Safety-Based Speed Control of a Wheelchair Using Robust Adaptive Model Predictive Control

Area of Science:

• Robotics and Control Systems
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Electric-powered wheelchairs are crucial for mobility-impaired individuals.
• Controller design for wheelchairs must ensure safety across diverse users and scenarios.
• Existing systems may struggle with external disturbances and parameter uncertainties.

Purpose of the Study:

• To propose a safety-oriented speed tracking control algorithm for electric wheelchairs.
• To address external disturbances and dynamic parameter uncertainties.
• To ensure safety-related constraint satisfaction during speed tracking.

Main Methods:

• Utilized a set-membership approach for online estimation of uncertain parameters.
• Implemented a model predictive control (MPC) scheme with real-time adaptation.
• Developed a controller to manage both admissible and inadmissible speed references.

Main Results:

• The proposed controller effectively tracks desired wheelchair speeds while adhering to safety constraints.
• Demonstrated the ability to navigate to the nearest admissible reference when the target is unsafe.
• High-fidelity speed tracking results validated the controller's efficiency in simulations.

Conclusions:

• The developed safety-oriented controller enhances electric wheelchair operation.
• Real-time adaptation and constraint satisfaction are key to safe autonomous mobility.
• This approach improves accessibility and user safety for electric wheelchair systems.