Torque-Type Backlash Inverse Control for an Electromechanical Actuator With Active Disturbance Rejection

Article Engineering, Multidisciplinary

Robust adaptive precision motion control of tank horizontal stabilizer based on unknown actuator backlash compensation

Shu-Sen Yuan et al.

Summary: This paper presents a robust adaptive precision motion controller to effectively eliminate the adverse effect of backlash nonlinearity in the actuator of tank horizontal stabilizer and improve the system control performance.

DEFENCE TECHNOLOGY (2023)

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Article Automation & Control Systems

Adaptive neural network output feedback robust control of electromechanical servo system with backlash compensation and disturbance rejection

Yanchun Bai et al.

Summary: This paper focuses on the high-performance tracking control of electromechanical servo systems. A novel neural network state observer is designed to observe the unknown states. The proposed observer has higher observation accuracy and better robustness compared to existing neural network observers. Additionally, a fixed-weight single-node neural network is added to effectively improve the approximation ability of the double-layer neural network.

MECHATRONICS (2022)

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Article Engineering, Multidisciplinary

Accurate Angle Representation From Misplaced Hall-Effect Switch Sensors for Low-Cost Electric Vehicle Applications

Carlos Miguel-Espinar et al.

Summary: This article presents an accurate method to determine the mandatory rotor position of a permanent magnet synchronous machine, overcoming the issue of misplaced Hall-effect switch sensors. The method utilizes estimated speed, a compensation algorithm, and a Taylor series approximation to achieve accurate rotor position estimation, resulting in a more straightforward implementation and optimal balance performance.

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2022)

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Article Robotics

Model Learning With Backlash Compensation for a Tendon-Driven Surgical Robot

Francesco Cursi et al.

Summary: This research investigates how incorporating a backlash model and compensation can enhance model learning and control in highly articulated tendon-driven surgical robots. The experimental results demonstrate that the proposed backlash compensation effectively reduces nonlinearities in the system, improves model learning and control, and outperforms the traditional neural network in terms of path tracking accuracy.

IEEE ROBOTICS AND AUTOMATION LETTERS (2022)

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Proceedings Paper Automation & Control Systems

Monitoring based on Analytical Redundancy and Classification for a Primary Flight Surface Electromechanical Actuator

Benjamin Wauthion et al.

Summary: The study aims to develop a monitoring algorithm for early detection of degradation in electromechanical actuators, utilizing a simulator and residual generator. A multiclass Support Vector Machine classifier is used, with its validity confirmed by K-fold cross-validation.

IFAC PAPERSONLINE (2022)

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Article Computer Science, Artificial Intelligence

Robust Adaptive Path-Tracking Control of Autonomous Ground Vehicles With Considerations of Steering System Backlash

Xingyu Zhou et al.

Summary: This paper proposes a novel control architecture to tackle the backlash issue in ground vehicle path-tracking. The dynamics of the steering system's backlash are compensated using an adaptive inverse controller and robustified with sigma modification. Hardware experiments demonstrate the superiority of the proposed solution.

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES (2022)

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Article Automation & Control Systems