具有输入和输出约束的高阶随机系统神经网络控制

针对高阶非线性系统,开展自适应神经网络跟踪控制器设计,系统受到随机扰动的影响.首次把输入和输出约束问题引入到高阶系统的跟踪控制中,并假定系统动态是未知.首先借用高斯误差函数表达连续可微的非对称饱和模型以实现输入约束,和障碍Lyapunov函数保证系统输出受限;其次,针对高阶非线性系统,径向基函数(RBF)神经网络用来克服未知系统动态和随机扰动.在每一步的backstepping计算中,仅用到单一的自适应更新参数,从而克服了过参数问题;最后,基于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.最终结果表明设计的控制器能保证所有闭环信号半全局最终一致有界,并能使跟踪误差收敛到零值小的邻域内.仿真研究进一步验证了提出方法的有效性.     

Adaptive consensus control for stochastic nonlinear multiagent systems with full state constraints

In this paper, the consensus tracking problem is investigated for stochastic nonlinear multiagent systems with full state constraints and time delays. The barrier Lyapunov functions proposed for single‐agent constrained systems are constructively extended to solve the consensus problem for multiagent systems with the full state constraints. Some Lyapunov‐Krasovskii functionals are introduced to compensate for state time delays, which are inherent in the complicated nonlinear systems. Based on the variable separation technique, the difficulty arising from the nonstrict‐feedback structure is overcome. Under a directed communication topology, the distributed neuroadaptive control protocols are proposed to guarantee that all the follower agents follow the trajectory of the leader agent and the full state constraints are not violated. The effectiveness of the proposed distributed adaptive control approach is verified via simulation examples.     

基于事件触发非线性多智能体系统的固定时间一致性

本文研究了在有向拓扑下,带有非线性动力学多智能体系统的固定时间一致性问题.提出了一种新的基于事件触发机制的非线性控制策略,对于每个智能体给出了基于状态信息的事件触发条件,当状态误差满足所给条件时才触发事件,能有效的减小系统的能量耗散和控制器的更新频次.利用Lyapunov稳定性理论和代数图论,证明在该控制策略下,多智能体系统在固定时间能实现领导跟随一致性,且不存在Zeno行为.相较于有限时间一致性策略,采用固定时间一致性策略系统的收敛时间不再依赖于系统的初始状态.最后,仿真实例验证了理论结果的有效性.     

具有时变通信受限非线性信息物理系统的网络化预测控制

针对具有时变通信受限的一类非线性信息物理系统,本文采用网络化预测控制策略,对于时变通信时延和数据丢失,不是使用常规的被动方式抑制,而是进行主动补偿.为了使补偿时变通信受限的方式简单、主动和通用,提出了一种新颖的网络化非线性预测控制方法.所设计的网络化非线性预测控制器能达到具有与无网络的本地闭环控制系统完全相同的期望控制...     

Finite-time tracking control for strict-feedback nonlinear systems with full state constraints

In this paper, an adaptive finite-time controller is considered for a class of strict-feedback nonlinear systems with parametric uncertainties and full state constraints. Novel tan-type barrier Lyapunov functions are proposed to ensure the boundedness of the fictitious state tracking errors. A new tuning function is constructed to eliminate the effect of uncertainties by using the extended finite-time stability condition. It is shown that under the proposed backstepping control scheme the finite-time convergence of system output tracking error to a small set around zero is realised and the full state constraints are not violated. A numerical example is provided to demonstrate the effectiveness of the proposed finite-time control scheme.     

Practical time-varying formation tracking for high-order nonlinear multi-agent systems based on the distributed extended state observer

Practical time-varying formation tracking analysis and design problems for high-order nonlinear multi-agent systems are investigated, where the time-varying formation tracking error is controlled within an arbitrarily small bound. The states of followers form a predefined time-varying formation while tracking the state of the leader with unknown control input. Besides, the dynamics of each agent has heterogeneous nonlinearity and disturbance. First, a distributed extended state observer is constructed to estimate the follower's nonlinearity and disturbance, and the leader's unknown control input simultaneously. A protocol based on the distributed extended state observer is proposed. Second, sufficient conditions for the multi-agent systems to achieve the practical time-varying formation tracking under the protocol are presented by using the Lyapunov stability theory. Third, an approach is derived to design the proposed protocol by solving a linear matrix inequality. Finally, numerical simulation results are given to illustrate the effectiveness of the theoretical results.     

具有全状态约束和未建模动态的严格反馈系统有限时间自适应动态面控制

针对一类具有全状态约束、未建模动态和动态扰动的严格反馈非线性系统,通过构造非线性滤波器,并利用Young’s不等式,提出一种新的有限时间自适应动态面控制方法.引入非线性映射处理全状态约束,将有约束系统变成无约束系统,利用径向基函数逼近未知光滑函数,利用辅助系统产生的动态信号处理未建模动态.对于变换后的系统,利用改进的动态面控制和有限时间方法设计的控制器结构简单,移去现有有限时间控制中出现的“奇异性”问题,可加快系统的收敛速度.理论分析表明,闭环系统中的所有信号在有限时间内有界,全状态不违背约束条件.数值算例的仿真结果表明,所提出的自适应动态面控制方案是有效的.     

