一类非线性切换系统的自适应神经动态面控制

针对一类严格反馈型不确定非线性切换系统,提出了一种鲁棒自适应神经动态面跟踪控制方案.该方案在基于共同Lyapunov函数的后推法设计中引入动态面控制(dynamic surface control,DSC)技术,利用径向基神经网络逼近构造的未知共同上界函数,并将滤波器输出导数取代传统中间变量作为神经网络输入,降低了网络输入维度;同时利用Young’s不等式技术有效减少了神经网络控制器的可调参数数目.此外,理论证明了该控制方案可以保证在任意切换下闭环系统所有信号半全局一致终结有界,且跟踪误差在有限时间收敛到零的小邻域内.实验结果表明了所提方法达到了很好的跟踪性能.     

任意切换下高能随机系统的神经网络预设控制

针对一类不确定高能随机非线性系统,开展自适应神经网络backstepping控制研究,并保证在任意切换信号下的预设跟踪性能.该高能系统假定系统动态和任意切换信号未知.首先,利用预设性能控制,保证跟踪控制性能;其次,RBF神经网络用来克服未知系统动态,仅用到单一自适应更新参数,从而克服过参数问题;最后,基于公共的Lyapunov稳定性理论提出自适应神经网络控制策略,并减少了学习参数.最终结果表明所设计的公共控制器能保证所有闭环信号半全局最终一致有界,并能在任意切换下保证预设的跟踪性能.仿真结果进一步表明所提出方法的有效性.     

切换非线性系统的输出反馈周期事件触发控制

本文针对一类在任意切换信号作用下的切换非线性系统, 研究了其输出反馈周期事件触发控制问题. 所考 虑的非线性系统采用非严格反馈形式且含有未知时变控制系数. 在本文中, 仅利用采样时刻的系统输出. 为了估计 系统的不可量测的状态, 基于采样的系统输出构造了降维状态观测器. 为了减少通信资源的利用, 提出了一种新的 输出反馈周期事件触发策略, 该策略包含仅利用事件触发时刻的信息构造的输出反馈事件触发控制器以及仅在采 样时刻间歇性监测的离散事件触发机制. 通过选取可容许的采样周期及合适的公共Lyapunov函数, 证明了闭环系统 在任意切换下全局渐近稳定. 最后, 通过将本文中所给出的控制方案应用到数值算例中验证了其有效性.     

严格反馈系统的事件触发学习控制

本文针对一类严格反馈非线性系统,提出了基于确定学习的事件触发控制方案.首先,在本地控制测试端设计自适应神经网络控制,并在控制过程中实现系统未知动态的知识获取和存储.随后,基于常值权值,设计了新颖的事件触发控制器和事件触发条件.结合李雅普诺夫稳定性分析和非线性脉冲动态系统原理,验证了所提方案能够保证跟踪误差收敛到零的小邻域内以及所有闭环信号是最终一致有界的.此外,本文所提方案采用常值权值代替了估计权值,使得所提方案易于实现,暂态性能好和网络资源占用少.最后,通过对比仿真结果证明了所提方案的有效性.     

一类线性切换系统的事件触发输出调节问题

通过设计事件触发状态反馈控制器,研究一类线性切换系统的输出调节问题.相比于时间触发控制,事件触发控制可显著地降低控制任务执行的次数.由于事件触发时刻与切换时刻的相互混合,导致切换系统控制器的设计十分困难.本文通过给出事件触发机制、状态反馈控制器和满足平均驻留时间的切换信号联合设计的方案,得到系统输出调节问题可解的充分条件.非共同坐标变换突破原有各子系统的调节器方程组具有共同解的限制.此外,为了避免Zeno现象,给出相邻事件触发间隔时间存在一个正下界.最后,应用切换RLC电路系统进行仿真验证结论的有效性.     

一类不确定非线性系统的鲁棒自适应控制

针对一类不确定非线性系统 ,设计出一种新的自适应控制器 ,它克服了现有方案存在的过多参数辨识问题 ,从而降低了控制器的动态阶次 .在较弱条件下 ,该控制器不仅能保证闭环系统所有信号有界 ,而且能使跟踪误差以指数速度收敛到零的有界小邻域内     

基于事件触发的离散 MIMO 系统自适应评判容错控制

本文针对具有执行器故障的一类离散非线性多输入多输出(Multi-input multi-output, MIMO)系统, 提出了一种基于事件触发的自适应评判容错控制方案. 该控制方案包括评价和执行网络. 在评价网络里, 为了缓解现有的非光滑二值效用函数可能引起的执行网络跳变问题, 利用高斯函数构建了一个光滑的效用函数, 并采用评价网络近似最优性能指标函数. 在执行网络里, 通过变量替换将系统状态的将来信息转化成关于系统当前状态的函数, 并结合事件触发机制设计了最优跟踪控制器. 该控制器引入了动态补偿项, 不仅能够抑制执行器故障对系统性能的影响, 而且能够改善系统的控制性能. 稳定性分析表明所有信号最终一致有界且跟踪误差收敛于原点的有界小邻域内. 数值系统和实际系统的仿真结果验证了该方案的有效性.     

