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A Distributed Adaptive Observer-Based Approach to Synchronization of Heterogeneous Nonmonotonic Nonlinear Systems for Formation Application

Bohui Wang

2024IEEE Transactions on Automatic Control14 citationsDOI

Abstract

In this paper, the challenging problem of distributed adaptive observer design for synchronization and formation control of heterogeneous nonlinear cyber-physical-vehicle systems is addressed. A scheme of the distributed adaptive observer is first investigated for the synchronization of heterogeneous nonlinear systems in which the leader's dynamics are unknown and the heterogeneous system dynamics are non-monotonic. Since the heterogeneous systems contain nonidentical nonlinear dynamics and the leader has unknown dynamics composed of an unknown input bound, the error dynamics of the equilibrium point for the heterogeneous non-monotonic nonlinear systems will be affected, which has not previously been recognized in the observer design of synchronization literature. To solve this problem, a distributed adaptive observer-based approach is first developed to provide the estimation and compensation of the error dynamics of the equilibrium point for heterogeneous non-monotonic nonlinear systems. The nonidentical nonlinear dynamics among subsystems and the unknown dynamics of the leader will be handled by the developed distributed estimation laws. Then, by constructing the appropriate error compensation controllers and scheduling the limited information interaction among neighbors, an integrated synchronization control strategy is further proposed by designing a novel class of error dynamic compensation laws to achieve perfect synchronization behaviors. Finally, the mentioned approach is applied to the formation tracking control of heterogeneous nonlinear cyber-physical-vehicle systems, and the effectiveness of our approach is illustrated by case studies.

Topics & Concepts

Control theory (sociology)Synchronization (alternating current)Nonlinear systemComputer scienceAdaptive controlObserver (physics)Multi-agent systemDistributed computingControl engineeringControl (management)Artificial intelligenceEngineeringPhysicsChannel (broadcasting)Quantum mechanicsComputer networkNonlinear Dynamics and Pattern FormationDistributed Control Multi-Agent SystemsNeural Networks Stability and Synchronization