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, H ∞ control problems are investigated for a class of networked control systems. An improved networked control system model is proposed and the effects of random packet dropout, delay and sensor fault are considered simultaneously. The packet dropout process is modeled as a Markov chain, and the delays are bounded and occurred in a random way in this paper. The fault for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution. The resulting closed-loop system is transformed to a Markovian switching system. Sufficient conditions for stochastic stability of the closed-loop system are given in terms of linear matrix inequality. A mode-independent controller is designed such that the closed-loop system is stochastically stable and achieves the given H ∞ disturbance attenuation level. Finally, the simulation of the inverted pendulum control is given to illustrate the effectiveness of the proposed method.

H∞ control for networked control systems with limited information

Bipartite output regulation for singular heterogeneous multi-agent systems on signed graph

In this study, the optimal tracking performance for single-input multiple-output (SIMO) systems under control energy constraints is investigated. The packet dropouts in the upstream channel and down channel are adequately considered. The minimal tracking error is obtained by searching through all stablising controllers. The main results of this study show that the optimal tracking performance in these kinds of system is closely dependent on the structure of the given plant and statistic characteristics of the reference signal. Furthermore, the packet dropouts in the communication channel will degenerate the tracking performance. Finally, a typical example is given to illustrate the theoretical results.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cta.2017.1164

Optimal tracking performance for SIMO systems with packet dropouts and control energy constraints

This article investigates the resilient proportional-integral observer (PIO) problem for Markov switching memristive neural networks (MSMNNs) with randomly occurring sensor saturation within a finite-time interval. The Markov switching of memristive neural networks is regulated by a higher level deterministic switching signal, whose transition probabilities are piecewise time-varying and can be depicted by the average dwell-time strategy. Meanwhile, a Bernoulli stochastic process associated with an uncertain packet arriving rate is adopted to describe the randomly occurring sensor saturation. The aim is to design a resilient PIO such that the augmented dynamic has the property of stochastic finite-time boundedness while meeting the desired performance index. By applying the Lyapunov method and the average dwell-time scheme, sufficient criteria are established for MSMNNs, and a unified design method is presented for the existence of the PIO. Lastly, the attained theoretical results are validated via a numerical simulation.

Huaicheng Yan

Papers

H∞ control for networked control systems with limited information

Bipartite output regulation for singular heterogeneous multi-agent systems on signed graph

Optimal tracking performance for SIMO systems with packet dropouts and control energy constraints

Proportional-Integral Observer-Based State Estimation for Markov Memristive Neural Networks With Sensor Saturations.

Component-based dynamic event-triggered control for nonlinear singularly perturbed systems: A gain-scheduling method