Nonlinear Predictive Motion Control for Autonomous Mobile Robots Considering Active Fault-Tolerant Control and
Peng Hang1, Baichuan Lou1, Chen Lv1
1School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Sensors (Basel, Switzerland)
|May 28, 2022
Summary
This study introduces an integrated chassis control framework for autonomous mobile robots (AMRs), enhancing stability and safety. The active fault-tolerant control (AFTC) system improves braking performance during failures and recovers braking energy.
Area of Science:
- Robotics
- Control Systems Engineering
- Automotive Engineering
Background:
- Autonomous mobile robots (AMRs) require advanced control for performance and safety.
- Existing control systems may lack robustness against actuator failures.
Purpose of the Study:
- To propose an integrated chassis control framework for AMRs.
- To enhance driving stability, braking safety, and energy recovery in AMRs.
Main Methods:
- Designed a velocity-tracking controller using integrated feedforward and feedback algorithms for longitudinal motion.
- Applied nonlinear model predictive control (NMPC) for four-wheel steering (4WS) path-tracking.
- Developed an active fault-tolerant control (AFTC) algorithm using weighted least squares (WLS) for torque reallocation.
Main Results:
- The proposed framework improves driving stability and braking safety under braking failure conditions.
- The AFTC system effectively reallocates torques from normal actuators.
- Braking energy is recaptured during deceleration events.
Conclusions:
- The integrated chassis control framework significantly enhances AMR performance and safety.
- AFTC is crucial for maintaining operational integrity during actuator failures.
- The system offers potential for energy efficiency improvements in AMRs.
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