Fuzzy Dynamic Modeling for Accurate Control of Uncertain Mechanical Systems

Abstract

Mechanical systems become more complex, achieving precise control becomes increasingly challenging due to uncertainty. This study presents a fuzzy dynamics-based strategy for precise control of uncertain mechanical systems and investigates the use of robust control theory to assess system performance and stability under constraints. Fuzzy theory enables uncertainties to be addressed, resulting in a more precise description of system behaviour. The study findings demonstrate that utilising the constraint invariant dynamics analysis method led to a decrease in control input amplitude, resulting in an average total input U reduction of approximately 60 volts and improving system stability. The constraint invariant dynamics analysis method led to an average reduction of 40 volts in u1 amplitude and an average position error of 1 mm under motor control. The experimentation undertaken on the permanent magnet synchronous motor angular trajectory exhibits that each test was successful in following the anticipated path. The average angular discrepancies between experiments A, B, C, and D were 0.5, 1, 0.3, and 0.8 degrees respectively. The experimental trajectories for A and B occasionally surpassed the upper limit, while C and D remained consistently within the upper and lower bounds. The implementation of the state-dependent control strategy resulted in a 10% reduction in standard deviation of current fluctuation on average, further enhancing the stability and efficiency of the motor system. The research results are expected to provide more stable and efficient control solutions for a wide range of industrial and engineering applications, thereby making a positive contribution to sustainable development and technological progress in society.

Keywords

• Control strategies
• uncertain mechanical systems
• CIDA method
• fuzzy dynamics
• HORC control