Optimal distributed time-varying formation control for second-order multiagent systems: LQR-based method.

The optimal leaderless and leader-following time-varying formation (TVF) control problems for second-order multiagent systems (MASs) are investigated, where two optimal TVF control protocols are proposed to achieve the desired formations as well as minimize the comprehensive optimization function that contain the cooperative performance index and the control energy index. For leaderless case, the optimal formation control problem is reformulated as an infinite-time state regulator problem by employing the state space decomposition method, which is subject to specified constraints on energy and performance indices, and the analytic criterion for optimal TVF achievability is subsequently proposed. Then, the results of optimal leaderless TVF control are extended to the leader-following case with switching topologies, where the main challenge is changed to find the optimal controller rather than the optimal gain matrix, and the optimal value of the comprehensive index is accurately determined. Finally, two simulation cases are proposed to validate the effectiveness of the theoretical results, and comparisons with previous works are presented to expound the optimality of the proposed formation control method.

Prescribed-time distributed optimization problem with constraints.

In recent years, distributed optimization problem have a wide range of applications in various fields. This paper considers the prescribed-time distributed optimization problem with/without constraints. Firstly, we assume the state of each agent is constrained, and the prescribed-time distributed optimization algorithm with constraints is designed on the basis of gradient projection algorithm and consensus algorithm. Secondly, the constrained distributed optimization problem is transformed into the unconstrained distributed optimization problem, and according to the gradient descent algorithm and consensus algorithm, we also propose the prescribed-time distributed optimization algorithm without constraints. By designing the appropriate objective functions, we prove the multi-agent system can converge to the optimal solution within any prescribed-time, and the convergence time is fully independent of the initial conditions and system parameters. Finally, three simulation examples are provided to verify the validity of the designed algorithms.

Induced attack with prescribed consensus trajectory against multiagent systems.

This paper proposes a new induced attack strategy against multiagent systems from the perspective of the attacker. It is noted that the induced attack can drive multiagent systems as a whole to follow a specific trajectory prescribed by the attacker, which cannot be achieved by denial-of-service attacks or deception attacks. Firstly, the induced attack signal is produced by establishing an attack generation exosystem, whose dynamics can be regulated to generate the prescribed consensus trajectory. Then, by the local state information and the induced attack signal among partial agents, a new induced attack protocol is proposed, which consists of the nominal consensus term and the induced attack term. By constructing the projection of the induced attack signal onto the consensus subspace, an explicit expression of the prescribed consensus trajectory is determined, which describes the movement trajectory of the entire multiagent system under the induced attack. Meanwhile, the induced attack design criterion is proposed to determine the dynamics matrix of the attack generation exosystem via the robust H∞ scheme. Finally, the simulation example is performed to illustrate the effectiveness of theoretical results.

Distributed formation for interconnected networks with minimum energy restriction and interaction silence.

The minimum-energy formation strategy for interconnected networks with distributed formation protocols is persented, where the impacts of the total energy restriction and the interaction silence are analyzed, respectively. The critical feature of this article is that the distributed formation and the minimum-energy restriction are realized simultaneously, and the total energy restriction is minimum in the sense of the linear matrix inequality. However, the guaranteed-cost formation strategy and the limited-budget formation strategy cannot guarantee that the energy restriction is minimum. Firstly, sufficient conditions for minimum-energy-restriction formation without the interaction silence are proposed, which can be solved by a specific optimization approach in terms of the linear matrix inequality, and the formation whole motion trajectory is determined, which is closely related to the average of the initial states of all agents and formation control vectors. Then, minimum-energy-restriction formation criteria for interconnected systems with the interaction silence are proposed by introducing two inhibition parameters and the interaction silence rate. Finally, two simulation examples are performed to illustrate the effectiveness of theoretical analyses.

Consensus Tracking for High-Order Uncertain Nonlinear MASs via Adaptive Backstepping Approach.

In this article, we focus on the problems of consensus control for nonlinear uncertain multiagent systems (MASs) with both unknown state delays and unknown external disturbances. First, a nonlinear function approximator is proposed for the system uncertainties deriving from unknown nonlinearity for each agent according to adaptive radial basis function neural networks (RBFNNs). By taking advantage of the Lyapunov-Krasovskii functionals (LKFs) approach, we develop a compensation control strategy to eliminate the effects of state delays. Considering the combination of adaptive RBFNNs, LKFs, and backstepping techniques, an adaptive output-feedback approach is raised to construct consensus tracking control protocols and adaptive laws. Then, the proposed consensus tracking scheme can steer the nonlinear MAS synchronizing to the predefined reference signal on account of the Lyapunov stability theory and inequality properties. Finally, simulation results are carried out to verify the validity of the presented theoretical approach.

