Adaptive Control Protocol Research Articles

Adaptive dynamic event-triggered cluster consensus for second-order delayed MASs with input saturation

In this paper, the cluster consensus problem of second-order multi-agent systems (SOMASs) is investigated in which cooperative-competitive interactions among agents, input time delay, and input saturation are involved simultaneously. A novel adaptive dynamic event-triggered control (ETC) protocol is first designed to realize cluster consensus. Since the constant in static trigger condition is replaced by a dynamic parameter, the new control scheme can reduce the trigger times and save energy consumption. Then, switching topology problem of heterogeneous multi-agent systems (MASs) is also discussed based on the dynamic ETC strategy. Some sufficient conditions for achieving the cluster consensus of SOMASs are proposed by utilizing the Lyapunov stability theory and algebraic graph theory. Especially, to solve the saturation problem, Lagrange mean value theorem is adopted. Moreover, it is also proved that no Zeno behavior occurs under the proposed control protocol. Finally, two examples justify the significance of our theoretical results.

Robust Bearing-Based Formation Tracking Control of Underactuated Surface Vessels: An Output Regulation Approach

This article is concerned with the robust formation tracking control of a group of underactuated surface vessels whose formation is characterized by the relative bearings between the vessels. Control protocols are proposed to asymptotically steer certain points on the vessels, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hand points</i> , which lie ahead of their centers of mass along the longitudinal axes, to track the desired moving formation; such a control method is called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">an output regulation approach</i> . The moving formation is guided by the motions of two or more agents, which are referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">leaders</i> , and the other <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">follower</i> agents track the leaders by maintaining bearing constraints to neighbors. The proposed control schemes are designed based on a backstepping technique and sliding mode control. The latter is employed to attenuate known bounded disturbances present in the vessels' dynamics. When the bounds of the disturbances are unknown, an adaptive control protocol is subsequently investigated, under which the system is shown to converge to a small neighborhood of the target formation. Further, sufficient conditions on the upper bound of the hand points' desired velocities are provided for the uniform ultimate boundedness of the vessels' internal sway-yaw dynamics. Simulation results are provided to support the theoretical analysis.

Reinforcement learning-based optimal adaptive fuzzy control for nonlinear multi-agent systems with prescribed performance

In this paper, the problem of optimal adaptive consensus tracking control for nonlinear multi-agent systems with prescribed performance is investigated. To address the issue of satisfying the initial value conditions in existing results, an improved performance function is employed as the prescribed performance boundary, effectively resolving this problem. Then, by employing the error transformation function, the constrained system is converted into an unconstrained one. Furthermore, fuzzy logic systems are employed to identify unknown system parts. By applying the dynamic surface technique, the problem of "differential explosion", which often occurs in backstepping, is solved. Moreover, a distributed optimal adaptive fuzzy control protocol based on the reinforcement learning actor-critic algorithm is proposed. Under the proposed control scheme, it is proved that all the signals within the closed-loop system are bounded, and the consensus tracking errors have remained within the predefined bounds. Finally, the numerical simulation results demonstrate the effectiveness of the proposed scheme.

Adaptive and optimal regulation controller design for fractional linear multi‐agent systems

SummaryThis express brief is concerned with the adaptive and optimal regulation control for fractional linear multi‐agent systems (MASs). Firstly, the adaptive control strategy is applied to address the regulation issue for fractional linear MASs with time varying edges. Under the designed adaptive control protocols with adaptive edge‐dependent synchronization gain, the regulation condition is achieved by constructing a Lyapunov functional with the edges. Secondly, the optimal control approach is used to solve the regulation issue for fractional linear MASs with constant edges. The optimization gain is chosen by minimizing an appropriate performance function. Moreover, the synchronization objectives are also achieved based on the proposed the regulation conditions. Finally, the correctness of the theoretical analysis and the feasibility of the designed controllers are verified by two numerical examples.

A Review on Dynamic Network Using Flexible Active-Mode Period Scheme for Telemedicine

Challenges associated with transmitter node during the process of intelligent transceiver nodes attempting to be active state after receiving a message outside its time slot schedule which might result in energy depletion through receiver node are the most notable origin of excessive energy consumption in the system. Various methods have been carried out to minimize the overhead cost. In this article, we presented the Dynamic Network using Adaptive Wake-Up Interval Media Access Control (MAC) protocol for Wireless Body Area Networks (WBANs) for telemedicine which could lead to the minimization of the energy consumption in the network and maximization of network lifetime. A Receiver Controlled mechanism balances the number of wake-up periods between Receiver node and Transmitter nodes and estimation of traffic load. This article depicts no earlier examination of dynamic network using Flexible Active-Mode period scheme-based media access control protocol for WBAN. Therefore, this review work could lead to the improvement of dynamic network Flexible Active-Mode –media access control protocols and invigorate a clearer way of finding AWI-Media Access Control protocol problems.

