Output-Constrained Control of Nonaffine Multiagent Systems With Partially Unknown Control Directions

Fan, Bo; Yang, Qinmin; Jagannathan, S.; Sun, Youxian

doi:10.1109/tac.2019.2892391

Cited by 85 publications

(64 citation statements)

References 31 publications

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“…"> i.Assumption indicates that the control directions of the considered multiagent system are unknown and are allowed to be nonidentical. Such a condition is less stringent than the restrictions appeared in our previous work and the recent related work that the control directions of the agents should be unknown identical or nonidentical partially unknown. Furthermore, by choosing the Nussbaum function as

N false(ξ false) = \sin false(ξ false) e^{ξ^{2}}

and replacing Lemma by lemma 4.3 in the work of Chen, this assumption can also be relaxed to the cases of time‐varying control coefficients b i ( t ) as in the existing works …”

Section: Problem Statement and Preliminariesmentioning

confidence: 80%

“…Recently, by exploiting the symmetric positive semidefiniteness of the Laplacian matrices on undirected connected graphs and the state transformation technique, an adaptive consensus algorithm is presented for first‐order nonlinear multiagent systems with state constraints in the work of Meng et al Furthermore, the result has been generalized to higher‐order output‐constrained multiagents with unknown control directions under undirected graphs in the work of Fan et al With further development of directed graphs, by resorting to adaptive technique, our previous work has investigated the consensus problem of second‐order multiagents with unknown control directions and position constraints. However, the aforementioned consensus methods in the presence of output constraints have two restrictions. The first is to require that the control directions in a multiagent system are known or unknown but identical .…”

Section: Introductionmentioning

confidence: 99%

“…However, the aforementioned consensus methods in the presence of output constraints have two restrictions. The first is to require that the control directions in a multiagent system are known or unknown but identical . The second is that the communication topologies among the agents have to be undirected connected or directed strongly connected .…”

Section: Introductionmentioning

confidence: 99%

“…The first is to require that the control directions in a multiagent system are known or unknown but identical . The second is that the communication topologies among the agents have to be undirected connected or directed strongly connected . How to design consensus algorithms for output‐constrained multiagent systems with unknown nonidentical control directions under a general directed graph is a significant research topic and, to the best of our knowledge, has not been addressed yet.…”

Section: Introductionmentioning

confidence: 99%

“… iv.Contrary to the output‐constrained consensus works under undirected graphs, the proposed new distributed algorithm can handle the consensus problem as well as the output‐constrained problem under the directed communication condition. Besides, the assumptions of the control directions in a multiagent system being known or unknown identical are no longer imposed.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

Wang

Cai

2020

Intl J Robust & Nonlinear

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Summary This paper presents a novel distributed adaptive control algorithm for uncertain higher‐order nonlinear multiagent systems subject to output constraints and unknown control directions. Regarding the latter, a generic class of cases is considered, allowing completely unknown and even nonidentical control directions. Furthermore, the communication topology is only required to contain a fixed directed spanning tree. To guarantee the output constraints and address the asymmetric directed communication topology, a new reference output using the transformation strategy is introduced for each agent, benefiting from which the consensus problem of the multiagent system is recast as local tracking control problems of single agents. Then, the distributed control algorithm is recursively established based on the backstepping technique and the Nussbaum‐type function. By leveraging the unique properties of the Laplacian matrix on directed graphs and matrix theory, it is shown that, under the proposed distributed algorithm, uniform boundedness of all closed‐loop signals can be ensured, and asymptotic consensus is achieved without violation of the output constraints. Finally, simulation studies on the angle control of single‐link robots are given to verify the effectiveness of the proposed algorithm.

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N false(ξ false) = \sin false(ξ false) e^{ξ^{2}}

and replacing Lemma by lemma 4.3 in the work of Chen, this assumption can also be relaxed to the cases of time‐varying control coefficients b i ( t ) as in the existing works …”

Section: Problem Statement and Preliminariesmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

Wang

Cai

2020

Intl J Robust & Nonlinear

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Adaptive finite‐time control for turbo‐generator of power systems with prescribed performance

Liang

Yang

Liu

2021

Asian Journal of Control

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Control of turbo-generator is facing great challenges resulting from more renewable energies injected into power systems, and it is still a challenging task to improve the accuracy and convergence speed when the operation point changes. In this paper, an adaptive finite-time controller design is proposed for turbo-generators in the presence of bounded disturbances and unknown system dynamics. Compared with existing methods, the finite-time stability rather than asymptotic stability or uniformly ultimately bounded (UUB) can be guaranteed and prescribed transient performance can be achieved. First, the constant constraints on the system states and terminal sliding mode (TSM) manifold are proposed to enhance the transient performance. Furthermore, the uncertainties of the system are overcome by the neural network (NN), and both the bounded external disturbances and the reconstruction error of NN are handled by an adaptive term and a robust term. In addition, the important chattering-free property could be achieved by the boundary layer. Finally, the finite-time stability of the output in the system is rigidly proved via Lyapunov analysis, and the effectiveness of the theoretical result is substantiated by extensive simulations.

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Adaptive consensus of second‐order nonlinear MASs with aperiodically time‐varying parameters and unknown control directions

Yi,

2023

Asian Journal of Control

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The problem of adaptive consensus is addressed for a class of second‐order nonlinear multi‐agent systems with aperiodically time‐varying parameters and unknown control directions. Firstly, a new adaptive control approach, so‐called congelation of variables method, is adopted to deal with aperiodically time‐varying parameters which are fast‐varying in an unknown compact set with only their radii known a priori. Secondly, a novel Nussbaum‐type function approach is utilized to address the problem of unknown control directions. It is noteworthy that the control directions investigated in this paper are allowed to be completely unknown and nonidentical, whereas the unknown control directions in the most existing works are assumed to be identical. Thirdly, the unknown nonlinear function in each follower's dynamics is approximated by radial basis function neural network approximation technique. The approximation error, external disturbance in the follower's dynamics, as well as the leader's unknown acceleration dynamics are suppressed as an adaptive robust term, which can alleviate the online computational burden. Then, by designing time‐varying control gains updated adaptively with only local information, a fully distributed adaptive consensus control scheme is designed to guarantee that the multi‐agent systems achieve consensus asymptotically in the presence of unknown aperiodically time‐varying parameters, unknown nonidentical control directions, unknown nonlinearities, and external disturbances. Two simulation examples are provided to validate the effectiveness of the proposed consensus protocol.

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Output-Constrained Control of Nonaffine Multiagent Systems With Partially Unknown Control Directions

Cited by 85 publications

References 31 publications

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

Consensus control of output‐constrained multiagent systems with unknown control directions under a directed graph

Adaptive finite‐time control for turbo‐generator of power systems with prescribed performance

Adaptive consensus of second‐order nonlinear MASs with aperiodically time‐varying parameters and unknown control directions

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