Abstract
A high-gain linear observer is proposed for online identification and reconstruction of a periodic disturbance. It is assumed that the frequency of the periodic disturbance is known, but its amplitude and phase are unknown. This is not a stringent assumption since such supposition can be easily characterized for disturbances like cogging torque, or bearing defects, both well-known problems in the control of electric machines. The observer design is based on the internal model principle in combination with a high-gain observer. Numerical results are included to validate the estimation of the periodic disturbance even when another disturbance of a different frequency is added. The estimated disturbance can be used to design a controller for reducing the disturbance effect. Alternatively, the estimated disturbance can be used for fault detection like in the case of gears and bearing faults, or simply to characterize the cogging torque of a particular machine.
Published Version
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