A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System

In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and...     

带状态约束的事件触发积分强化学习控制

为克服全状态对称约束以及控制策略频繁更新的局限,同时使得无限时间的代价函数最优,针对一类具有部分动力学未知的仿射非线性连续系统,提出一种带状态约束的事件触发积分强化学习的控制器设计方法。该方法是一种基于数据的在线策略迭代方法。引入系统转换将带有全状态约束的系统转化为不含约束的系统。基于事件触发机制以及积分强化学习算法,通过交替执行系统转换、策略评估、策略改进,最终系统在满足全状态约束的情况下,代价函数以及控制策略将分别收敛于最优值,并能降低控制策略的更新频率。此外,通过构建李亚普诺夫函数对系统以及评论神经网络权重误差的稳定性进行严格的分析。单连杆机械臂的仿真实验也进一步说明算法的可行性。     

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...     

输入饱和下非线性系统的事件触发控制器设计

本文研究了具有输入饱和的非线性系统事件触发控制策略设计问题.首先,针对输入饱和下非线性系统,建立混杂系统模型.其次,当非线性函数满足Lipschitz条件下,给出闭环混杂系统局部一致渐近稳定性的稳定判据,并设计了事件触发饱和控制器.然后,当非线性函数满足扇区条件时,给出闭环混杂系统框架下满足局部一致渐近稳定性的LMI条件,并设计了事件触发饱和控制器.进一步地,在事件触发饱和控制器作用下,分析了非线性系统的半全局鲁棒镇定性.最后,结合两个仿真实例说明了所提出事件触发控制策略的有效性.     

基于事件触发的Buck型DC-DC变换器有限时间控制

针对Buck型DC-DC变换器输出电压跟踪控制问题,提出了一种基于事件触发机制的有限时间控制方案。首先,将Buck变换器建模成一类反馈型非线性系统。然后,为能有效地避免通信资源的浪费,通过构造一种状态变换设计了一种事件触发机制;同时,利用反步法,设计了系统的状态反馈控制器,该控制器在事件触发时刻更新;然后,基于所设计的事件触发控制器,利用有限时间Lyapunov稳定性理论分析了系统的稳定性,并证明了所设计的控制方案不会发生Zeno现象;最后,通过Buck变换器仿真实例验证了所提出的事件触发控制方案的有效性,仿真结果表明了在所设计的控制方案下,Buck型DC-DC变换器的输出在有限时间内可以达到期望值,同时还能减少通信资源的浪费。     

Time-Varying Asymmetrical BLFs Based Adaptive Finite-Time Neural Control of Nonlinear Systems With Full State Constraints

This paper concentrates on asymmetric barrier Lyapunov functions (ABLFs) based on finite-time adaptive neural network (NN) control methods for a class of nonlinear strict feedback systems with time-varying full state constraints. During the process of backstepping recursion, the approximation properties of NNs are exploited to address the problem of unknown internal dynamics. The ABLFs are constructed to make sure that the time-varying asymmetrical full state constraints are always satisfied. According to the Lyapunov stability and finite-time stability theory, it is proven that all the signals in the closed-loop systems are uniformly ultimately bounded (UUB) and the system output is driven to track the desired signal as quickly as possible near the origin. In the meantime, in the scope of finite-time, all states are guaranteed to stay in the pre-given range. Finally, a simulation example is proposed to verify the feasibility of the developed finite time control algorithm.      

状态时延和全状态约束下的多智能体系统自适应事件触发控制

研究有向通信图下非线性多智能体系统的一致控制问题.首先,通过引入性能函数,使输出误差满足预定性能;其次,采用障碍Lyapunov函数,保证所有状态满足约束条件,结合李雅普诺夫-克拉索夫斯基(Lyapunov-Krasovskii,LK)泛函和杨氏不等式消除状态时延的影响,利用径向基函数神经网络(radial basis...     

Stability analysis of nonlinear systems in the presence of event-triggered impulsive control

This note puts forward continuous event-triggered impulsive control (CETIC) and dynamic event-triggered impulsive control (DETIC) to discuss a class of (integral) input-to-state stability (iISS, ISS) for nonlinear systems (NSs), where the impulse sequences are produced by certain predesigned event-triggering conditions. Different from traditionary event-triggered control (ETC), CETIC indicates that a controller will be stimulated only if the given state-dependent event condition is invoked. There exist no transfer of control between two continuous impulse triggered instants. Compared with the traditional static ETC, the DETIC can efficaciously lessen controller update and dramatically save energy at the same decay rate. In addition, all sample path solutions (SPS) for the system have the lowest time between events guaranteed to be positive. Utilizing CETIC strategy, we get some Lyapunov conditions to effectually avoid infinite triggering behavior and obtain the ISS-type stability of the investigative systems. Then, one applies the theoretical consequences to NSs and derive a class of ETC mechanism with impulsive control gains (ICG) by linear matrix inequalities (LMIs). Because of the existence of timer, the DETIC strategy naturally excludes Zeno phenomena. Furthermore, conclusions in this thesis permit the upper bound estimation for the differential Lyapunov function coefficient to be time-varying function instead of a constant in certain extant results, which means the criteria of the Lyapunov technique in this paper is less conservative and looser. Eventually, three examples with related simulations are demonstrated to indicate the rationalization and usefulness of our conclusion.     

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.     

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.     

