Robust Visual Servoing of Robot Manipulators with Neuro Compensation

This paper considers the problem of visual servoing of planar robot manipulators in the presence of uncertainty associated with robot dynamics, camera system and Jacobian matrix. By using radial basis function neural networks, these uncertainties can be compensated effectively. Two kinds of robust visual servoing are proposed, one is for image uncertainties, another is for Jacobian matrix uncertainty. By Lyapunov method and input-to-state stability technique, we prove that these robust controllers with neural compensators are stable. Real-time experiments are presented to show the applicability of the approach presented in this paper.     

Event-triggered sliding mode control of uncertain switched systems under denial-of-service attacks

This study is concerned with the event-triggered sliding mode control problem for a class of cyber-physical switched systems, in which the Denial-of-Service (DoS) attacks may randomly occur according to the Bernoulli distribution. A key issue is how to design the output feedback sliding mode control (SMC) law for guaranteeing the dynamical performance of the closed-loop system under DoS attacks. To this end, an event-triggered mechanism is firstly introduced to reduce the communication load, under which the measurement signal is transmitted only when a certain triggering condition is satisfied. An usable output signal for the controller is constructed to compensate the effect of unmeasured states and DoS attacks. And then, a dynamic output feedback sliding mode controller is designed by means of the attack probability and the compensated output signals. Both the reachability and the mean-square exponential stability of sliding mode dynamics are investigated and the corresponding sufficient conditions are obtained. Finally, some numerical simulation results are provided.     

Global adaptive fuzzy consensus control of nonlinear multi-agent systems via distributed event-triggered communication

This paper investigates globally bounded consensus of leader-following multi-agent systems with unknown nonlinear dynamics and external disturbance via adaptive event-triggered fuzzy control. Different from existing works where filtering and backstepping techniques are applied to design controllers and event-triggered conditions, a matrix inequality is established to obtain the feedback gain matrix and event-triggered functions. To save communication resources, a new distributed event-triggered controller with fully discontinuous communication among following agents is designed. Meanwhile, a strictly positive minimum of inter-event time is provided to exclude Zeno behavior. Furthermore, to achieve globally bounded leader-following consensus, an adaptive fuzzy approximator and a parameter estimator are designed to approximate the unknown nonlinear dynamics and parameters, respectively. Finally, the effectiveness of the proposed method is validated via a simulation example.     

Reduced-order K-filters-based event-triggered adaptive command filtered tracking control for stochastic constrained nonlinear systems

To ensure better performance and simultaneously save resources, an event-triggered adaptive command filtered dynamic surface control (ACFDSC) method for uncertain stochastic nonstrict-feedback nonlinear systems with dynamic output constraints and prescribed performance is designed in this article. Firstly, with the help of reduced-order K-filters, linearly parameterized neural networks and specific coordinate transformation technique, the unmeasurable states, nonlinearities, two types of unmodeled dynamics and output constraints are dealt with respectively. Then, an event-triggered ACFDSC strategy is proposed to ensure that the tracking error reaches a specific bound within a finite time. By introducing the compensated signal into the complete Lyapunov function, and with the assistance of the compact set defined in the stability analysis, all signals are strictly demonstrated to be semi-globally uniformly ultimately bounded. The simulation results verify the effectiveness of the proposed method.     

Adaptive fault compensation control for nonlinear uncertain fractional-order systems: Static and dynamic event generator approaches

The tracking problem of the fractional-order nonlinear systems is assessed by extending new event-triggered control designs. The considered dynamics are accompanied by the uncertain strict-feedback form, unknown actuator faults and unknown disturbances. By using the neural networks and the fault compensation method, two adaptive fault compensation event-triggered schemes are designed. Unlike the available control designs, two static and dynamic event-triggered strategies are proposed for the nonlinear fractional-order systems, in a sense that the minimum/average time-interval between two successive events can be prolonged in the dynamic event-triggered approach. Besides, it is proven that the Zeno phenomenon is strictly avoided. Finally, the simulation results prove the effectiveness of the presented control methods.     

