Robust formation maneuvers through sliding mode for multi-agent systems with uncertainties

Qian, Dianwei; Li, Chengdong; Lee, Suk-Gyu; Ma, Chao

doi:10.1109/jas.2017.7510787

Cited by 35 publications

(16 citation statements)

References 23 publications

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“…According to the nominal system in Equation (19), the super-twisting sliding mode control can be designed as…”

Section: Super-twisting Sliding Mode Control Designmentioning

confidence: 99%

“…As a synthetic tool, sliding mode control is an alternative for the formation problem of uncertain multirobot systems. So far, some sliding-mode-based formation methods have been presented, that is, first-order sliding mode control [18,19], integral sliding mode control [8], derivative and integral terminal sliding mode control [4], and terminal sliding mode control [20]. Sliding mode control's most attractive property is its invariance, which can guarantee that a sliding mode control system is completely robust despite the matched uncertainties and disturbances [21].…”

Section: Introductionmentioning

confidence: 99%

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Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

et al. 2019

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This paper addresses a second-order sliding mode control method for the formation problem of multirobot systems. The formation patterns are usually symmetrical. This sliding mode control is based on the super-twisting law. In many real-world applications, the robots suffer from a great diversity of uncertainties and disturbances that greatly challenge super-twisting sliding mode formation maneuvers. In particular, such a challenge has adverse effects on the formation performance when the uncertainties and disturbances have an unknown bound. This paper focuses on this issue and utilizes the technique of an extreme learning machine to meet this challenge. Within the leader–follower framework, this paper investigates the integration of the super-twisting sliding mode control method and the extreme learning machine. The output weights of this extreme learning machine are adaptively adjusted so that this integrated formation design has guaranteed closed-loop stability in the sense of Lyaponov. In the end, some simulations are implemented via a multirobot platform, illustrating the superiority and effectiveness of the integrated formation design in spite of uncertainties and disturbances.

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“…According to the nominal system in Equation (19), the super-twisting sliding mode control can be designed as…”

Section: Super-twisting Sliding Mode Control Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

et al. 2019

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“…In recent years, the formation control of multiagent systems is an actively studied topic, where the objective is to drive multiple agents to achieve predefined constraints on their states. The broad applications of formation control have been shown in unmanned aerial vehicles (UAVs), attitude synchronization control of satellites, and teaming of multirobotics . Formation control is a special form of cooperative control of multiagent systems.…”

Section: Introductionmentioning

confidence: 99%

“…The broad applications of formation control have been shown in unmanned aerial vehicles (UAVs), 4,5 attitude synchronization control of satellites, 6 and teaming of multirobotics. 7,8 Formation control is a special form of cooperative control of multiagent systems. In recent decades, some centralized or decentralized protocols have been introduced to make the multiagent systems converge to the predefined formation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fault‐tolerant time‐varying formation tracking for multiagent systems with multiple leaders

Wang

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, an adaptive fault‐tolerant time‐varying formation control problem for nonlinear multiagent systems with multiple leaders is studied against actuator faults and state‐dependent uncertainties. Simultaneously, the followers form a predefined formation while tracking reference signal determined by the convex combination of the multiple leaders. Based on the neighboring relative information, an adaptive fault‐tolerant formation time‐varying control protocol is constructed to compensate for the influences of actuator faults and model uncertainties. In addition, the updating laws can be adjusted online through the adaptive mechanism, and the proposed control protocol can guarantee that all the signals in the closed‐loop systems are bounded. Lyapunov‐like functions are addressed to prove the stability of multiagent systems. Finally, two examples are provided to demonstrate the effectiveness of the theoretical results.

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“…The study conducted on robustness focuses mainly on the linear time-invariant control systems [8], including stability [9,10], being free from static error [11], adaptive control [12][13][14][15] and so on. Qian et al [16,17] conducted a relevant study on a robust control method for formation manoeuvres of a multi-agent system and carried out an investigation on the problems related to formation control of multiple agents.…”

Section: Introductionmentioning

confidence: 99%

High-frequency feedback robust control for flocking of multi-agent system with unknown parameters

et al. 2019

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In this paper, a kind of high-frequency feedback robust control for flocking of a multi-agent system with unknown parameters is put forward in detail. Firstly, a high-frequency feedback robust control scheme is proposed for the flocking problem of a multi-agent system with unknown parameters. Secondly, through the employment of Lyapunov stability theory, it's proved that velocity error is gradually stabilized and collisions between agents are also avoided. In addition, the high-frequency feedback robust control for flocking of a multi-agent system with unknown parameters is further proved. Finally, it is verified with the help of numerical simulation.

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Robust formation maneuvers through sliding mode for multi-agent systems with uncertainties

Cited by 35 publications

References 23 publications

Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

Adaptive fault‐tolerant time‐varying formation tracking for multiagent systems with multiple leaders

High-frequency feedback robust control for flocking of multi-agent system with unknown parameters

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