A Novel Framework of Cooperative Design: Bringing Active Fault Diagnosis Into Fault-Tolerant Control

Jia, Fanlin; Cao, Fangfei; Lyu, Guangran; He, Xiao

doi:10.1109/tcyb.2022.3176538

Cited by 33 publications

(4 citation statements)

References 32 publications

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“…Ranatunga [12] proposed an adaptive admittance control model to enhance the stability and compliance of the admittance controller. Nonetheless, strong nonlinearity, time variability, and random noise interference [13][14][15][16][17] in the human-robot collaborative control process make it challenging for robotic control to meet most clinical application requirements. To address this nonlinear and time-varying system, which is difficult to model mathematically, researchers have introduced fuzzy control theory [18][19][20][21] for further optimization of control methods.…”

Section: Introductionmentioning

confidence: 99%

Human-robot interaction for orthopedic surgical robots based on fuzzy variable admittance control

Chen,

Zhao

2024

Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024)

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Keeping the balance of flexibility and stability is difficult in orthopedic surgery when the doctor and the robot operate together. This paper gives a fuzzy theory-based variable admittance control method to solve this question. For the fuzzy controller, the robot's traction force and current velocity are inputs, the damping parameters are the output, calculation rules are the fuzzy rules through expert experience, the fuzzy controller can get different damping parameters according to the doctor's operating intention, different damping parameters represent different desired speed of the robot. The stability of the robot is characterized by the change of acceleration at the end of the arm during the dragging process, and the flexibility of the robot is characterized by the amount of traction force exerted by the doctor on the end of the arm. A 7-DOF robotic arm experimental platform was built, and the dragging experiment was carried out. The experimental results show that the stability of the fuzzy-based variable-admittance controller is improved by 54.5% over the fixed-admittance controller for the same flexibility. Under the optimal variation range of damping parameters, the fuzzy-based variable admittance-controlled robot has a maximum speed of 0.047 m/s, a maximum traction force of 9.43 N, and a maximum trajectory deviation of 1.74 mm during human-robot collaboration. These improvements effectively enhance the speed and precision of human-robot collaboration in orthopedic surgery.

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Section: Introductionmentioning

confidence: 99%

Human-robot interaction for orthopedic surgical robots based on fuzzy variable admittance control

Chen,

Zhao

2024

Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024)

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“…In order to improve the sensitivity of the detection stage, an active fault-detection algorithm was proposed by adding auxiliary input signals [ 27 ]. Since the active fault-detection algorithm can identify more complex and variable faults, it has been studied by some scholars [ 28 , 29 , 30 ]. However, the existing active detection algorithms are mainly for single-agent systems and few are for multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

Interval Type-II Fuzzy Fault-Tolerant Control for Constrained Uncertain 2-DOF Robotic Multi-Agent Systems with Active Fault Detection

Yan

Qin

et al. 2023

Sensors

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This study proposed a novel adaptive interval Type-II fuzzy fault-tolerant control for constrained uncertain 2-DOF robotic multi-agent systems with an active fault-detection algorithm. This control method can realize the predefined-accuracy stability of multi-agent systems under input saturation constraint, complex actuator failure and high-order uncertainties. Firstly, a novel active fault-detection algorithm based on pulse-wave function was proposed to detect the failure time of multi-agent systems. To the best of our knowledge, this was the first time that an active fault-detection strategy had been used in multi-agent systems. Then, a switching strategy based on active fault detection was presented to design the active fault-tolerant control algorithm of the multi-agent system. In the end, based on the interval type-II fuzzy approximated system, a novel adaptive fuzzy fault-tolerant controller was proposed for multi-agent systems to deal with system uncertainties and redundant control inputs. Compared with other relevant fault-detection and fault-tolerant control methods, the proposed method can achieve predefinition of stable accuracy with smoother control input. The theoretical result was verified by simulation.

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“…Up to now, there have been a variety of tracking control methods, such as robust control, [1][2][3][4][5] sliding control, [6][7][8] intelligence-based control, [9][10][11][12] and adaptive control. [13][14][15] Practical applications are usually nonlinear, which make controller design challenges. In recent years, adaptive tracking control, which has the advantage of coping with nonlinearity, disturbances, and parameter uncertainties of systems, has attracted more and more attention in academia and practice.…”

Section: Introductionmentioning

confidence: 99%

“…Tracking control of dynamic systems is a research hotspot in control theory. Up to now, there have been a variety of tracking control methods, such as robust control, 1‐5 sliding control, 6‐8 intelligence‐based control, 9‐12 and adaptive control 13‐15 . Practical applications are usually nonlinear, which make controller design challenges.…”

Section: Introductionmentioning

confidence: 99%

Adaptive predefined‐time tracking control for high‐order strict‐feedback nonlinear systems with unknown mismatched disturbances

Jia

Huang

2022

Adaptive Control & Signal

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Summary The problem of practical predefined‐time tracking control is con sidered for high‐order strict‐feedback nonlinear systems subject to unknown mismatched disturbances. The exact bound of the mismatched disturbances is unknown in this study. A novel adaptive predefined‐time tracking control strategy based on backstepping is proposed by applying a predefined time stability theory. Using the designed tracking controller, all signals are bounded, and a user‐defined bound on the tracking error is ensured in a predefined interval, independent of initial states. The estimation parameters associated with the upper bound of the disturbances are updated adaptively, making the system robust to the disturbances. Simulation studies are conducted to illustrate the performance of the proposed control strategy.

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A Novel Framework of Cooperative Design: Bringing Active Fault Diagnosis Into Fault-Tolerant Control

Cited by 33 publications

References 32 publications

Human-robot interaction for orthopedic surgical robots based on fuzzy variable admittance control

Human-robot interaction for orthopedic surgical robots based on fuzzy variable admittance control

Interval Type-II Fuzzy Fault-Tolerant Control for Constrained Uncertain 2-DOF Robotic Multi-Agent Systems with Active Fault Detection

Adaptive predefined‐time tracking control for high‐order strict‐feedback nonlinear systems with unknown mismatched disturbances

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