Robust Packetized MPC for Networked Systems Subject to Packet Dropouts and Input Saturation With Quantized Feedback.

This article develops a robust packetized predictive control framework to deal with the quantized-feedback control problem of networked systems subject to Markovian packet dropouts and input saturation. In the proposed framework, the Markov chain model of packet dropout is established from the link of the controller to the actuator. To deal with the quantized measurements, a robust packetized predictive control method is presented with a quantized-feedback law. The problem of unreliable transmission is addressed by proposing a packet dropout compensation strategy with a forgetting factor. An augmented Markovian jump system model is established to take the packet dropouts into account. The synthesis of packetized predictive control is then developed by minimizing a worst case cost function with respect to the model uncertainties. The recursive feasibility of the proposed controller design problem and the mean-square stability of the closed-loop systems are proved, respectively. The proposed packetized predictive control method is demonstrated by simulating a four-tank process system.

Game-Based Consensus of Hybrid Multiagent Systems.

This article considers consensus of first-order/second-order hybrid multiagent systems (MASs) based on game modeling. In the first-order hybrid MAS (HMAS), a subset of agents select the Nash equilibrium of a multiplayer game as their states at each game time and the others update their states with first-order continuous-time (C-T) dynamics. By graph theory and matrix theory, we establish sufficient and necessary conditions for consensus of the first-order HMAS with two proposed protocols. The second-order HMAS is composed of agents whose states are determined by the Nash equilibrium of a multiplayer game and agents whose states are governed by second-order C-T dynamics. Similarly, sufficient and necessary conditions are given for consensus of the second-order HMAS with two proposed protocols. Several numerical simulations are provided to verify the effectiveness of our theoretical results.

Synchronous and asynchronous resilient impulsive control for group consensus of second-order multi-agent systems with communication delays.

This paper studies the resilient group consensus of continuous-time second-order multi-agent systems (MASs) with malicious agents. Adopting the idea that each normal agent ignores the most extreme values from neighbors, synchronous resilient impulsive algorithm based on sampled data is proposed for normal agents with bounded communication delays to achieve group consensus. Meanwhile, asynchronous resilient impulsive algorithm is also proposed for MASs where each agent has its own time clock. Sufficient topological conditions are obtained for solving resilient group consensus under synchronous and asynchronous settings, respectively. Numerical examples are provided to illustrate the effectiveness of the theoretical results.

Cooperative Output Regulation for Linear Multiagent Systems via Distributed Fixed-Time Event-Triggered Control.

In this article, we consider the cooperative output regulation for linear multiagent systems (MASs) via the distributed event-triggered strategy in fixed time. A novel fixed-time event-triggered control protocol is proposed using a dynamic compensator method. It is shown that based on the designed control scheme, the cooperative output regulation problem is addressed in fixed time and the agents in the communication network are subject to intermittent communication with their neighbors. Simultaneously, with the proposed event-triggering mechanism, Zeno behavior can be ruled out by choosing the appropriate parameters. Different from the existing strategies, both the compensator and control law are designed with intermittent communication in fixed time, where the convergence time is independent of any initial conditions. Moreover, for the case that the states are not available, the output regulation problem can further be addressed by the distributed observer-based output feedback controller with the fixed-time event-triggered compensator and event-triggered mechanism. Finally, a simulation example is provided to illustrate the effectiveness of the theoretical results.

Iterative Learning Control for Discrete-Time Systems With Full Learnability.

This article considers iterative learning control (ILC) for a class of discrete-time systems with full learnability and unknown system dynamics. First, we give a framework to analyze the learnability of the control system and build the relationship between the learnability of the control system and the input-output coupling matrix (IOCM). The control system has full learnability if and only if the IOCM is full-row rank and the control system has no learnability almost everywhere if and only if the rank of the IOCM is less than the dimension of system output. Second, by using the repetitiveness of the control system, some data-based learning schemes are developed. It is shown that we can obtain all the needed information on system dynamics through the developed learning schemes if the control system is controllable. Third, by the dynamic characteristics of system outputs of the ILC system along the iteration direction, we show how to use the available information of system dynamics to design the iterative learning gain matrix and the current state feedback gain matrix. And we strictly prove that the iterative learning scheme with the current state feedback mechanism can guarantee the monotone convergence of the ILC process if the IOCM is full-row rank. Finally, a numerical example is provided to validate the effectiveness of the proposed iterative learning scheme with the current state feedback mechanism.