Nussbaum gain adaptive fuzzy control for switched nonlinear systems with predefined output and full time-varying states constraints

In this paper, the problem of adaptive fuzzy tracking control for a class of uncertain switched nonlinear systems with unknown control direction is studied. Aiming at the problem, an adaptive control scheme with Nussbaum gain technology is constructed by using the average dwell time (ADT) method and the backstepping method to overcome the unknown control direction, and time-varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure the full-state constraints satisfaction. The proposed control scheme guarantees that all closed-loop signals remain bounded under a class of switching signals with ADT, while the output tracking error converges to a small neighborhood of the zero. An important innovation of this design method is that the unknown control direction, asymmetric time-varying full state constraints, and predefined time-varying output requirements are simultaneously considered in uncertain switched nonlinear systems for the first time. We set a moment in advance, and make the systems comply with the constraint conditions before running the moment by the shift function nested in the first time-varying ABLF. Finally, a simulation example verifies the effectiveness of the proposed scheme.     

Adaptive neural network dynamic event-triggered control for strong interconnected stochastic nonlinear systems with output constraint

This paper proposes a dynamic event-triggered mechanism based command filtered adaptive neural network (NN) tracking control scheme for strong interconnected stochastic nonlinear systems with time-varying output constraints. By designing a state observer, the unmeasured states of the systems can be estimated. The NNs are utilized to handle the unknown intermediate functions. In the controller design process, the asymmetric time-varying barrier Lyapunov functions are used to guarantee that the systems outputs do not violate the constraint regions. By integrating the command filter with variable separation technique, the controller design process is more simple, and the problem of algebraic-loop can be solved which caused by interconnected functions. According to the Lyapunov stability theory, it can be ensured that all signals of the systems are bounded in probability. Finally, the availability of the developed control scheme can be showed by the simulation example.     

Global output feedback stabilisation of high-order nonlinear systems with multiple time-varying delays

This paper investigates the problem of global output feedback stabilisation for a class of high-order nonlinear systems with multiple time-varying delays. By using backstepping recursive technique and the homogeneous domination approach, a continuous output feedback controller is successfully designed, and the global asymptotic stability of the resulting closed-loop system is proven with the help of an appropriate Lyapunov– Krasovskii functional. Two simulation examples are given to illustrate the effectiveness of the proposed approach.     

一类高阶非线性不确定系统自适应稳定控制

研究了一类高阶非线性不确定性系统的自适应稳定控制设计问题.因该系统的非线性程度高,其控制系数不等同、符号已知、但数值未知,故在此之前其稳定控制设计问题没有得到解决.本文应用自适应技术,结合设计参数的适当选取,从而得到了设计该类非线性系统状态反馈稳定控制器的新方法,并基于反推技术,给出了稳定控制器的设计步骤.所设计的状态反馈控制器使得闭环系统的状态全局渐近收敛于零,其余闭环信号一致有界.最后通过一个仿真例子说明了控制设计方法的有效性.     

Finite time adaptive filter control of nonlinear systems with actuator faults and state constraints

The finite time adaptive filter control problem is studied for strict-feedback nonlinear systems with actuator faults and state constraints in this paper. First, with the aid of the backstepping technique, the controller and the adaptive laws are designed to compensate the actuator faults and parameter uncertainties. Then, the dynamic surface control is used to establish a first-order filter to alleviate computational burden for the reason of the derivative of virtual control laws. In addition, none of the system states violate predefined constraint boundaries by utilizing a log-type barrier Lyapunov function. Furthermore, the boundedness can be ensured for all the closed-loop signals, and better tracking performance of the system is obtained within a finite-time. Finally, the simulation examples are shown to prove the feasibility and effectiveness of the proposed strategy.     

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.     

Multi-stage dynamic event-triggered containment control of nonlinear multi-agent systems with input-bounded leaders and time-varying delay

This article immerses in the event-triggered containment control problem for a Lipschitz-like nonlinear multi-agent system with multiple active leaders. First, two event-triggered mechanisms with internal dynamic variables are designed in both sensor-observer (S-O) and controller-actuator (C-A) channels to monitor data transmission and reduce communication burden. Second, an observer is constructed with the aid of the output information to estimate the states that cannot be acquired directly. Then, a control protocol considering time-varying communications delays is proposed based on the observer. Third, the boundedness analysis of the containment error system is constructed by Lyapunov stability theory, the sufficient conditions are given in light of strict feasible LMIs. Finally, the validity of the proposed controller is verified by two simulations.     

