Robust cascade control of a deployable cable-driven robot

Khalilpour, S. A.; Khorrambakht, R.; Taghirad, Hamid D.; Cardou, Philippe

doi:10.1016/j.ymssp.2019.03.010

Cited by 36 publications

(16 citation statements)

References 17 publications

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“…The tracking errors and can be written as functions of : (15), (17) and (58), the robust control law described by Equation (18) and the adaptive update law described by Equation (19) or the controller design described by Equations (15), (17) and (58), the robust control law described by Equation (20) and the adaptive update law described by Equations (21) and (22), the closed-loop system Equation 10…”

Section: Lemma 1 Based On Theorem 3 the Low-level Subsystemmentioning

confidence: 99%

“…Khosravi et al [ 17 ] proposed a robust PID controller which requires information about the upper bound of modelling uncertainties. Other studies have designed robust adaptive controllers, assuming that the required knowledge about the bounds of uncertainties is unavailable [ 18 , 19 , 20 ]. Jabbari and Yoon [ 19 ] and Khalilpour et al [ 20 ] proposed a cascade control mechanism for both cable tension and end-effector position.…”

Section: Introductionmentioning

confidence: 99%

“…Other studies have designed robust adaptive controllers, assuming that the required knowledge about the bounds of uncertainties is unavailable [ 18 , 19 , 20 ]. Jabbari and Yoon [ 19 ] and Khalilpour et al [ 20 ] proposed a cascade control mechanism for both cable tension and end-effector position. However, the approach in [ 18 ] lacks trajectory-tracking control for cable tension and does not provide an adequately quantitative criterion to select the control gains.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust Adaptive Control of Fully Constrained Cable-Driven Serial Manipulator with Multi-Segment Cables Using Cable Tension Sensor Measurements

Lou

Lin

Quan

et al. 2021

Sensors

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The structure of the cable-driven serial manipulator (CDSM) is more complex than that of the cable-driven parallel manipulator (CDPM), resulting in higher model complexity and stronger structural and parametric uncertainties. These drawbacks challenge the stable trajectory-tracking control of a CDSM. To circumvent these drawbacks, this paper proposes a robust adaptive controller for an n-degree-of-freedom (DOF) CDSM actuated by m cables. First, two high-level controllers are designed to track the joint trajectory under two scenarios, namely known and unknown upper bounds of uncertainties. The controllers include an adaptive feedforward term based on inverse dynamics and a robust control term compensating for the uncertainties. Second, the independence of control gains from the upper bound of uncertainties and the inclusion of the joint viscous friction coefficient into the dynamic parameter vector are realised. Then, a low-level controller is designed for the task of tracking the cable tension trajectory. The system stability is analysed using the Lyapunov method. Finally, the validity and effectiveness of the proposed controllers are verified by experimenting with a three-DOF six-cable CDSM. In addition, a comparative experiment with the classical proportional–integral–derivative (PID) controller is carried out.

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Section: Lemma 1 Based On Theorem 3 the Low-level Subsystemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Adaptive Control of Fully Constrained Cable-Driven Serial Manipulator with Multi-Segment Cables Using Cable Tension Sensor Measurements

Lou

Lin

Quan

et al. 2021

Sensors

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“…The wire length is adjusted by a ball screw and slider. Therefore, the dynamic equation of the drive system is established based on the dynamic torque balance equation of AC servo motor, as shown in Equation (12).…”

Section: B Dynamic Modeling Of the Driving Systemmentioning

confidence: 99%

“…In the design of the outer loop controller, a sliding mode robust controller based on the direct method of Lyapunov is proposed, and an experiment is carried out on a deployable suspension cable-driven robot. The experimental results show the controller's effectiveness in the case of inherent uncertainty in the system [12]. Based on the established dynamic model of the cable drive unit, YUPENG ZOU et al proposed a master dynamic control strategy and proved that the designed control strategy improved the loading precision and dynamic performance of the force servo system through experimental research [13].…”

Section: Introductionmentioning

confidence: 95%

Sliding Mode Robust Control of a Wire-Driven Parallel Robot Based on HJI Theory and a Disturbance Observer

et al. 2020

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A sliding mode robust control law based on Hamilton-Jacobi Inequality (HJI) theory and a disturbance observer is proposed for a wire-driven parallel robot (WDPR) used in a wind-tunnel test. First, the wire-driven parallel robot is described, and its kinematics model established. Second, according to the uncertainty, external disturbance, and redundant drive of the system, the dynamic model of the end-effector and drive system, and the overall dynamic model of the system are established. Hamilton-Jacobi Inequality theory and the designed disturbance observer are applied to the designed sliding mode robust control law, and the anti-interference ability of the WDPR is verified. The stability of the closed-loop system is analyzed by Lyapunov's second method, and the results show that the closed-loop system tends to be asymptotically stable. Finally, taking the dynamic trajectory simulation of compound motion and six-degree-of-freedom motion as examples, the designed sliding mode robust control law is verified by simulation, and the contrastive simulation analysis shows that the disturbance observer can effectively reduce the switching gain, thus effectively reducing chattering and improving the control accuracy of the system. The simulation results show that the designed sliding mode robust control law can effectively suppress the influence of external disturbance on the control error. The control input and the length of the wire change in a certain range. They also prove that the pose error is small, and the control accuracy is high. All of the foundings lay a theoretical foundation and technical support for the practical application of the prototype in a wind-tunnel test.

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Disturbance observer‐based control for cable‐driven parallel robots with external disturbance using deep reinforcement learning

Lu,

Yao,

et al. 2024

Asian Journal of Control

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In cable‐driven parallel robots (CDPRs) practical applications, external disturbances inevitably influence the actuator performance, leading to low positioning accuracy of end‐effector (EE), and even system crashes. This paper addresses a disturbance observer‐based control scheme using deep reinforcement learning (RL) to suppress the effect of external disturbances. A controller via the non‐singular terminal sliding mode (NTSM) is proposed to enhance the system robustness. The estimation of the disturbance is investigated, and the deep RL is employed to enhance the model‐based disturbance observer, namely, the RLDO, and a corresponding controller via NTSM (RLDO‐NTSMC) is proposed. Simulations and experimental results validate that the RLDO effectively improves the estimation accuracy, and the RLDO‐NTSMC significantly increases the control accuracy of CDPRs. The root mean square errors of the EE's positioning errors controlled by the RLDO‐NTSMC decreased by over 93% compared with the classical augmented proportional–derivative (APD) controller.

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Robust cascade control of a deployable cable-driven robot

Cited by 36 publications

References 17 publications

Robust Adaptive Control of Fully Constrained Cable-Driven Serial Manipulator with Multi-Segment Cables Using Cable Tension Sensor Measurements

Robust Adaptive Control of Fully Constrained Cable-Driven Serial Manipulator with Multi-Segment Cables Using Cable Tension Sensor Measurements

Sliding Mode Robust Control of a Wire-Driven Parallel Robot Based on HJI Theory and a Disturbance Observer

Disturbance observer‐based control for cable‐driven parallel robots with external disturbance using deep reinforcement learning

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