证闭环系统的解是终极一致有界的．最后的仿真结果说明该设计方法是有效的．     

具有未知上界时滞状态扰动的非线性系统自适应鲁棒镇定

讨论了一类具有时滞状态扰动的非线性系统的自适应鲁棒镇定问题.时滞状态扰动的上界是未知的.在控制中通过自适应律估计上界的值,并且利用估计值设计鲁棒控制器.基于Lyapunov-Krasovskii函数,证明了闭环系统具有一致最终有界意义下的鲁棒稳定性.最后通过一个数值例子的仿真验证了结论的正确性.     

一类具有匹配时滞状态扰动的非线性系统自适应鲁棒镇定

讨论了一类具有时滞状态扰动的非线性系统的自适应鲁棒镇定问题,所考虑的时滞状态扰动的上界与时变函数相关并且含有未知参数.通过自适应律估计未知参数,并且利用估计值设计了鲁棒控制器.同时,基于Lyapunov_Krasovskii函数,证明了闭环系统具有一致最终有界意义下的鲁棒稳定性.最后,通过一个数值例子的仿真验证了结论的正确性.     

高阶耦合机器人的自适应模糊滑模分散控制

针对一类存在模型不确定性和未知非线性扰动的机器人系统,考虑其不确定项和未知扰动项的上界是关于系统状态的普通高阶多项式,结合模糊系统的逼近能力,提出了一种基于滑模控制原理的自适应模糊分散控制方法.该方法不仅能够使得关节之间相互耦合的机器人各关节的控制器仅由本关节的信息就能完全确定,而且消除了现存文献在设计机器人分散控制器...     

一类时滞大系统的分散弹性控制器设计:自适应方法

研究了一类时滞大系统的分散弹性自适应控制器的设计问题.当控制器增益摄动范数 有界但上界未知时,采用自适应方法,给出了系统一致有界稳定的条件和控制器的设计方案,且 该控制器具有在线调整的功能.并给出了特例情况下,即控制器增益摄动范数有界且上界已知 时,闭环系统可镇定的充分条件和相应弹性控制器的设计方案.数值算例说明了设计的可行性 和有效性.     

时变时滞非线性系统自适应神经网络控制

对于一类具有未知时变时滞和虚拟控制系数的不确定严格反馈非线性系统,基于后推设计提出一种自适应神经网络控制方案.选取适当的Lyapunov-Krasovskii泛函补偿未知时变时滞不确定项.通过构造连续的待逼近函数来解决利用神经网络对未知非线性函数进行逼近时出现的奇异问题.通过引入一个新的中间变量,保证了虚拟控制求导的正确性.仿真算例表明,所设计的控制器能保证闭环系统所有信号是半全局一致终结有界的,且跟踪误差收敛到零的一个邻域内.     

不确定时滞系统的自适应近似变结构控制

针对一类具有未知不确定性范数上界的线性时滞系统,设计自适应近似变结构控制器 ,对系统的不确定性范数上界进行在线估计,近似变结构控制器使系统进入滑模运动区域, 保证系统的一致终结有界性,进而用李雅谱诺夫函数方法分析了所得控制系统的性能．所提 出的近似自适应变结构控制器可以避免控制器中的不连续继电项,同时不必已知系统不确定 性范数界．用数字仿真例子验证了所提出控制器设计方法的有效性．     

一类严格反馈系统变比例增益精确微分补偿控制

针对包含不确定函数和未知外部扰动的一类严格反馈型非线性系统,提出基于精确扰动观测器的变比例增益自适应模糊控制器.系统中的未知不确定函数由模糊逻辑系统在线逼近,同时将模糊逻辑系统的逼近误差和未知外部扰动定义为总扰动,利用精确扰动观测器进行精确微分补偿控制. 将非线性函数应用于设计可调节的输出反馈增益,有效消除系统的稳态误差,使得系统跟踪误差可以控制在零的任意小邻域内.最后,通过Lyapunov定理证明闭环系统中所有信号均是有界的.数值仿真表明了所提出方案的有效性.     