H∞ Scaled Consensus for MASs With Mixed Time Delays and Disturbances via Observer-Based Output Feedback.

In this article, the H∞ scaled consensus control problem for multiagent systems in the presence of external disturbances and mixed time delays in both input and Lipschitz nonlinearity is investigated. First, a state observer is introduced for each agent based on the output information of the agent. Then, a scaled consensus protocol is proposed via a truncated predictor output-feedback method, which can deal with the input delay. The integral terms with the mixed time delays that are contained in the transformed systems are analyzed by using the Lyapunov-Krasovskii functionals method, and sufficient conditions are obtained to achieve scaled consensus with guaranteed H∞ performance. An iterative procedure is utilized to calculate the linear matrix inequality. By this, the feedback gain and observer gain are then designed. Finally, a simulation example is provided to illustrate the effectiveness of the theoretical results.

On Distributed Nash Equilibrium Computation: Hybrid Games and a Novel Consensus-Tracking Perspective.

With the incentive to solve Nash equilibrium computation problems for networked games, this article tries to find answers for the following two problems: 1) how to accommodate hybrid games, which contain both continuous-time players and discrete-time players? and 2) are there any other potential perspectives for solving continuous-time networked games except for the consensus-based gradient-like algorithm established in our previous works? With these two problems in mind, the study of this article leads to the following results: 1) a hybrid gradient search algorithm and a consensus-based hybrid gradient-like algorithm are proposed for hybrid games with their convergence results analytically investigated. In the proposed hybrid strategies, continuous-time players adopt continuous-time algorithms for action updating, while discrete-time players update their actions at each sampling time instant and 2) based on the idea of consensus tracking, the Nash equilibrium learning problem for continuous-time games is reformulated and two new computation strategies are subsequently established. Finally, the proposed strategies are numerically validated.

Consensus of Hybrid Multi-Agent Systems.

In this brief, we consider the consensus problem of hybrid multiagent systems. First, the hybrid multiagent system is proposed, which is composed of continuous-time and discrete-time dynamic agents. Then, three kinds of consensus protocols are presented for the hybrid multiagent system. The analysis tool developed in this brief is based on the matrix theory and graph theory. With different restrictions of the sampling period, some necessary and sufficient conditions are established for solving the consensus of the hybrid multiagent system. The consensus states are also obtained under different protocols. Finally, simulation examples are provided to demonstrate the effectiveness of our theoretical results.

Consensus of Multiagent Systems With Distance-Dependent Communication Networks.

In this paper, we study the consensus problem of discrete-time and continuous-time multiagent systems with distance-dependent communication networks, respectively. The communication weight between any two agents is assumed to be a nonincreasing function of their distance. First, we consider the networks with fixed connectivity. In this case, the interaction between adjacent agents always exists but the influence could possibly become negligible if the distance is long enough. We show that consensus can be reached under arbitrary initial states if the decay rate of the communication weight is less than a given bound. Second, we study the networks with distance-dependent connectivity. It is assumed that any two agents interact with each other if and only if their distance does not exceed a fixed range. With the validity of some conditions related to the property of the initial communication graph, we prove that consensus can be achieved asymptotically. Third, we present some applications of the main results to opinion consensus problems and formation control problems. Finally, several simulation examples are presented to illustrate the effectiveness of the theoretical findings.In this paper, we study the consensus problem of discrete-time and continuous-time multiagent systems with distance-dependent communication networks, respectively. The communication weight between any two agents is assumed to be a nonincreasing function of their distance. First, we consider the networks with fixed connectivity. In this case, the interaction between adjacent agents always exists but the influence could possibly become negligible if the distance is long enough. We show that consensus can be reached under arbitrary initial states if the decay rate of the communication weight is less than a given bound. Second, we study the networks with distance-dependent connectivity. It is assumed that any two agents interact with each other if and only if their distance does not exceed a fixed range. With the validity of some conditions related to the property of the initial communication graph, we prove that consensus can be achieved asymptotically. Third, we present some applications of the main results to opinion consensus problems and formation control problems. Finally, several simulation examples are presented to illustrate the effectiveness of the theoretical findings.