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 research, a hybrid adaptive bionic fuzzy control strategy is developed for a class of complicated nonlinear multiple-input-multiple-output (MIMO) systems with dead-zone input. The first component of the bionic adaptive controller is a general phrase for tunning system parameters depending on the present state, and the second component is a trend-based compensation for adjusting the system parameters. This technique makes the system more intelligent and boosts its anti-interference capabilities. The stability and convergence are analyzed using the Lyapunov synthetic method, and thus the parameter restrictions of the MIMO system are provided. Finally, the strong anti-interference of the system is verified by the simulations. 

Huaicheng Yan

Papers

Hybrid adaptive bionic fuzzy control method for MIMO systems with dead-zone input