控制方向未知的高次非线性系统的鲁棒自适应控制

研究了一类具有不可控不稳定线性化的非线性系统的自适应控制问题.该类系统的控制方向未知且含有不确定时变非线性参数.应用Nussbaum-type增益技术和adding a power integrator递推设计方法,设计了一种鲁棒自适应状态反馈控制器.所设计的控制器能够保证闭环系统的所有信号全局一致有界,且系统的状态渐近趋于零.除了假设未知参数及不确定性有界外,所设计的控制策略不需要控制系数的任何先验知识.仿真例子验证了算法的有效性.     

一类带时滞状态扰动系统的自适应鲁棒镇定

针对一类带时滞状态扰动的系统,讨论了系统的鲁棒自适应镇定问题.当扰动有界且界未知时,运用自适应控制方法,设计出一类自适应控制器.采用Lyapunov＿Karasovskii函数方法,证明了文中所提出的控制器可鲁棒镇定该系统.     

Decentralized adaptive robust control for a class of large scale systems with uncertainties in the interconnections

The problem of decentralized control is considered for a class of time-varying large scale systems with uncertainties and external disturbances in the interconnections. In this paper, the upper bounds of the uncertainties and external disturbances are assumed to be unknown. The adaptation laws are proposed to estimate such unknown bounds, and by making use of the updated values of these unknown bounds, a class of decentralized linear and non-linear state feedback controllers are constructed. It is shown that by employing the proposed decentralized non-linear state feedback controllers, the solutions of the resulting adaptive closed-loop large scale system can be guaranteed to be uniformly bounded, and the states are uniformly asymptotically stable. By using the decentralized linear state feedback controllers, one can guarantee the uniform ultimate boundedness of the resulting adaptive closed-loop large scale system. Finally, a numerical example is given to demonstrate the validity of the results.     

Robust adaptive fault‐tolerant tracking control of multiple time‐delays systems with mismatched parameter uncertainties and actuator failures

This study deals with the problem of robust adaptive fault‐tolerant tracking for uncertain systems with multiple delayed state perturbations, mismatched parameter uncertainties, external disturbances, and actuator faults including loss of effectiveness, outage, and stuck. It is assumed that the upper bounds of the delayed state perturbations, the external disturbances and the unparameterizable time‐varying stuck faults are unknown. Then, by estimating online such unknown bounds and on the basis of the updated values of these unknown bounds from the adaptive mechanism, a class of memoryless state feedback fault‐tolerant controller with switching signal function is constructed for robust tracking of dynamical signals. Furthermore, by making use of the proposed adaptive robust tracking controller, the tracking error can be guaranteed to be asymptotically zero in spite of multiple delayed state perturbations, mismatched parameter uncertainties, external disturbances, and actuator faults. In addition, it is also proved that the solutions with tracking error of resulting adaptive closed‐loop system are uniformly bounded. Finally, a simulation example for B747‐100/200 aircraft system is provided to illustrate the efficiency of the proposed fault‐tolerant design approach. Copyright © 2014 John Wiley & Sons, Ltd.     

基于观测器的一类非线性系统的自适应模糊控制

针对一类有界的不确定非线性系统设计了模糊观测器和自适应控制器.该方法不需要系统状态完全可测的条件,而是通过模糊观测器估计系统的状态变量并且能保证观测误差是一致最终有界的.该自适应控制器取得了良好的控制效果并且保证了跟踪误差的一致最终有界性.仿真结果表明了本文所提出的方法有效性.     

基于非线性增益递归滑模的船舶轨迹跟踪动态面自适应控制

针对三自由度全驱动船舶存在模型不确定和未知外部环境扰动的情况,设计出一种基于非线性增益递归滑模的船舶轨迹跟踪动态面自适应神经网络控制方法.该方法综合考虑船舶位置和速度误差之间关系设计递归滑模面,引入神经网络对船舶模型不确定部分进行逼近,设计带σ-修正泄露项的自适应律对神经网络逼近误差与外界环境扰动总和的界进行估计,并应用一种非线性增益函数构造动态面控制律,选取李雅普诺夫函数证明了该控制律能够保证轨迹跟踪闭环系统内所有信号的一致最终有界性.最后,基于一艘供给船进行仿真验证,结果表明,船舶轨迹跟踪响应速度快、精度高,所设计控制器对系统模型参数摄动及外界扰动具有较强的鲁棒性.     