Arbitrary settling time control with prescribed performance for high-order nonlinear systems

This paper studies an arbitrary convergence time tracking controller design problem for high-order nonlinear systems. Our aim is to enhance the existing free-will arbitrary time control (FATC), which cannot track time-varying reference signals. To do so, a new nonautonomous equation is firstly introduced to enable an arbitrary settling time stability for one-order systems. Then, a prescribed performance control (PPC) technology is integrated for general high order systems. By a backstepping Lyapunov analysis with iteratively contructed nonautonomous equations, it is proved that the closed-loop system satisfies the prescribed performance and all signals of the closed-loop system are arbitrary settling time stable (ASTS). Compared with the existing results, the tracking control problem with arbitrary convergence time is addressed by a continuous control law, which shows a better transient performance also. Simulation results confirm the effectiveness of the proposed control method.     

Dynamic event-triggered prescribed performance control for nonlinear systems with signal temporal logic

This article is concerned with the problem of dynamic event-triggered prescribed performance control for nonlinear systems under signal temporal logic tasks. By utilizing the method of prescribed performance control, the constrained plant can be transformed into an unconstrained one, and a dynamic event-triggered feedback control law is generated for the transformed system to ensure that the signal temporal logic specification is satisfied. A dynamic event-triggered mechanism is designed to guarantee the event-triggered stability, safety and complex specification. Besides, Zeno phenomenon is definitely avoided. Compared with the continuous-time feedback controller, the event-triggered controller has proven to be effective in reducing sensing, communication and computation costs. Finally, two simulations are given to illustrate the effectiveness of theoretical results.     

Robust adaptive fault-tolerant control for time delay uncertain nonlinear systems with time-varying performance bounds

In this paper, a robust adaptive fault tolerant controller guaranteeing with time-varying performance bounds is designed for a class of time delay uncertain nonlinear systems subject to actuator failures and external disturbance. The influence of time delay on the system is mitigated and the system performance can be guaranteed by introducing a positive nonlinear control gain function and the generalised restricted potential function. A new method with more design degrees of freedom is developed to ensure the norm of the system state within a-priori, user-defined time varying performance bounds. Using the online estimation information provided by adaptive mechanism, a robust adaptive fault-tolerant control method guaranteeing time varying performance bounds is proposed. It is shown that all the signals of the resulting closed-loop system are bounded and the system state less than a-priori, user-defined performance bounds. Finally, simulation results are given to demonstrate the efficacy of the proposed fault-tolerant control method.     

Hybrid threshold strategy‐based adaptive tracking control for nonlinear stochastic systems with full‐state constraints

This article focuses on the adaptive tracking control problem for a class of interconnected nonlinear stochastic systems under full‐state constraints based on the hybrid threshold strategy. Different from the existing works, we propose a novel pre‐constrained tracking control algorithm to deal with the full‐state constraint problem. First, a novel nonlinear transformation function and a new coordinate transformation are developed to constrain state variables, which can directly cope with asymmetric state constraints. Second, the hybrid threshold strategy is constructed to provide a reasonable way in balancing system performance and communication constraints. By the use of dynamic surface control technique and neural network approximate technique, a smooth pre‐constrained tracking controller with adaptive laws is designed for the interconnected nonlinear stochastic systems. Moreover, based on the Lyapunov stability theory, it is proved that all state variables are successfully pre‐constrained within asymmetric boundaries. Finally, a simulation example is presented to verify the effectiveness of proposed control algorithm.     

Distributed fuzzy adaptive event-triggered finite-time consensus tracking control for uncertain nonlinear multi-agent systems with asymmetric output constraint

This article investigates the consensus problem for uncertain nonlinear multi-agent systems (MASs) with asymmetric output constraint. Different from BLF-based constraint consensus tracking control, a novel approach based on nonlinear state-dependent function is proposed to solve the asymmetric output constraint, which need not convert output constraint into tracking error bound. First-order sliding mode differentiator is incorporated into each step of backstepping control design to reduce computation burden. Further, in combination of proposed event-triggered mechanism based on time-varying threshold, a distributed fuzzy adaptive event-triggered finite-time consensus method is developed. It can ensure that the consensus tracking error tends to a small neighbor in a finite time and the asymmetric output constraint of each subsystem is not violated. Two simulations are given to demonstrate the effectiveness of control method.     

Output-feedback stabilization for stochastic high-order nonlinear systems with time-varying delay

This paper investigates output-feedback control for a class of stochastic high-order nonlinear systems with time-varying delay for the first time. By introducing the adding a power integrator technique in the stochastic systems and a rescaling transformation, and choosing an appropriate Lyapunov-Krasoviskii functional, an output-feedback controller is constructed to render the closed-loop system globally asymptotically stable in probability and the output can be regulated to the origin almost surely. A simulation example is provided to show the effectiveness of the designed controller.