Event-triggered and consensus-based attitude tracking alignment for discrete-time multiple spacecraft system exploiting interference

This paper presents a discrete-time attitude control strategy with equi-global practical stabilizability for aligning the attitude of multiple spacecraft to a predesigned configuration according to a time-variant reference.By utilizing the interference of the wireless channel,the communication scheme designed in this paper can save communication resources,amount of computation,and energy proportionally to the number of spacecraft.The exact discrete-time model and approximate discrete-time model of the consensus-based spacecraft tracking system are given.Then the framework for the design of an event-triggered control scheme for the exact discrete-time system via its approximate models is developed,which avoids the periodic actuation,and Zeno behavior is proved to be excluded.Furthermore,the control scheme can handle the presence of the unknown fading channel.Finally,simulation results are presented to demonstrate the effectiveness of the control strategy.

Distributed state estimation for linear timeinvariant dynamical systems:A review of theories and algorithms

Distributed state estimation is of paramount importance in many applications involving the large-scale complex systems over spatially deployed networked sensors.This paper provides an overview for analysis of distributed state estimation algorithms for linear time invariant systems.A number of previous works are reviewed and a clear classification of the main approaches in this field are presented,i.e.,Kalman-filter-type methods and Luenberger-observer-type methods.The design and the stability analysis of these methods are discussed.Moreover,a comprehensive comparison of the existing results is provided in terms of some standard metrics including the graph connectivity,system observability,optimality,time scale and so on.Finally,several important and challenging future research directions are discussed.

Dynamic event-triggered-based human-in-the-loop formation control for stochastic nonlinear MASs

The dynamic event-triggered(DET)formation control problem of a class of stochastic nonlinear multi-agent systems(MASs)with full state constraints is investigated in this article.Supposing that the human operator sends commands to the leader as control input signals,all followers keep formation through network topology communication.Under the command-filter-based backstepping technique,the radial basis function neural networks(RBF NNs)and the barrier Lyapunov function(BLF)are utilized to resolve the problems of unknown nonlinear terms and full state constraints,respectively.Furthermore,a DET control mechanism is proposed to reduce the occupation of communication bandwidth.The presented distributed formation control strategy guarantees that all signals of the MASs are semi-globally uniformly ultimately bounded(SGUUB)in probability.Finally,the feasibility of the theoretical research result is demonstrated by a simulation example.

Cooperative coalition for formation flight scheduling based on incomplete information

This study analyzes the cooperative coalition problem for formation scheduling based on incomplete information. A multi-agent cooperative coalition framework is developed to optimize the formation scheduling problem in a decentralized manner. The social class differentiation mech- anism and role-assuming mechanism are incorporated into the framework, which, in turn, ensures that the multi-agent system （MAS） evolves in the optimal direction. Moreover, a further differen- tiation pressure can be achieved to help MAS escape from local optima. A Bayesian coalition nego- tiation algorithm is constructed, within which the Harsanyi transformation is introduced to transform the coalition problem based on incomplete information to the Bayesian-equivalent coali- tion problem based on imperfect information. The simulation results suggest that the distribution of agents＇ expectations of other agents＇ unknown information approximates to the true distribution after a finite set of generations. The comparisons indicate that the MAS cooperative coalition algo- rithm produces a significantly better utility and possesses a more effective capability of escaping from local optima than the proposal-engaged marriage algorithm and the Simulated Annealing algorithm.