Event-Triggered Bounded Consensus Tracking for Second-Order Nonlinear Multi-Agent Systems with Uncertainties.

This paper is concerned with event-triggered bounded consensus tracking for a class of second-order nonlinear multi-agent systems with uncertainties (MASs). Remarkably, the considered MASs allow multiple uncertainties, including unknown control coefficients, parameterized unknown nonlinearities, uncertain external disturbances, and the leader's control input being unknown. In this context, a new estimate-based adaptive control protocol with a triggering mechanism is proposed. We rule out Zeno behavior by testifying that the lower bound on the interval between two consecutive events is positive. It is shown that under the designed protocol, all signals caused by the closed-loop systems are bounded globally uniformly and tracking errors ultimately converge to a bounded set. The effectiveness of the devised control protocol is demonstrated through a simulation example.

Adaptive Synchronization of Second-Order Leader-Following Multiagent Systems

This article considers a distributed adaptive control scheme for a class of second-order leader-following multiagent systems with only position information as output. An auxiliary network for the agent network is modeled to estimate the unmeasurable velocity information and make the output-based distributed adaptive control protocol effective. Under the distributed adaptive control scheme based on the auxiliary network model, several distributed synchronization criteria are established, and the corresponding convergence analysis is provided based on the stability theory. Finally, several simulation examples are provided to conform to the presented criteria.

Periodic Intermittent Adaptive Control with Saturation for Pinning Quasi-Consensus of Heterogeneous Multi-Agent Systems with External Disturbances.

A periodic intermittent adaptive control method with saturation is proposed to pin the quasi-consensus of nonlinear heterogeneous multi-agent systems with external disturbances in this paper. A new periodic intermittent adaptive control protocol with saturation is designed to control the internal coupling between the follower agents and the feedback gain between the leader and the follower. In particular, we use the saturation adaptive law: when the quasi-consensus error converges to a certain range, the adaptive coupling edge weight and the adaptive feedback gain will not be updated. Furthermore, we propose three saturated adaptive pinning control protocols. The quasi-consensus is achieved through its own pinning as long as the agents remain connected to each other. Using the Lyapunov function method and inequality technique, the convergence range of the quasi-consensus error of a heterogeneous multi-agent system is obtained. Finally, the rationality of the proposed control protocol is verified through numerical simulation. Theoretical derivation and simulation results show that the novel proposed periodic intermittent adaptive control method with saturation can successfully be used to achieve the pinning of quasi-consensus of nonlinear heterogeneous multi-agent systems.

Consensus tracking and vibration control for multiple single-link flexible manipulators with input signal quantization

This study examines consensus tracking and vibration control of a multiagent system consisting of multiple single-link flexible manipulators with input signal quantization. The dynamics of each flexible manipulator are described by fourth-order partial differential equations (PDEs). A logarithmic quantizer with changeable parameters is adopted to quantize control inputs, and adaptive laws are designed to compensate for the effect caused by quantization. A distributed adaptive boundary control protocol is proposed based on the PDE model to ensure all manipulators track the desired angular position and eliminate vibrations without knowledge of quantizer parameters. The proposed control protocol is proven to ensure the uniformly bounded stability of the closed-loop system. Simulations are carried out under three cases to illustrate the effectiveness of the designed strategy.

Dynamic event-triggered adaptive semi-global bipartite consensus of linear multi-agent systems with input saturation under fixed and switching topologies

This paper investigates dynamic event-triggered adaptive leader-following semi-global bipartite consensus (SGBC) of multi-agent systems (MASs) with input saturation. A dynamic event-triggered adaptive control (DETAC) protocol is presented, where the triggering function can regulate its threshold value dynamically. It’s turned out that the SGBC can be achieved via the DETAC protocol under some inequalities. Then, the proposed DETAC protocol is extended to solve bipartite consensus under jointly connected topology. Furthermore, the Zeno behaviors will be avoided. Finally, the rationality of proposed DETAC protocols are tested by simulation results.