基于观测器的周期拒绝服务攻击网络化系统动态事件触发控制

针对具有周期拒绝服务(DoS)攻击的网络化系统,设计一种基于观测器的具有动态事件触发策略的控制器.首先,通过DoS攻击对网络化系统的影响建立了DoS攻击模型,采用切换系统的方法,将具有DoS攻击的网络化系统分为DoS攻击活跃子系统和DoS攻击休眠子系统.对不可测的系统状态设计状态观测器,通过在静态事件触发中引入一个内部动态参数,设计了动态事件触发机制.利用动态事件触发序列设计基于观测器状态的控制器,同时,为保证系统在DoS攻击活跃期间子系统的稳定性,将当前最后一次成功触发状态作为DoS攻击活跃的控制信号,通过引入两个辅助函数得到闭环增广系统.其次,依据Lyapunov稳定性理论、Jensen's不等式和Schur补引理,得到两个切换子系统稳定充分条件,在此基础上引入DoS攻击限制得到具有LMI形式的切换系统渐近稳定的充分条件,同时给出了状态观测器、控制器和动态事件触发协同设计的参数.最后,通过一个数值例子验证所提方法的有效性.     

一类非线性切换系统任意切换采样控制设计

本文针对一类具有非严格反馈形式的非线性切换系统,在输出只在采样点可获得的情况下,提出了一种基于模糊采样观测器的自适应输出反馈控制方法.该方法降低了现有任意切换控制研究结果中因共同控制思想导致的控制器设计的保守性,避免了迭代过程对虚拟控制的反复求导引发的计算爆炸现象及控制器高增益的弊端.切换的自适应律突显了每个子系统的特性,建立的采样控制器节约了信息传输资源.共同Lyapunov函数理论确保了相应闭环切换系统所有变量在任意切换信号下的一致有界性.     

具有随机网络攻击的切换信息物理系统的事件触发控制（英文）

本文研究了随机网络攻击下切换信息物理系统的事件触发控制问题.将信息物理系统描述为一种切换线性系统形式.引入事件触发机制来节省系统资源和减轻网络负载,当误差超过给定阈值时传感器中的采样数据才通过通信网络传输到控制器中.考虑在传感器与控制器的通信网络中受到两种不同特征的随机网络攻击.在网络攻击和所设计的事件触发控制器下,建立了切换随机信息物理系统模型.利用模态依赖平均驻留时间方法构建了相应的切换信号.在设计的事件触发控制器和模态依赖平均驻留时间切换信号下实现了系统的均方指数稳定性,并给出了控制器增益.最后,通过实例验证了所得理论结果的有效性.     

Funnel‐like prescribed tracking control for uncertain nonlinear stochastic switched systems

This paper deals with the funnel‐like prescribed tracking control problem for a class of uncertain nonlinear stochastic switched systems. An improved performance technique is developed to restrain the fluctuation at the moment of switches and a new algorithm is proposed to address the funnel‐like prescribed tracking problem. First, a dynamic gain‐based switched K‐filter is constructed to estimate the unmeasured state information of the switched system. Subsequently, the performance technique is applied to prescribe output tracking error and restrain fluctuations of the system. Thereafter, the dynamic output feedback switched controller is designed by the use of the backstepping method. Moreover, based on the Lyapunov stability theory, it is proved strictly that all signals of the resulting closed‐loop system are bounded in probability if the switching signal satisfies the average dwell time. Finally, a numerical simulation is presented to illustrate the effectiveness of the proposed theoretical results.     

Multiple Lyapunov functions‐based adaptive neural network tracking control of uncertain switched nonlinear systems

In this paper, the problem of adaptive neural network (NN) tracking control of a class of switched strict‐feedback uncertain nonlinear systems is investigated by state‐feedback, in which the solvability of the problem of adaptive NN tracking control for individual subsystems is unnecessary. A multiple Lyapunov functions (MLFs)–based adaptive NN tracking control scheme is established by exploiting backstepping and the generalized MLFs approach. Moreover, based on the proposed scheme, adaptive NN controllers of all subsystems and a state‐dependent switching law simultaneously are constructed, which guarantee that all signals of the resulting closed‐loop system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. The scheme provided permits removal of a technical condition in which the adaptive NN tracking control problem for individual subsystems is solvable. Finally, the effectiveness of the design scheme proposed is shown by using two examples.     

