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Guiju Xu,Jiangshuai Huang,Xiaojie Su 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.1
In this paper, we propose a decentralized adaptive control scheme for a class of interconnected nonlinearsystems without a priori knowledge of subsystems’ control directions and unknown actuator failure. To addressthis problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifyingthe interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in asingle inequality. The effect of actuator failures is successfully compensated. Global stability of the closed-loopsystem and asymptotic stabilization of subsystems’ output are proved and a simulation example is given to illustratethe effectiveness of the proposed control scheme.
Adaptive Event-triggered Control of a Class of Series Elastic Actuator System
Tingting Gao,Jiangshuai Huang,Rui Ling,Yong Zhou 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.7
In this paper, the event-triggered adaptive control for a class of series elastic actuator systems is considered. To solve this problem, firstly we propose an adaptive control scheme with a novel one-step design framework such that both the controller expression and parameter estimator are much simpler than related existing recursive design approaches. Then a set of event-triggering conditions is designed which is updated for each triggering. The ISS assumption is not needed for control design. It is shown that the proposed control schemes guarantee that allthe closed-loop signals are semi-globally bounded and the stabilization error converges to the origin asymptotically. The Zeno behavior is avoided. Simulation results illustrate the effectiveness of our scheme.
Leitao Gao,Guangshe Zhao,Guoqi Li,Yuming Liu,Jiangshuai Huang,Changyun Wen 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.1
In this paper, we consider how to determine the minimum number of leaders with allocation and how toachieve consensus over directed networks consisting of time-varying nonlinear multi-agents. Firstly, the problemof finding minimum number of leaders is formulated as a minimum spanning forest problem, i.e., finding theminimum population of trees in the network. By introducing a toll station connecting with each agent, this problemis converted to a minimum spanning tree problem. In this way, the minimum number of leaders is determined andthese leaders are found locating at the roots of each tree in the obtained spanning forest. Secondly, we describe avirtual leader connected with the allocated leaders, which indicates that the number of edges connected the followeragents with the virtual leader is the least in an arbitrary directed network. This method is different from the existingconsensus problem of redundant leaders or edges that connect the follower with one leader in special networks. A distributed consensus protocol is revisited for achieving final global consensus of all agents. It is theoreticallyshown that such a protocol indeed ensures consensus. Simulation examples in real-life networks are also providedto show the effectiveness of the proposed methodology. Our works enable studying and extending application ofconsensus problems in various complex networks.