Adaptive Consensus of the Stochastic Leader-Following Multi-Agent System with Time Delay

For the multi-agent system with time delay and noise, the adaptive consensus of tracking control problems is discussed by the Lyapunov function. The main purpose of this study is to design an adaptive control protocol for the system, such that even if there exists time delay among agents, the protocol can still ensure the consensus of the stochastic system. The main contribution is to revise the protocols that were previously only applicable to system without time delay. Because the system is inevitably disrupted by time delay and noise during the interactive process, achieving coordination and consensus is difficult. To enable the followers to track the leader, a novel adaptive law depending on the Riccati equation is firstly proposed, and the adaptive law is different from previous mandatory control law completely depending on a known function. The ability to be altered online based on the state of system is a major feature of the adaptive law. When there are interactive noise and time delay between the followers and leader of the system, a special Lyapunov function is constructed to prove the adaptive consensus. And the upper bound of time delay is obtained by using the Itô integral theory. Finally, if the time delay of the system approaches zero, it is shown that the adaptive law still ensures that each follower tracks the leader under simpler conditions.

Adaptive Bipartite Leaderless Consensus of Multiagent Systems With Uncertain MIMO Dynamics Over a Signed Directed Graph

This paper investigates the bipartite leaderless consensus problem for uncertain multi-input multi-output (MIMO) multi-agent systems (MASs) over a directed cooperation-competition network. An adaptive control protocol is proposed to achieve the bipartite consensus for agents in the presence of matching uncertainties. It is required that the signed directed graph should be structurally balanced and contain a directed spanning tree. A numerical example is performed to verify the effectiveness of the proposed algorithm.

Hierarchical Structure-Based Fixed-Time Optimal Fault-Tolerant Time-Varying Output Formation Control for Heterogeneous Multiagent Systems

This article studies the issue of distributed hierarchical fixed-time optimal fault-tolerant output formation for heterogeneous multiagent systems (MASs). A two-layer formation control framework is proposed by using distributed optimization and cooperative fault-tolerant output regulation approaches. The upper layer includes a virtual system and a distributed fixed-time optimization control algorithm to produce a global optimal reference signal, which minimizes the global objective function in a fixed time. The lower layer includes an actual agent system and an adaptive fixed-time fault-tolerant tracking control protocol to compensate for the actuator faults and ensure the fixed-time tracking of the optimal formation trajectory composed of the optimal reference signal and the expected time-varying formation vector. Different from the relevant works, this framework can avoid the phenomenon of fault propagation between neighboring agents by the interaction network. Furthermore, the convergence time of the formation error is not relied on the initial conditions of MASs. Finally, two simulation experiments are designed to prove the effectiveness of the developed theoretics.

Event‐triggered‐based secure adaptive NN consensus tracking control of switched multi‐agent systems

AbstractThis paper addresses the problem of event‐triggered‐based secure adaptive neural‐networked (NN) consensus tracking control for a class of switched nonlinear multi‐agent systems (MASs) with unknown control directions under network attacks. In order to mitigate the effects of sensor and actuator attacks, a new event‐triggered‐based secure adaptive NN consensus tracking control protocol is proposed by exploring backstepping and the average dwell time method and the Nussbaum gain technique. In addition, if the switching happens between any two consecutive triggering instants, then asynchronous switching between subsystems of each follower and candidate controllers of subsystems will arise. Without any strict limitation on maximum asynchronous time, the asynchronous switching is handled by constructing a novel switching event‐triggered mechanism (ETM) and event‐triggered‐based adaptive NN controllers of subsystems for each follower. Meanwhile, the protocol proposed can guarantee that consensus tracking errors converge to a small neighborhood of the origin. Also, a strictly positive lower bound on inter‐event time is guaranteed. Finally, a practical example is presented to illustrate the effectiveness of the developed protocol.

Distributed Resilient Tracking of Multiagent Systems Under Actuator and Sensor Faults.

The distributed resilient tracking problem for multiagent systems (MASs) is investigated in the presence of actuator/sensor faults over directed topology. Both actuator fault and sensor fault are taken into account. Meanwhile, using the local information, the fault compensators are introduced. Then, based on the fuzzy-logic systems (FLSs) and modification technique of adaptive law, a novel distributed adaptive resilient control protocol is developed, which can compensate the effect of faults on the actuator and sensor. It turns out that all signals of MASs are bounded, while the tracking errors enter an adjustable bounded region around the origin. Toward the end, two simulations are provided to validate the effectiveness of the theoretical results.

