Adaptive Decentralized Output-Feedback Control Dealing With Static/Dynamic Interactions and Different-Unknown Subsystem Control Directions

Zhang, Zhirong; Song, Yongduan; Chen, Wen

doi:10.1109/tac.2020.3028563

Cited by 34 publications

(8 citation statements)

References 17 publications

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“…Remark 7 It can be seen that the introduction of actuator faults makes unknown control directions timevarying, which leads to the unavailability of the Nussbaum functions in [12,13]. By utilizing the Nussbaum functions in [15], this issue is well addressed.…”

Section: Pi Control Designmentioning

confidence: 99%

“…In fact, the control directions of agents may be unknown in practical engineering, which will bring the difficulty of handling the unknown interactions for multiple agents with unknown control directions [11]. More recently, some breakthroughs were made in this field by utilizing a new Nussbaum-type function [12,13], and the problem of multiple Nussbaum functions counteracting each other was addressed. For a class of highorder strict-feedback nonlinear MASs under directed graphs, the work of [14] innovatively solved the difficulty caused by the interconnection of multiple Nussbaumtype functions and achieved the distributed bounded consensus tracking.…”

Section: Introductionmentioning

confidence: 99%

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Distributed adaptive PI consensus tracking control for output-constrained nonlinear multiagent systems with unknown control directions

Zhu

Zhang

Hua

2023

Preprint

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This paper investigates the problem of distributed adaptive PI consensus tracking control for output-constrained nonlinear multiagent systems (MASs) with unknown control directions and unknown time-varying actuator faults under the directed graph. Firstly, an auxiliary filter network is constructed to estimate the output of the leader. Then, by introducing a nonlinear state transformation function, the asymmetric constraints on agents' outputs can be achieved with unconstrained initial conditions. Furthermore, based on the Nussbaum-type functions, a distributed adaptive PI controller is designed by utilizing the constructed generalized error for nonlinear MASs with unknown time-varying control directions caused by actuator faults. It is proved that the proposed control scheme can guarantee that all signals in the closed-loop system are bounded and the distributed asymptotic consensus tracking is achieved. Finally, a simulation example illustrates the effectiveness of the proposed control strategy.

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Section: Pi Control Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed adaptive PI consensus tracking control for output-constrained nonlinear multiagent systems with unknown control directions

Zhu

Zhang

Hua

2023

Preprint

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“…2) For the nonstrict-feedback system subject to unmeasured states and input saturation, the observer-based fixed-time controller is constructed without the bounded assumptions of control input and estimation error in [49][50][51]. Instead of the Nussbaum function [52][53][54][55], the nonstrict-feedback system is reconstructed to handle the unknown virtual and actual control gain functions with RBFNN.…”

Section: Introductionmentioning

confidence: 99%

Fixed-Time Tracking Control for State-Constrained Nonstrict-Feedback Systems Without Feasibility Conditions

Zhao

et al. 2023

Preprint

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This paper investigates the fixed-time tracking control schemes for a class of state-constrained nonstrict-feedback nonlinear systems without involving the feasibility conditions. Based on nonlinear mapping, a nonlinear state transformation function is constructed to convert the constrained system into an equivalent system without state constraints, which achieves the asymmetric time-varying state constraints and eliminates the feasibility conditions on the virtual controllers. A nonlinear fixed-time filter with dynamic surface control is utilized to handle the problem of explosion of complexity in the backstepping framework. Furthermore, we develop a fixed-time observer-based tracking control strategy for the nonstrict-feedback system subject to unmeasured states. To remove the restrictive assumptions of known control gain functions, the nonlinear system is reconstructed and the neural networks are employed to approximate the unknown terms. In addition, a hyperbolic tangent function is utilized to address the input saturation problem. Through the Lyapunov theorem, the closed-loop system is proven to be practical fixed-time stable within the constraint requirements. Finally, simulation results demonstrate the effectiveness of the proposed methods.

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“…A novel Nussbaum‐type function was first given in Reference 15 to deal with constant unknown control directions for a more general nonlinear system. Based on the lemma 3.1 in Reference 15, many results have been published in the filed of unknown control directions, such as References 16‐19. So far, although fruitful results have been established to handle the problem of unknown control directions, for the system with multiple unknown control directions, the Nussbaum‐type functions proposed above can only be applied to a single unknown control direction, which can not avoid the problem that multiple unknown terms cancelled each other in a single inequality.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered control for stochastic interconnected nonlinear systems with unknown control directions

Hua,

Wang,

Ning

2023

Intl J Robust & Nonlinear

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SummaryThis paper presents an event‐triggered control strategy for stochastic interconnected nonlinear systems with unknown control directions. Firstly, a new lemma is proposed for stochastic nonlinear systems with multiple time‐varying unknown control directions, which guarantees the boundedness of Nussbaum function parameter variables. Different from the existing results, each subsystem is allowed to have multiple time‐varying unknown control directions. Then, by using the backstepping method, a novel controller is proposed based on the relative threshold event‐triggered strategy. The controller not only reduces the communication burden but also eliminates the interference of unknown control directions. Based on Lyapunov stability theory, it is proved that the controller can make all signals in the closed‐loop system be bounded in probability and the system state variables converge to zero in probability. Finally, two simulation examples are presented to certify the effectiveness of the proposed control algorithm.

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Adaptive Decentralized Output-Feedback Control Dealing With Static/Dynamic Interactions and Different-Unknown Subsystem Control Directions

Cited by 34 publications

References 17 publications

Distributed adaptive PI consensus tracking control for output-constrained nonlinear multiagent systems with unknown control directions

Distributed adaptive PI consensus tracking control for output-constrained nonlinear multiagent systems with unknown control directions

Fixed-Time Tracking Control for State-Constrained Nonstrict-Feedback Systems Without Feasibility Conditions

Event‐triggered control for stochastic interconnected nonlinear systems with unknown control directions

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