Distributed controller–estimator for target tracking of networked robotic systems under sampled interaction

Abstract

This paper investigates the target tracking problem for networked robotic systems (NRSs) under sampled interaction. The target is assumed to be time-varying and described by a second-order oscillator. Two novel distributed controller-estimator algorithms (DCEA), which consist of both continuous and discontinuous signals, are presented. Based on the properties of small-value norms and Lyapunov stability theory, the conditions on the interaction topology, the sampling period, and the other control parameters are given such that the practical stability of the tracking error is achieved and the stability region is regulated quantitatively. The advantages of the presented DCEA are illustrated by comparisons with each other and the existing coordination algorithms. Simulation examples are given to demonstrate the theoretical results.

Distributed Consensus Filter for a Class of Continuous‐Time Nonlinear Stochastic Systems in Sensor Networks

“…By minimizing tr(Z) + tr(W), λ 1 and maximizing λ 2 under inequalities (20) and Assumptions 1 to 3, a suboptimal gain is obtained for the DCF with the dynamic equation (3) to decrease the estimation error.…”

“…Compared with the previous works , the contribution of this paper is at least fivefold. First, in contrast to the works of , which assume that the target has linear dynamics or target states are available, this paper considers that the target has nonlinear dynamics and its states are not available and a DCF is proposed to estimate the states of the target.…”

“…Compared with the previous works , the contribution of this paper is at least fivefold. First, in contrast to the works of , which assume that the target has linear dynamics or target states are available, this paper considers that the target has nonlinear dynamics and its states are not available and a DCF is proposed to estimate the states of the target. Second, a DCF is proposed in this paper that can be used for continuous nonlinear systems, whereas most of the previous results in are discrete and cannot be applied for state estimation in continuous‐time systems.…”

Attitude‐synchronization flocking of multiple 3‐dimensional nonholonomic agents without position measurement

“…The investigation of the flocking phenomenon is of particular interest to biologists, which helps them to understand and study group behaviors in biological systems, and it is also of particular importance to engineers, which allows them to design simple control algorithms for manmade systems. Besides, flocking is a general framework where one can consider target tracking of networked robotic systems, formation control of networked mobile robots, consensus of multiagent systems,() and so on.…”

Asynchronous Communication under Reliable and Unreliable Network Topologies in Distributed Multiagent Systems: A Robust Technique for Computing Average Consensus

“…Such coordination in multiagent system is referred to as a consensus, and it is considered as one the fundamental research activities in distributed control strategy. Study of multiagent systems attracted scientists and researchers from diverse fields of control theory, applied mathematical modelling, computer sciences, engineering, and so on to study the significance of distributed control of agents in a network, as distributed multiagents systems gain a lot of significance in various real time applications such as flocking [1][2][3][4], wireless sensor networks (WSN) [5,6], coordination control of robots [7,8], underwater vehicles, unmanned aerial vehicles [9,10], intelligent transportation systems [11], robotics [12], formation control [13,14], balancing of load in parallel computers [15], and intelligent decentralized mechanism for smart grids [16,17].…”