Backstepping design for global stabilization of switched nonlinear systems in lower triangular form under arbitrary switchings

This paper is concerned with the global stabilization problem for switched nonlinear systems in lower triangular form under arbitrary switchings. Two classes of state feedback controllers and a common Lyapunov function (CLF) are simultaneously constructed by backstepping. The first class uses the common state feedback controller which is independent of switching signals; the other class utilizes individual state feedback controllers for the subsystems. As an extension of the designed method, the global stabilization problem under arbitrary switchings for switched nonlinear systems in nested lower triangular form is also studied. An example is given to show the effectiveness of the proposed method.     

Adaptive quantized tracking control for uncertain switched nonstrict‐feedback nonlinear systems with discrete and distributed time‐varying delays

This paper is concerned with an adaptive tracking problem for a more general class of switched nonstrict‐feedback nonlinear time‐delay systems in the presence of quantized input. The system structure in a nonstrict‐feedback form, the discrete and distributed time‐varying delays, the sector‐bounded quantized input, and arbitrary switching behavior are involved in the considered systems. In particular, to overcome the difficulties from the distributed time‐varying delays and the sector‐bounded quantized input, the mean‐value theorem for integrals and some special techniques are exploited respectively. Moreover, by combining the Lyapunov‐Razumikhin method, dynamic surface control technique, fuzzy logic systems approximation, and variable separation technique, a quadratic common Lyapunov function is easily built for all subsystems and a common adaptive quantized control scheme containing only 1 adaptive parameter is proposed. It is shown that the tracking error converges to an adjustable neighborhood of the origin whereas all signals of the closed‐loop systems are semiglobally uniformly ultimately bounded. Finally, 2 simulation examples are provided to verify the feasibility and effectiveness of the proposed design methodology.     

Neural networks stabilization and disturbance attenuation for nonlinear switched impulsive systems

In this paper, we address the problem of neural networks (NNs) stabilization and disturbance rejection for a class of nonlinear switched impulsive systems. An adaptive NN feedback control scheme and an impulsive controller for output tracking error disturbance attenuation of nonlinear switched impulsive systems are given under all admissible switched strategy based on NN. The NN is used to compensate for the nonlinear uncertainties of switched impulsive systems, and the approximation error of NN is introduced to the adaptive law in order to improve the tracking attenuation quality of the switched impulsive systems. Impulsive controller is designed to attenuate effect of switching impulse. Under all admissible switching law, impulsive controller and adaptive NN feedback controller can guarantee asymptotic stability of tracking error and improve disturbance attenuation level of tracking error for the overall nonlinear switched impulsive system. Finally, a numerical example is given to demonstrate the effectiveness of the proposed control and stabilization methods.     

Non-approximation-based outputs stabilization for switched large-scale nonlinear systems with quantized inputs and sensor uncertainties

A non-approximation-based output feedback control strategy for a class of switched large-scale nonlinear systems with quantized inputs and sensor uncertainties is proposed. A dynamic gain, which is shared by the state observers and controllers of all the subsystems, is designed so that the effects of sensor uncertainties, quantized inputs, unknown parameters, and external disturbances can be compensated. By constructing some common Lyapunov functions (CLFs) shared by the switched systems, it is proved that with the proposed scheme, the closed-loop system stability can be guaranteed under arbitrary switching, and the outputs of all the subsystems can be steered to within arbitrarily small neighborhoods of the origin.     

Adaptive event-triggered tracking control for a class of stochastic nonlinear systems with full-state constraints

This paper proposes an adaptive event trigger-based sample-and-hold tracking control scheme for a class of strict-feedback nonlinear stochastic systems with full-state constraints. By introducing a tan-type stochastic Barrier Lyapunov function (SBLF) combined with radial basis function neural networks (RBFNNs), which is used to approximate the nonlinear functions in backstepping procedures, an adaptive event-triggered controller is designed. It is shown with stochastic stability theory that all the states cannot violate their constraints, and Zeno behavior is excluded almost surely. Meanwhile, all the signals of the closed-loop systems are bounded almost surely and the tracking error converges to an arbitrary small compact set in the fourth-moment sense. A simulation example is given to show the effectiveness of the control scheme.     

Design proportional‐integral‐derivative/proportional‐derivative controls for second‐order time‐varying switched nonlinear systems

Based on proportional‐integral‐derivative (PID)/PD controls, we in the article investigate the tracking problem of a class of second‐order time‐varying switched nonlinear systems. To start with, for tracking a given point under arbitrary switching signals, we propose a sufficient condition about PID controller parameters, which can be implicitly described as semialgebraic sets. Successively, we consider the tracking problem under average dwell time (ADT)‐based switching signals and propose an alternative sufficient condition about PID controller parameters. Especially, for tracking an equilibrium point of the system without controls, we can further simply utilize the proportional‐derivative control and similarly construct corresponding semialgebraic conditions about proportional‐derivative controller parameters under arbitrary switching signals and ADT‐based switching signals. Finally, two examples are given to show the applicability of our theoretical results.