Improved event-triggered control for networked control systems subject to deception attacks

This paper investigates the event-triggered control problem for networked control systems subject to deception attacks. An improved event-triggered scheme is proposed to reduce transmission rate by using both the information of the relative error and the past released signals. Under the proposed event-triggered scheme, a new switched time-delay system model is proposed for the event-triggered control systems. Based on the new model, the exponential mean-square stability criteria are derived by using the constructed Lyapunov function. Then, a co-design method is developed to obtain both trigger parameters and mode-dependent controller gains. Finally, the proposed scheme is verified by an unmanned aerial vehicle system.     

An improved design strategy for approximation-based adaptive event-triggered tracking of a class of uncertain nonlinear systems

This paper presents an improved adaptive design strategy for neural-network-based event-triggered tracking of uncertain strict-feedback nonlinear systems. An adaptive tracking scheme based on state variables transmitted from the sensor-to-controller channel is designed via only single neural network function approximator, regardless of unknown nonlinearities unmatched in the control input. Contrary to the existing multiple-function-approximators-based event-triggered backstepping control results with multiple triggering conditions dependent on all error surfaces, the proposed scheme only requires one triggering condition using a tracking error and thus can overcome the problem of the existing results that all virtual controllers with multiple function approximators should be computed in the sensor part. This leads to achieve the structural simplicity of the proposed event-triggered tracker in the presence of unmatched and unknown nonlinearities. Using the impulsive system approach and the error transformation technique, it is shown that all the signals of the closed-loop system are bounded and the tracking error is bounded within pre-designable time-varying bounds in the Lyapunov sense.     

Event-triggered adaptive control of multi-agent systems with saturated input and partial state constraints

In this paper, we study the consensus tracking control problem of a class of strict-feedback multi-agent systems (MASs) with uncertain nonlinear dynamics, input saturation, output and partial state constraints (PSCs) which are assumed to be time-varying. An adaptive distributed control scheme is proposed for consensus achievement via output feedback and event-triggered strategy in directed networks containing a spanning tree. To handle saturated control inputs, a linear form of the control input is adopted by transforming the saturation function. The radial basis function neural network (RBFNN) is applied to approximate the uncertain nonlinear dynamics. Since the system outputs are the only available data, a high-gain adaptive observer based on RBFNN is constructed to estimate the unmeasurable states. To ensure that the constraints of system outputs and partial states are never violated, a barrier Lyapunov function (BLF) with time-varying boundary function is constructed. Event-triggered control (ETC) strategy is applied to save communication resources. By using backstepping design method, the proposed distributed controller can guarantee the boundedness of all system signals, consensus tracking with a bounded error and avoidance of Zeno behavior. Finally, the correctness of the theoretical results is verified by computer simulation.     

Event-triggered adaptive NN control for MIMO switched nonlinear systems with non-ISpS unmodeled dynamics

This paper investigates the problem of event-triggered adaptive neural network (NN) control for multi-input multi-output (MIMO) switched nonlinear systems with output and state constraints and non-input-to-state practically stable (ISpS) unmodeled dynamics. A nonlinear mapping is firstly utilized to deal with output and state constraints. Also, by developing a new switching signal with persistent dwell-time (PDT) and a switching dependent dynamic signal, the difficulty caused by some non-ISpS unmodeled dynamics is overcome. Then, a type of switching event-triggering mechanisms (ETMs) and event-triggered adaptive NN controllers of subsystems are designed, which handle the issue of asynchronous switching without requiring any known restriction on maximum asynchronous time. A piecewise constant introduced into this ETM effectively ensures a strict positive lower bound of inter-event times. Zeno behavior is thus ruled out. Finally, by proposing a novel class of switching signals with reset PDT, it is ensured that all output and state constrains are never violated and all signals of the switched closed-loop system are semi-global uniform ultimate boundedness (SGUUB). A two inverted pendulum system and a numerical example are provided for illustrating the applicability and validity of the proposed method.     

