4 research outputs found
Adaptive guaranteed-performance consensus design for high-order multiagent systems
The current paper addresses the distributed guaranteed-performance consensus
design problems for general high-order linear multiagent systems with
leaderless and leader-follower structures, respectively. The information about
the Laplacian matrix of the interaction topology or its minimum nonzero
eigenvalue is usually required in existing works on the guaranteed-performance
consensus, which means that their conclusions are not completely distributed. A
new translation-adaptive strategy is proposed to realize the completely
distributed guaranteed-performance consensus control by using the structure
feature of a complete graph in the current paper. For the leaderless case, an
adaptive guaranteed-performance consensualization criterion is given in terms
of Riccati inequalities and a regulation approach of the consensus control gain
is presented by linear matrix inequalities. Extensions to the leader-follower
cases are further investigated. Especially, the guaranteed-performance costs
for leaderless and leader-follower cases are determined, respectively, which
are associated with the intrinsic structure characteristic of the interaction
topologies. Finally, two numerical examples are provided to demonstrate
theoretical results
Observer-based Adaptive Optimal Output Containment Control problem of Linear Heterogeneous Multi-agent Systems with Relative Output Measurements
This paper develops an optimal relative output-feedback based solution to the
containment control problem of linear heterogeneous multi-agent systems. A
distributed optimal control protocol is presented for the followers to not only
assure that their outputs fall into the convex hull of the leaders' output
(i.e., the desired or safe region), but also optimizes their transient
performance. The proposed optimal control solution is composed of a feedback
part, depending of the followers' state, and a feed-forward part, depending on
the convex hull of the leaders' state. To comply with most real-world
applications, the feedback and feed-forward states are assumed to be
unavailable and are estimated using two distributed observers. That is, since
the followers cannot directly sense their absolute states, a distributed
observer is designed that uses only relative output measurements with respect
to their neighbors (measured for example by using range sensors in robotic) and
the information which is broadcasted by their neighbors to estimate their
states. Moreover, another adaptive distributed observer is designed that uses
exchange of information between followers over a communication network to
estimate the convex hull of the leaders' state. The proposed observer relaxes
the restrictive requirement of knowing the complete knowledge of the leaders'
dynamics by all followers. An off-policy reinforcement learning algorithm on an
actor-critic structure is next developed to solve the optimal containment
control problem online, using relative output measurements and without
requirement of knowing the leaders' dynamics by all followers. Finally, the
theoretical results are verified by numerical simulations
Completely Distributed Guaranteed-performance Consensualization for High-order Multiagent Systems with Switching Topologies
The guaranteed-performance consensualization for high-order linear and
nonlinear multiagent systems with switching topologies is respectively realized
in a completely distributed manner in the sense that consensus design criteria
are independent of interaction topologies and switching motions. The current
paper firstly proposes an adaptive consensus protocol with
guaranteed-performance constraints and switching topologies, where interaction
weights among neighboring agents are adaptively adjusted and state errors among
all agents can be regulated. Then, a new translation-adaptive strategy is shown
to realize completely distributed guaranteed-performance consensus control and
an adaptive guaranteed-performance consensualization criterion is given on the
basis of the Riccati inequality. Furthermore, an approach to regulate the
consensus control gain and the guaranteed-performance cost is proposed in terms
of linear matrix inequalities. Moreover, main conclusions for linear multiagent
systems are extended to Lipschitz nonlinear cases. Finally, two numerical
examples are provided to demonstrate theoretical results
Fully-Heterogeneous Containment Control of a Network of Leader-Follower Systems
This paper develops a distributed solution to the fully-heterogeneous
containment control problem (CCP), for which not only the followers' dynamics
but also the leaders' dynamics are non-identical. A novel formulation of the
fully-heterogeneous CCP is first presented in which each follower constructs
its virtual exo-system. To build these virtual exo-systems by followers, a
novel distributed algorithm is developed to calculate the so-called normalized
level of influences (NLIs) of all leaders on each follower and a novel adaptive
distributed observer is designed to estimate the dynamics and states of all
leaders that have an influence on each follower. Then, a distributed control
protocol is proposed based on the cooperative output regulation framework,
utilizing this virtual exo-system. Based on estimations of leaders' dynamics
and states and NLIs of leaders on each follower, the solutions of the so-called
linear regulator equations are calculated in a distributed manner, and
consequently, a distributed control protocol is designed for solving the output
containment problem. Finally, theoretical results are verified by performing
numerical simulations