Remote control of an omnidirectional mobile robot with time-varying delay and noise attenuation

Santos, Jessivaldo; Conceição, André Gustavo Scolari; Santos, Tito L.M.; Araujo, H. X.

doi:10.1016/j.mechatronics.2018.04.003

Cited by 24 publications

(7 citation statements)

References 21 publications

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“…The nominal optimal control law using additional error integral feedback is first designed and the integral sliding mode control law is then performed. The control FIGURE 3 The overall architecture of the control system input u(t ) for the FWIDR system (8) will be designed as the combination of an optimal nominal control law u 0 (t ) and a switching control law u s (t ). Hence, the overall control law u(t ) can be expressed as…”

Section: Optimal Integral Sliding Mode Controlmentioning

confidence: 99%

“…Mobile robots have been gradually utilized in a growing number of applications in recent decades thanks to the noteworthy dexterity, manoeuvrability and active security [1][2][3]. Among existing mobile robots, four-wheel independent driven robot (FWIDR), which is equipped with four independent steering and driving motors, is capable of obtaining more effectively flexible actuation and fast torque responses.…”

Section: Introductionmentioning

confidence: 99%

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Recurrent neural network based optimal integral sliding mode tracking control for four‐wheel independently driven robots

Zhang

Huang

Rong

et al. 2021

IET Control Theory & Appl

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This paper investigates robust path tracking issue of the four-wheel independent driven robot (FWIDR) under time-varying system uncertainties and unavoidable external disturbances. A robust optimal integral sliding mode tracking control (OISMTC) scheme based on double feedback recurrent neural network (DFRNN) is proposed for the FWIDR system. Firstly, the presented OISMTC scheme modifies nominal optimal control part by exploiting an additional integral term to improve the tracking accuracy. Then, the designed DFRNN utilizes a double feedback loops structure to enhance the robustness against large system uncertainties by learning to approximate nonlinear systems. The adaptive law of the DFRNN is presented based on the Lyapunov theory to obtain favourable approximation performance in the presence of the time-varying operating conditions. Moreover, the asymptotic stability of the resultant FWIDR system is guaranteed by mathematical analysis. Finally, practical experiments are conducted to demonstrate the advantages of the proposed DFRNN-OISMTC method.

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Section: Optimal Integral Sliding Mode Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recurrent neural network based optimal integral sliding mode tracking control for four‐wheel independently driven robots

Zhang

Huang

Rong

et al. 2021

IET Control Theory & Appl

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“…Theorem 1. The predictor described by Equations (11) and (12) ensures semi-global asymptotic regulation of e 1 and e 2 in the sense that e 1 → 0 and e 2 → 0 as t → ∞, provided that the matrix K a are selected sufficiently large relative to the system initial conditions and the following conditions are simultaneously satisfied:…”

Section: Prediction Error Analysismentioning

confidence: 99%

“…Due to remote communication between robot sensors and control platforms, time delays are inevitable in measurement channels of a robotic system [10][11][12]. As such, real-time information of robot manipulator cannot arrive at the cloud platform on time, which may break down the operational capability or even destabilize the robotic system [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Predictor-Based Motion Tracking Control for Cloud Robotic Systems with Delayed Measurements

Shen

Song

2019

Electronics

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This paper addresses the problem of motion prediction and tracking control for cloud robotic systems with time-varying delays in measurements. A novel method using an observer-based structure for position and velocity prediction is developed to estimate the real-time information of robot manipulator. The prediction error can converge to zero even if model uncertainties exist in the robot manipulator. Based on the predicted positions and velocities, some sufficient conditions are derived to design suitable tracking controllers such that semi-globally uniformly ultimately bounded tracking performance of the predictor–controller couple can be guaranteed. Finally, the effectiveness and robustness to model uncertainties of the proposed method are verified by a two degree-of-freedom (DOF) robot system.

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“…O problema do controle em cascata de sistemas com atrasó e um tema relevante uma vez que este tipo de estratégiá e usualmente empregada em processos industriais e ná area de robótica móvel (Garcia et al, 2010;Santos et al, 2018a). A título de exemplo, robôs móveis costumam apresentar um controlador local para regular a velocidade das rodas e um controlador externo para controlar uma trajetória.…”

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Crit´erio de estabilidade simplificado para sistemas lineares em cascata com atraso vari´avel: uma abordagem via preditor de Smith Filtrado

Franklin

Santos

Araújo

2020

Anais Do Congresso Brasileiro De Automática 2020

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Este artigo trata do controle em cascata de sistemas lineares com atraso vari´avel. Esta abordagem ´e baseada na compensa¸c˜ao de atraso por meio do preditor de Smith filtrado (PSF) para mitigar uma parcela constante deste atraso e a parcela vari´avel ´e tratada pelo crit´erio de estabilidade simplificado baseado no teorema do ganho pequeno. O filtro de robustez presente no PSF ´e usado para recuperar a estabilidade afetada pela presen¸ca de incertezas de modelo epelo atraso vari´avel. Assume-se que a malha interna ´e regulada por um controlador Proporcional Integral Derivativo (PID) local, ao passo que o controle da malha externa ´e realizado via rede de comunica¸c˜ao. Um estudo de caso ´e utilizado para ilustrar os benef´ıcios da estrat´egia proposta.

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Remote control of an omnidirectional mobile robot with time-varying delay and noise attenuation

Cited by 24 publications

References 21 publications

Recurrent neural network based optimal integral sliding mode tracking control for four‐wheel independently driven robots

Recurrent neural network based optimal integral sliding mode tracking control for four‐wheel independently driven robots

Predictor-Based Motion Tracking Control for Cloud Robotic Systems with Delayed Measurements

Crit´erio de estabilidade simplificado para sistemas lineares em cascata com atraso vari´avel: uma abordagem via preditor de Smith Filtrado

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