一类中立时滞系统的一种改进的鲁棒自适应控制设计

The problem of adaptive robust control is addressed for a class of neutral delay systems. All uncertainties are assumed to be bounded by unknown constants. An improved adaptation law is proposed to estimate the square of these unknown bounds. Then, by making use of the updated values of the squared unknown bounds, an adaptive controller is designed to make the solution of the resultant closed-loop system uniformly ultimately bounded. Furthermore, this method avoids chattering and improves the performance. An example is given to illustrate the effectiveness of this method.     

Disturbance-observer-based sampled-data adaptive output feedback control for a class of uncertain nonlinear systems

In this paper, a sampled-data adaptive output feedback controller is proposed for a class of uncertain nonlinear systems with unmeasured states, unknown dynamics and unknown time-varying external disturbances. To approximate uncertain nonlinear functions, radial basis function neural networks (RBFNNs) are employed. The state observer and the disturbance observer (DO) are constructed to estimate the unmeasured state and the external disturbance, respectively. Then, the sampled-data adaptive output feedback controller and adaptive laws are designed by using the backstepping design technique. The allowable sampling period T is derived to guarantee that all states of the resulting closed-loop system are semi-globally uniformly ultimately bounded. Finally, two simulation examples are presented to illustrate the effectiveness of the proposed approach.     

Adaptive sliding mode observer‐based synchronization for uncertain chaotic systems

This paper investigates the synchronization problem for a class of uncertain chaotic systems. Only partial information of the system states is known. An adaptive sliding mode observer‐based slave system is designed to synchronize a given chaotic master system with unknown parameters and external disturbances. Based on the Lyapunov stability theorem, the global synchronization between the master and slave systems is ensured. Furthermore, the structure of the slave system is simple and the proposed adaptive sliding mode observer‐based synchronization scheme can be implemented without requiring a priori knowledge of upper bounds on the norm of the uncertainties and external disturbances. Simulation results demonstrate the effectiveness and robustness of the proposed scheme. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Adaptive fuzzy backstepping output feedback control for strict feedback nonlinear systems with unknown sign of high-frequency gain

In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of SISO nonlinear strict-feedback systems with unknown sign of high-frequency gain and the unmeasured states. The nonlinear systems addressed in this paper are assumed to possess the unmodeled dynamics, dynamical disturbances and unknown nonlinear functions, where the unknown nonlinear functions are not linearly parameterized, and no prior knowledge of their bounds is available. In the recursive designing, fuzzy logic systems are used to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unmodeled dynamics and the unknown sign of the high-frequency gain, respectively. Based on Lyapunov function method, a stable adaptive fuzzy output feedback control scheme is developed. It is mathematically proved that the proposed adaptive fuzzy control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded, the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples.     

Decentralised robust stabilisation of uncertain large-scale interconnected time-delay systems with unknown upper bounds of uncertainties

The problem of decentralised robust stabilisation is considered for a class of uncertain large-scale time-delay interconnected dynamical systems. In the paper, the upper bounds of delayed state perturbations, uncertainties, interconnection terms, and external disturbances are assumed to be completely unknown, and the delays are assumed to be any non-negative constants. For such a class of uncertain large-scale time-delay interconnected systems, a new method is presented whereby a class of adaptation-free decentralised local robust state feedback controllers can be constructed. In addition, it is also shown that the solutions of uncertain large-scale time-delay interconnected systems can be guaranteed to be uniformly ultimately bounded. Finally, as an application to the practical mechanical systems, some simulations of a numerical example are provided to demonstrate the validity of the theoretical results.