Adaptive sliding mode controller design for mobile robot fault tolerant control. introducing ARTEMIC.

Axenie, Cristian; Cernega, Daniela

doi:10.1109/raad.2010.5524575

Cited by 6 publications

(7 citation statements)

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“…The design of robust controllers allows to compensate for uncertainty (e.g., wheel slip); these include dynamic modeling [14], robust [19], data-driven [20], and adaptive control [21], as well as sliding control [15], [8], [22]. Typical controllers aim to recover the desired robot behaviour by either "suppressing" uncertainty (i.e., robust control), modelling it (i.e., adaptive control), or predicting it (i.e., resilient control).…”

Section: B Trajectory Tracking For Wheeled Mobile Robotsmentioning

confidence: 99%

“…In trajectory tracking mode, the real mobile robot must track a virtual mobile robot's trajectory under time constraints. The robotic setup was developed in [9] and [22]. The control objective is to compute the velocity of the robot such that its pose P r = [x r , y r , ϕ r ] ⊤ follows a reference trajectory of the virtual robot…”

Section: A Wheeled Mobile Robot Trajectory Trackingmentioning

confidence: 99%

“…Note that, based on the study of [8], the sign function sgn(•) in the control signals can be replaced in the practical implementation by the saturation function sat(•) with thresholds to reduce the chattering phenomenon. Now, we define the Lyapunov function candidate, introduced in [9] and [22],…”

Section: A: Desired Manifold Selectionmentioning

confidence: 99%

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Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

Axenie,

Saveriano

2023

IEEE Access

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Assistive care robots operate in cluttered, complex environments, akin to human residences, and need to face sensor and actuator faults during their operation without compromising safety. In these situations, the system must foresee and provide reactions that are beyond robust in addition to compensating for uncertainty and volatility in its functioning. We propose a new control design framework based on the principles of antifragility. In this work, we provide a formal concept of antifragile control and outline the design procedures for creating a mobile robot trajectory-tracking antifragile controller. An extended comparative evaluation against other controllers and a methodical investigation of the performance under parametrizable uncertainty and errors is also provided. Our findings demonstrate the effectiveness of antifragile closed-loop control in volatile and unanticipated circumstances.

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Section: B Trajectory Tracking For Wheeled Mobile Robotsmentioning

confidence: 99%

Section: A Wheeled Mobile Robot Trajectory Trackingmentioning

confidence: 99%

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Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

Axenie,

Saveriano

2023

IEEE Access

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“…There are many studies that focus on adaptive actuator failure compensation schemes such as the neural network control [10,11], sliding-mode control [12,13], and an adaptive actuator failure compensation scheme [14]. Within the robotic field, there are also several important literatures that are directly related to adaptive actuator failure compensation algorithms such as control of a precision pointing hexapod [15], adaptive coordinated controller scheme [16], and redundant manipulator system [17].…”

Section: Introductionmentioning

confidence: 99%

An adaptive actuator failure compensation scheme for a cooperative manipulator system

Rugthum

Tao

2014

Robotica

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SUMMARYThis paper develops a new adaptive actuator failure compensation algorithm for the control of a cooperative robotic system subject to uncertain actuator failures. The benchmark robotic system has two manipulators to balance a rigid platform, and the right-side manipulator contains one actuator and the left-side manipulator has two actuators (one of which may fail during system operation, but it is uncertain how much, when and which actuator may fail). The developed adaptive actuator failure compensation scheme, based on adaptive integration of three individual failure compensators and direct adaptation of controller parameters, is capable of ensuring desired closed-loop stability and asymptotic output tracking, despite the failure uncertainties. Such an adaptive actuator failure compensation method is extended to control of a general cooperative robotic system. Simulation results are shown to verify the desired adaptive failure compensation control performance.

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Section: Literature Reviewmentioning

confidence: 99%

An Adaptive Actuator Failure Compensation for a Cooperative Manipulator System

Rugthum

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Adaptive sliding mode controller design for mobile robot fault tolerant control. introducing ARTEMIC.

Cited by 6 publications

References 1 publication

Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

An adaptive actuator failure compensation scheme for a cooperative manipulator system

An Adaptive Actuator Failure Compensation for a Cooperative Manipulator System

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