Event-triggered containment control for second-order multi-agent systems with sampled position data

Containment control for fractional-order networked system with intermittent sampled position communication

This paper investigates containment control for fractional-order networked systems. Two novel intermittent sampled position communication protocols, where controllers only need to keep working during communication width of every sampling period under the past sampled position communication of neighbors' agents. Then, some necessary and sufficient conditions are derived to guarantee containment about the differential order, sampling period, communication width, coupling strengths, and networked structure. Taking into account of the delay, a detailed discussion to guarantee containment is given with respect to the delay, sampling period, and communication width. Interestingly, it is discovered that containment control cannot be guaranteed without delay or past sampled position communication under the proposed protocols. Finally, the effectiveness of theoretical results is demonstrated by some numerical simulations.

Containment control with delays, velocity constraints and position constraints in directed changing networks

This paper discusses a containment problem of multi-agent networks with inconsistently bounded communication time delays in directed changing topologies, where the velocity and position of each follower are, respectively, confined in a nonconvex set and a convex set during its movement. A projection-based distributed control protocol is developed to drive all followers into a target convex area spanned by some given leaders, and a sufficient condition for achieving the constrained containment is established. It is proven that the constrained containment problem can be solved by the developed control protocol only if every follower can communicate with no less than one stationary leader directly or indirectly in the union of the communication topologies. Eventually, a representative simulation experiment is performed to verify the main results.

Event-triggered H∞ filter design for sampled-data systems with quantization

This study verifies the H_∞ filter design for sampled-data systems with quantization and event-triggered schemes. Firstly, an event-triggered mechanism is presented to detect the release of the necessary sampled-data packet, which significantly reduces the limited network resources compared with the conventional time-triggered mechanism. Secondly, by considering the impact of quantization on the sampled-data system and using the time interval analysis approach, a new sampled-data filtering error model is presented. Then, the Lyapunov-Krasovskii functional (LKF) approach is utilized to derive the required conditions to ensure the asymptotical stability and attain the prescribed H_∞ performance for the mentioned system by solving a group of linear matrix inequality (LMIs). Consequently, the corresponding event-triggered and H_∞ parameters are co-designed. Finally, the efficiency and the advantage of the presented approach are demonstrated via a mass-spring system example.

Distributed bipartite leader-following consensus of linear multi-agent systems with input time delay based on event-triggered transmission mechanism

This study focuses on the distributed bipartite consensus tracking for linear multi-agent systems with input time delay based upon event-triggered transmission mechanism. Both cooperative interaction and antagonistic interaction between neighbor agents are considered. A novel distributed bipartite control technique with event-triggered mechanism is raised to address this consensus issue. Different from the existing methods, our control technique does not need continuous communication among agents, is capable of addressing the case of input delay, and is applicable for the signed communication topology. Moreover, to avoid continuous monitoring of one's own state, a self-triggered control strategy is further proposed. And when the system states cannot be measured, the observer-based bipartite control technique with event-triggered mechanism is thus put forward. Furthermore, the results in leader-following consensus are extended to containment control. It is proven that the proposed controllers fulfill the exclusion of Zeno behavior in two consensus problems. Finally, simulation experiments are used to test the practicability of the theoretical analysis.

Fully distributed containment control for second-order multi-agent systems with communication delay

In this paper, fully distributed containment control problems of multi-agent systems with double-integrator dynamics are investigated under directed topologies. For the cases with and without communication delay, two new fully distributed control protocols are designed, which do not need any global information of the communication topology graph. Necessary and sufficient conditions are obtained to ensure the solvability of the considered containment control problems. Particularly, for the case with communication delay, the critical value of the maximum allowable time delay of containment control is found. Finally, numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

H∞ consensus of Markovian jump multi-agent systems under multi-channel transmission via output feedback control strategy

This paper studies the H_∞ consensus problem of discrete-time multi-agent systems with Markovian jump parameters and exogenous disturbances via static output feedback control strategy. Each agent's measurement information is transmitted to its neighbors through the multiple quantized channels in which each channel obtains transmission permission based on a Markovian jump dispatcher. A static output feedback consensus controller is employed. In terms of an appropriate Lyapunov function, some sufficient conditions are derived to assure stochastic consensus for multi-agent systems subject to a specified H_∞ performance. At length, a simulation example is provided to illustrate the correctness of the result.

Predictive cloud control for multiagent systems with stochastic event-triggered schedule

This paper addresses a predictive cloud control problem for a linear multiagent system with random network delays and noises. To reduce communication cost, a stochastic event-triggered schedule is introduced to decide whether current measurements need to be transmitted. An optimal state estimation algorithm is designed to compensate random network delays in the feedback channel. Subsequently, a predictive cloud control scheme is proposed for the multiagent system to achieve both stability and consensus. Simultaneously, random network delays in the forward channel is compensated actively. Sufficient and necessary conditions of stability and consensus for the closed-loop multiagent system are derived. Finally, a numerical example is provided to verify correctness and effectiveness of the proposed methods.

Aperiodic adaptive control for neural-network-based nonzero-sum differential games: A novel event-triggering strategy

Owing to the adoption of aperiodic sampling pattern, the event-triggering control mode has been widely investigated in networked systems to save communication and reduce computation. Recently, there has been some preliminary findings to explore applications of this novel mode and to implement it in neural-network-based nonlinear systems by including an event generator. This motivates our investigation. For the first time, this paper designs triggering rules for neural-network-based nonzero-sum differential games characterized by nonlinear dynamics and quadratic cost functions. The main intention of the event-triggering strategy is to reduce communication between controllers and neural networks, thereby mitigating computational loads of controllers. An adaptive critic algorithm is subsequently applied to learn the required Nash equilibrium on line and meantime an alarm sampling period is proposed to ameliorate the learning accuracy. Furthermore, three simulation cases validate the approximate-optimal control performance and appraise virtues of the proposed event-triggering mode.

Event-Triggered Containment Control of Multi-Agent Systems With High-Order Dynamics and Input Delay

This paper studies the problem of distributed containment control for multi-agent systems with high-order dynamics and input delays. Two event-triggered control algorithms are proposed for multi-agent systems without and with input delay, respectively. The communication instants between two linked followers are determined by the event-triggering condition, and every follower can detect the event based on its own control input. For the followers, edge-based estimators are adopted to predict state differences to neighbors. Control inputs of the followers are calculated based on the predicted values of the state differences. To deal with the input delay, a delay comprehension approach is developed. It is proved that for arbitrarily large but bounded input delays, the followers can move into the convex hull spanned by the leaders asymptotically. Simulation results show the effectiveness of the proposed algorithms.