An improved memory-event-triggered control for networked control systems

In this paper, the H_∞ control problem is investigated for a class of networked control systems with network-induced delay. A memory event-triggered scheme (METS) is proposed to reduce the redundant packet transmission in the network channel. Different from the normal event-triggered scheme (ETS), some recent released packets are stored at the event generator and controller sides, which are utilized for the first time to generate the triggered events and design the memory-based controller. The proposed METS has the following two merits. (1) The information of certain recent released signals are first utilized, which helps to improve the triggering instants at the crest or trough of the responses. (2) A state-dependent time-varying threshold parameter is designed, which can adjust the packet transmission rate according to the information of the state. Based on the proposed METS, a memory event-triggered controller is designed, the controller feedback gains and triggering parameters can be co-designed by solving a set of linear matrix inequalities. Finally, an example is given to illustrate the effectiveness of the proposed method.     

Input-to-state stabilization of time-delay systems: An event-triggered hybrid approach with delay-dependent impulses

This paper studies the input-to-state stabilization problem of nonlinear time-delay systems. A novel event-triggered hybrid controller is proposed, where feedback controller and distributed-delayed impulsive controller are taken into account. By using the Lyapunov-Krasovskii method, sufficient conditions for input-to-state stability are constructed under the designed event-triggered hybrid controller, the relation among control parameters, threshold parameter of the event-triggered mechanism and time delay in the impulsive signals is derived. Compared with the existing results, the obtained input-to-state stability criteria are applicable to time-delay systems with stabilizing delay-dependent impulsive effects and destabilizing ones. Numerical examples are provided to demonstrate the effectiveness of the theoretical results.     

Event-triggered robust practical output regulation of linear systems with non-vanishing measurements

This paper has studied the event-triggered robust output regulation for linear systems with non-vanishing measurements. A comprehensive event-triggered mechanism (ETM) is designed to determine the transmission instants of both sampling measurement signals and execution control signals. A kind of hybrid regulator has been proposed, consisting of a hybrid filter, observer, stabilizer, internal model, and compensator. Applying a generalized hold device makes the event-based regulator easy to implement. The proposed regulator and ETM achieve that all the closed-loop signals are bounded, and the regulated errors converge to a constant range, which can be adjusted arbitrarily small.     

Fuzzy event-triggered control for nonlinear networked control systems

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated.     

Event-triggered fully distributed asymptotic consensus for leaderless multiple Euler-Lagrange systems

In this paper, the fully distributed consensus for a class of multiple Euler-Lagrange systems is investigated, where the protocol is designed under the event-triggered control framework and the dynamics of Euler-Lagrange systems are heterogeneous. Since only local information interactions at triggered instants can be used and the Euler-Lagrange systems are of relatively complex dynamics, it is challenging to achieve asymptotic consensus without using any global information (such as the Laplacian matrix information). By skillfully integrating the adaptive control, distributed control and event-triggered control techniques, a novel protocol is proposed for the investigated multiple Euler-Lagrange systems. It is proven that the asymptotic consensus can be achieved by the developed protocol. By a numerical example, the effectiveness of the developed protocol is illustrated.     

Observer-based event-triggered tracking consensus of non-ideal general linear multi-agent systems

In this paper, the leader-following consensus problem of general linear multi-agent systems without direct access to real-time state is investigated. A novel observer-based event-triggered tracking consensus control scheme is proposed. In the control scheme, a distributed observer is designed to estimate the relative full states, which are used in tracking consensus protocol to achieve overall consensus. And an event-triggered mechanism with estimated state-dependent event condition is adopted to update the control signals so as to reduce unnecessary data communication. Based on the Lyapunov theorem and graph theory, the proposed event-triggered control scheme is proved to implement the tracking consensus when real-time state cannot direct obtain. Moreover, such scheme can exclude Zeno-behavior. Finally, numerical simulations illustrate the effectiveness of the theoretical results.     