Event-triggered adaptive control based on integral sliding mode surface for a class of linear systems with matched disturbance

In this paper, we propose an event-triggered adaptive integral sliding mode control scheme for a class of linear systems with external disturbance. In this method, the controller is designed using a triggered-state-dependent integral sliding mode, which can ensure the robustness and avoid the shortcomings of traditional sliding mode arrival stage. The triggering mechanism utilizes a time-varying trigger threshold instead of a traditional fixed threshold, which not only realizes the dynamic update of the control law, reduces the overhead of network communication but also ensures that the system trajectory enters the bounded area. The lower bound of inter event time guarantees the avoidance of the Zeno phenomenon. Next, in order to reduce the impact of high-frequency chattering of the control signal effectively and allow the gain of the discontinuous control term to be adjusted automatically according to the rate of change of the disturbance, a dual-layer nested adaptive gain scheme based on equivalent control is considered. This scheme does not require a priori boundedness of the disturbance and its rate of change. Through Lyapunov stability analysis, the event-triggered adaptive sliding mode controller can make the system trajectory converge in finite time and ensure the robustness of the control. Finally, the simulation results verify the effectiveness and simplicity of this method.     

Event-Triggered Sliding Mode Control for Trajectory Tracking of Nonlinear Systems

In this paper, an event-triggered sliding mode control approach for trajectory tracking problem of nonlinear input affine system with disturbance has been proposed. A second order robotic manipulator system has been modeled into a general nonlinear input affine system. Initially, the global asymptotic stability is ensured with conventional periodic sampling approach for reference trajectory tracking. Then the proposed approach of event-triggered sliding mode control is discussed which guarantees semi-global uniform ultimate boundedness. The proposed control approach guarantees non-accumulation of control updates ensuring lower bounds on inter-event triggering instants avoiding Zeno behavior in presence of the disturbance. The system shows better performance in terms of reduced control updates, ensures system stability which further guarantees optimization of resource usage and cost. The simulation results are provided for validation of proposed methodology for tracking problem by a robotic manipulator. The number of aperiodic control updates is found to be approximately 44% and 61% in the presence of constant and time-varying disturbances respectively.     

基于事件触发的非线性多智能体系统的固定时间分群一致性

结合事件触发控制方法研究非线性多智能体系统的固定时间分群一致性问题.提出一种非线性分布式事件触发分群一致性控制协议,并给出状态信息触发控制器更新的条件.该控制协议不受入度平衡条件限制,且只需自身状态信息与邻居智能体进行通信即可在固定时间内快速实现分群一致性.系统收敛时间与智能体的初始状态无关,可有效降低系统控制器更新频率和系统的资源消耗.结合代数图论、矩阵分析及Lyapunov稳定性理论,证明在所提出协议作用下,多智能体系统在固定时间内能够实现分群一致性,且不存在Zeno行为.最后,通过仿真实例检验了理论结果的可行性.     

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

This article is concerned with event-triggered fuzzy control design for a class of discrete-time nonlinear networked control systems (NCSs) with time-varying communication delays. Firstly, a more general mixed event-triggering scheme (ETS) is proposed. Secondly, considering the effects of the ETS and communication delays, based on the T-S fuzzy model scheme and time delay system approach, the original nonlinear NCSs is reformulated as a new event-triggered networked T-S fuzzy systems with interval time-varying delays. Sufficient conditions for uniform ultimately bound (UUB) stability are established in terms of linear matrix inequalities (LMIs). In particular, the quantitative relation between the boundness of the stability region and the triggering parameters are studied in detail. Thirdly, a relative ETS is also provided, which can be seen as a special case of the above proposed mixed ETS. As a difference from the preceding results, sufficient conditions on the existence of desired fuzzy controller are derived to ensure the asymptotic stability of the closed-loop system with reduced communication frequency between sensors and controllers. Moreover, a co-design algorithm for simultaneously determining the gain matrices of the fuzzy controller and the triggering parameters is developed. Finally, two illustrative examples are presented to demonstrate the advantage of the proposed ETS and the effectiveness of the controller design method.     

具有指定性能和全状态约束的多智能体系统事件触发控制

针对一类非严格反馈的非线性多智能体系统一致性跟踪问题,在考虑全状态约束和指定性能的基础上提出了一种事件触发自适应控制算法.首先,通过设计性能函数,使跟踪误差在规定时间内收敛于指定范围.然后,在反步法中引入Barrier Lyapunov函数使所有状态满足约束条件,结合动态面技术解决传统反步法产生的"计算爆炸"问题,并利用径向基函数神经网络（Radial basis function neural networks,RBF NNs）处理系统中的未知非线性函数.最后基于Lyapunov稳定性理论证明系统中所有信号都是半全局一致最终有界的,跟踪误差收敛于原点的有界邻域内且满足指定性能.仿真结果验证了该控制算法的有效性.     

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.     

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.     

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.     

不对称欠驱动水面机器人事件触发全局渐近镇定控制

本文研究了不对称欠驱动水面机器人事件触发全局渐近镇定控制问题.首先,引入坐标变换将系统全局渐近镇定控制问题转化为变换后模型欠驱动子系统的全局渐近镇定控制问题,利用周期时间函数构造时变辅助变量提出了一种时变连续的镇定控制律,并结合切换门限事件触发机制设计实际的事件触发推力与力矩控制输入使闭环系统全局渐近稳定.所提出的方法...