Adaptive internal model principle-based control for tremor suppression and sinusoidal signal tracking

Tremor is an involuntary rhythmic motion that can significantly affect a person’s ability to perform daily activities. Suppressing tremor without disturbing voluntary motion remains a major challenge in biomedical control. This dissertation presents an adaptive Internal Model Principle-based controller with a primary focus on tremor suppression and sinusoidal signal tracking. The proposed designs include fixed-parameter and adaptive control strategies based on proportional, Two-Degree-of-Freedom, and pole-placement structures. The Internal Model Principle is first integrated with the Field-Oriented Control of Brushless DC motors to cancel sinusoidal torque disturbances within a narrowband frequency range, forming the foundation for the experimental tremor-suppression setup. Controller parameters are tuned using the geometric average of each frequency band and verified through Bode plot analysis to ensure appropriate gain and phase margins. Simulation results show average power spectral density suppression of 88.1%, 81.3%, and 80.8% for the first, second, and third harmonics, respectively, while preserving voluntary motion by 85.3%. These results are experimentally validated on the bench-top motor setup. An adaptive Two-Degree-of-Freedom control algorithm is then developed to suppress tremor signals with unknown or time-varying frequencies. The controller parameters and internal model gains are updated online by matching the closed-loop transfer function to a low-pass filter with notch characteristics. This approach enables selective tremor cancellation while preserving voluntary motion. Following this, a real-time pole-placement method is introduced for multi-harmonic tremor suppression while ensuring system stability. In the resting tremor, the controller achieved 97.1%, 91.5%, and 88.9% suppression for the first three harmonics. In the action tremor, voluntary motion preservation reached 95.35%, and fundamental tremor suppression reached 89.68%. Experimental results using coupled Brushless DC motors confirm the real-time effectiveness of the proposed control approach. Finally, the adaptive Two-Degree-of-Freedom design is extended to track sinusoidal reference signals with unknown and time-varying frequencies, including multiple harmonics and DC bias. Simulation results confirm accurate tracking and stable frequency estimation in real time. Overall, this dissertation presents an adaptive and computationally efficient control approach for rejecting or tracking sinusoidal signals with unknown frequencies. The proposed methods are validated through MATLAB/Simulink simulations and experimental implementation using Brushless DC motors. Collectively, the work advances adaptive control strategies, contributing to the development and improved performance of real-time tremor suppression technologies.

Name thesis:degree_name

Ph D

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor dc:publisher

The University of Western Ontario

Year dc:date.issued

2026

Author dc:creator

• Allafi, Ibrahim

Advisor dc:contributor.advisor

• Brown, Lyndon J.

• Internal Model Principle
• Two-Degree-of-Freedom Control
• Adaptive Control
• Tremor Suppression
• Voluntary Motion Preservation
• Pole-Placement
• Multi-Harmonic Signals
• Real-Time Control

Statement dc:rights

• Attribution 4.0 International

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14721/39992

OAI identifier oai:identifier

oai:uwo.scholaris.ca:20.500.14721/39992