Dual-Condition event-Triggered distributed adaptive neural control for multi-Agent systems with nonlinear fault

This paper studies the cooperative adaptive dual-condition event-triggered tracking control problem for the uncertain nonlinear nonstrict feedback multi-agent systems with nonlinear faults and unknown disturbances. Under the framework of backstepping technology, a new threshold update method is designed for the state event-triggered mechanism. At the same time, we develop a novel distributed dual-condition event-triggered strategy that combined the fixed threshold triggered mechanism acted on the controller with the new event-triggered mechanism, which can better reduce the waste of communication bandwidth. To deal with the algebraic loop problem caused by the non-affine nonlinear fault, the Butterworth low-pass filter is introduced. At the same time, the unknown function problems are solved by the neural network technology. All signals of the system are semiglobally uniformly ultimately bounded and the tracking performance is achieved, which proved by the Lyapunov stability theorem. Finally, the results of the simulation test the efficiency of the proposed control scheme.     

Distributed adaptive event-triggered protocol for tracking control of leader-following multi-agent systems

A novel adaptive event-triggered control protocol is developed to investigate the tracking control problem of multi-agent systems with general linear dynamics. By introducing the event-triggered control strategy, each agent can decide when to transfer its state to its neighbors at its own triggering instants, which can greatly reduce communication burden of agents. It is shown that the “Zeno phenomenon” does not occur by verifying that there exists a positive lower bound on the inter-event time intervals of agents under the proposed adaptive event-triggered control algorithm. Finally, an example is provided to testify the effectiveness of the obtained theoretical results.     

Event-triggered group consensus for multi-agent systems subject to input saturation

This paper investigates group consensus for leaderless multi-agent systems with non-identical dynamics. The consensus protocol is put forward in the form of the distributed event-triggered control subject to saturation, which depends on information from neighboring agents at event-triggered instants. In order to exclude the Zeno behavior and save resources, the given event-triggered condition is detected only at discrete sampling times, where the sampling intervals can be variable. Based on the graph theory, Lyapunov–Krasovskii functional method and by adopting the free-weighting matrix technique, some sufficient group consensus criteria in terms of linear matrix inequalities are derived. Furthermore, optimization problems aiming at maximizing the event-triggered parameter and the consensus region are proposed. Finally, numerical simulations illustrate the effectiveness of the theoretical results.     

Synchronization of switched logical control networks via event-triggered control

This paper investigates the event-triggered control design for state/output synchronization of switched k-valued logical control networks (SKVLCNs). Firstly, based on the algebraic form of SKVLCNs, some necessary and sufficient conditions are presented for the event-triggered state/output synchronization of SKVLCNs. Secondly, using the partitioning technique of matrix, a constructive procedure is proposed to design state feedback event-triggered controllers for the synchronization of SKVLCNs. Finally, an illustrative example is worked out to show the effectiveness of the obtained new results.     

Event-based H∞ filtering for discrete-time Markov jump systems with network-induced delay

The problem of event-based H_∞ filtering for discrete-time Markov jump system with network-induced delay is investigated in this paper. For different jumping modes, different event-triggered communication schemes are constructed to choose which output signals should be transmitted. Through the analysis of network-induced delay’s intervals, the discrete-time system, the event-triggered scheme and network-induced delay are unified into a discrete-time Markov jump filter error system with time-delay. Based on time-delay system analysis method, criteria are derived to guarantee the discrete-time Markov jump error system stochastically stable with an H_∞ norm bound. The correspondent filter and the event-based parameters are also given. A numerical example is given to show that the proposed filter design techniques are effective and event-triggered communication scheme can save limited network resources greatly.