This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

Event-triggered consensus of multiagent systems (MASs) has attracted tremendous attention from both theoretical and practical perspectives due to the fact that it enables all agents eventually to reach an agreement upon a common quantity of interest while significantly alleviating utilization of communication and computation resources. This paper aims to provide an overview of recent advances in event-triggered consensus of MASs. First, a basic framework of multiagent event-triggered operational mechanisms is established. Second, representative results and methodologies reported in the literature are reviewed and some in-depth analysis is made on several event-triggered schemes, including event-based sampling schemes, model-based event-triggered schemes, sampled-data-based event-triggered schemes, and self-triggered sampling schemes. Third, two examples are outlined to show applicability of event-triggered consensus in power sharing of microgrids and formation control of multirobot systems, respectively. Finally, some challenging issues on event-triggered consensus are proposed for future research.

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An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems

This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked systems. Compared with some existing event-triggered and self-triggered schemes, a sampled-data-based event-triggered scheme can ensure a positive minimum inter-event time and make it possible to jointly design suitable feedback controllers and event-triggered threshold parameters. Thus, more attention has been paid to the sampled-data-based event-triggered scheme. A deep investigation is first made on the sampled-data-based event-triggered scheme. Then, recent results on sampled-data-based event-triggered state feedback control, dynamic output feedback control, $H_\infty$ filtering for networked systems are surveyed and analyzed. An overview on sampled-data-based event-triggered consensus for distributed multiagent systems is given. Finally, some challenging issues are addressed to direct the future research.

An Overview and Deep Investigation on Sampled-Data-Based Event-Triggered Control and Filtering for Networked Systems

This paper addresses the distributed formation control problem of a networked multi-agent system (MAS) subject to limited communication resources. First, a dynamic event-triggered communication mechanism (DECM) is developed to schedule inter-agent communication such that some unnecessary data exchanges among agents can be reduced so as to achieve better resource efficiency. Different from most of the existing event-triggered communication mechanisms, wherein threshold parameters are fixed all the time, the threshold parameter in the developed event triggering condition is dynamically adjustable in accordance with a dynamic rule. It is numerically shown that the proposed DECM can achieve a better tradeoff between reducing inter-agent communication frequency and preserving an expected formation than some existing ones. Second, an event-triggered formation protocol is delicately proposed by using only locally triggered sampled data in a distributed manner. Based on the formation protocol, it is shown that the state formation control problem is cast into an asymptotic stability problem of a reduced-order closed-loop system. Then, criteria for designing desired formation protocol and communication mechanism are derived. Finally, the effectiveness and advantages of the proposed approach are demonstrated through a comparative study in multirobot formation control.

Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism

In this paper, the consensus problem of linear discrete-time multi-agent systems is investigated. An event-triggered mechanism is introduced to rationally save the limited network resources, where the event-triggered condition of each agent only utilizes the information of itself and its neighbors. In the designed event-triggered mechanism, a novel dynamic threshold parameter adjusted with the system state fluctuations is constructed for screening the data more reasonably. With the help of Lyapunov stability theorem, the consensus conditions of the considered discrete-time multi-agent systems are obtained. To demonstrate the effectiveness and superiority of the proposed method, a numerical example is proposed.

Dynamic event-triggered consensus for discrete-time multi-agent systems

This article addresses the design of an event-triggered finite-time singularity-free terminal sliding-mode control algorithm for the tracking of Euler–Lagrange (EL) systems subject to state/error constraints, unstructured dynamics, and external disturbances. First, a novel sliding-mode manifold (SMM), not only devoted to the finite-time convergence of tracking errors to a small residual set around zero but also ensuring stringent constraint requirements, is proposed. The SMM is available for both the constrained and unconstrained EL systems in a unified manner with no structural changes. Then, a fuzzy logic system is introduced to dynamically compensate for uncertainties in the system. An extra robustifying term is added to the training policy to accelerate online learning. Also, an event-triggered mechanism is integrated into the tracker design procedure to reduce the frequency of signal transmission. Stability analysis proves that all the closed-loop signals are uniformly bounded, and numerical simulations further illustrate the theoretical findings.

Adaptive Fuzzy Event-Triggered Sliding-Mode Control for Uncertain Euler–Lagrange Systems With Performance Specifications

Finite-time-prescribed performance-based adaptive command filtering control for MIMO nonlinear systems with unknown hysteresis

This article investigates the dissipative stability and stabilization problems of Takagi–Sugeno fuzzy systems by employing sampled-data control. First, in order to enhance the adaptability of the controller, the internal and external influence factors, such as communication time delay and aperiodic sampling pattern, are taken into consideration in the design process. Then, some new terms are proposed to construct the looped-functional-like Lyapunov functional, which can improve the dissipative performance, enlarge the admissible upper bound of the aperiodic sampling periods, and reduce the occupation of control signals in the communication channel. Next, based on the free-matrix-based integral inequalities, some novel dissipative criteria are presented in terms of linear matrix inequalities. Finally, the superiority of the provided criteria is demonstrated through a truck–trailer system.

Huaicheng Yan

Papers

Dynamic event-triggered consensus for discrete-time multi-agent systems

Adaptive Fuzzy Event-Triggered Sliding-Mode Control for Uncertain Euler–Lagrange Systems With Performance Specifications

Finite-time-prescribed performance-based adaptive command filtering control for MIMO nonlinear systems with unknown hysteresis

Further Results on Dissipativity Analysis for T–S Fuzzy Systems Based on Sampled-Data Control

Fuzzy Finite-Time Sliding Mode Control of Euler-Lagrange Systems with State/Error Constraints