Hardware-in-the-loop implementation of an unknown input observer for synchronous reluctance motor

Area of Science:

• Electrical Engineering
• Control Systems
• Fuzzy Logic

Background:

• Nonlinear synchronous reluctance motors require accurate state and unknown input estimation for optimal control.
• Existing observer designs may not adequately address the complexities of nonlinear motor dynamics.

Purpose of the Study:

• To design a proportional integral observer for nonlinear synchronous reluctance motors using a Takagi-Sugeno multi-model.
• To simultaneously estimate both states and unknown inputs within the motor system.

Main Methods:

• Mathematical modeling of the nonlinear synchronous reluctance motor.
• Transformation of the motor model into a Takagi-Sugeno fuzzy system.
• Design of a proportional integral observer based on the fuzzy system.
• Utilizing linear matrix inequalities and the second Lyapunov theorem for convergence analysis.

Main Results:

• The observer design guarantees bounded estimation error through established convergence conditions.
• Observer gains are successfully derived by solving a set of constraints.
• Hardware-in-the-loop implementation validates the observer's performance.

Conclusions:

• The proposed proportional integral observer effectively estimates states and unknown inputs in nonlinear synchronous reluctance motors.
• The Takagi-Sugeno fuzzy model approach provides a robust framework for observer design.
• The technique demonstrates significant performance and effectiveness in practical applications.