Fixed-Time Formation Tracking Control of Nonlinear Multi-Agent Systems with Directed Topology and Disturbance

In this paper, we study the fixed-time formation (FixF) control problem for the nonlinear second-order multi-agent systems (MASs) with directed graph, where all agents are subject to communication disturbances. To overcome the bounded disturbance of communication and to guarantee the realization of predesignated formation within a fixed-time, a suitable FixF control protocol based on the backstepping method is proposed. Furthermore, to eliminate the dependence of the control parameters on global information, a new adaptive FixF control protocol is provided to combine with some mild conditions of control gain such that the formation with acceptable bounded error of MASs can be achieved within a fixed-time. Finally, the theoretical results are verified by two simulation examples, one of the simulation examples is that we set the desired formation as a regular octagon and the desired formation motion trajectory as a circle, the results show that all agents can form formation motion within a fixed-time.

Distributed global adaptive bipartite consensus of multi-agent systems with signed communication topology structure

This paper focuses on designing a fully distributed adaptive fuzzy bipartite consensus control protocol for unknown nonlinear multi-agent systems with a class of undirected signed graph. Utilizing the fuzzy logical system universal approximator as a compensator to describe the uncertain nonlinear dynamics, a fully distributed adaptive fuzzy control protocol is proposed by means of re-parameterized approach and bounding technique, the global bipartite consensus of leader-following multi-agent systems without using any dynamics of the leader is proven via constructing a new Lyapunov function. The proposed protocol overcomes the drawback of the semi-global consensus in existing literature. Furthermore, as an extension of the former result, a bipartite formation control problem is also solved. Finally, the proposed methods are validated by simulation examples.

Distributed convex optimization of higher order nonlinear uncertain multi-agent systems with switched parameters and topologies

This paper investigates the distributed optimization problem for a class of nonlinear uncertain multi-agent systems with unmeasured states, switched parameters, and directed communication topologies changing in the control process. To achieve the goal of optimizing the global objective function, a penalty function is constructed through making up of a sum of local objective functions and integrating consensus conditions of the multi-agent systems to utilize local and neighboring information. Radial basis function neural-networks and neural-networks state observer are applied to approximate the unknown nonlinear functions and obtain the unmeasured states, respectively. To avoid “explosion of complexity” and obtain derivatives for virtual control functions continuously, dynamic surface control technology is proposed to develop a distributed adaptive backstepping neural network control protocol to ensure that all the agents’ outputs asymptotically reach consensus to the optimal solution of the global objective function. Simulations demonstrate the effectiveness of the proposed control scheme.

Data-Driven Bipartite Formation for a Class of Nonlinear MIMO Multiagent Systems.

The bipartite formation control for the nonlinear discrete-time multiagent systems with signed digraph is considered in this article, in which the dynamics of the agents are completely unknown and multi-input multi-output (MIMO). First, the unknown nonlinear dynamic is converted into the compact-form dynamic linearization (CFDL) data model with a pseudo-Jacobian matrix (PJM). Based on the structurally balanced signed graph, a distance-based formation term is constructed and a bipartite formation model-free adaptive control (MFAC) protocol is designed. By employing the measured input and output data of the agents, the theoretical analysis is developed to prove the bounded-input bounded-output stability and the asymptotic convergence of the formation tracking error. Finally, the effectiveness of the proposed protocol is verified by two numerical examples.

An intelligent MAC protocol for mission critical applications in wireless sensor networks

SummaryIn the current age, wireless sensor networks (WSN) are growing the attention of researchers. WSNs are significantly used in a broad scope of real‐time monitoring applications. With ongoing advances and requirements in industrial emerging time‐critical applications, WSNs have been accordingly stretched out to help the reliable, time‐bound data delivery. In WSNs, node organization, resource limitations, topology varieties, providing delay guarantees for channel access, and transmission time barrier are the most significant challenges in real‐time handling traffic. Suppose critical data packets arrive from sensor nodes simultaneously. In that case, finding the optimal path for the transmission of data packets so that data are reached within time bounds, taking into account the current network scenario, is a more inspiring task. With this perspective, in order to provide a priority‐based transmission scheme, an improved adaptive media access control (MAC) protocol is proposed to support priority‐based channel access considering the current network scenario, which ensures time‐bounded reliable transfer of critical data packets. The proposed system uses an adaptive learning‐centered approach to find the optimum path for sending critical data packets in varying network scenarios. The proposed mission‐critical MAC (MC‐MAC) protocol is assessed arithmetically to offer reliable and time‐bounded transmission for emergency data packets.