Jinwen Pan

Behrooz Shahsavari, Jinwen Pan, Roberto Horowitz

This paper proposes a novel direct adaptive control method for rejecting unknown deterministic disturbances and tracking unknown trajectories in systems with uncertain dynamics when the disturbances or trajectories are the summation of multiple sinusoids with known frequencies, such as periodic profiles or disturbances. The proposed algorithm does not require a model of the plant dynamics and does not use batches of measurements in the adaptation process. Moreover, it is applicable to both minimum and non-minimum phase plants. The algorithm is a "direct" adaptive method, in the sense that the identification of system parameters and the control design are performed simultaneously. In order to verify the effectiveness of the proposed method, an add-on controller is designed and implemented in the servo system of a hard disk drive to track unknown nano-scale periodic trajectories.

Jinwen Pan, Prateek Shah, Roberto Horowitz

A direct adaptive feedforward control method for tracking repeatable runout (RRO) in bit patterned media recording (BPMR) hard disk drives (HDD) is proposed. The technique estimates the system parameters and the residual RRO simultaneously and constructs a feedforward signal based on a known regressor. An improved version of the proposed algorithm to avoid matrix inversion and reduce computation complexity is given. Results for both MATLAB simulation and digital signal processor (DSP) implementation are provided to verify the effectiveness of the proposed algorithm.

Jinwen Pan, Yong Wang

The basic active disturbance rejection control (BADRC) algorithm with only one order higher extended state observer (ESO) proves to be robust to both internal and external disturbances. An advantage of BADRC is that in many applications it can achieve high disturbance attenuation level without requiring a detailed model of the plant or disturbance. However, this can be regarded as a disadvantage when the disturbance characteristic is known since the BADRC algorithm cannot exploit such information. This paper proposes an internal model based ADRC (IADRC) method, which can take advantage of knowing disturbance characteristic to achieve perfect estimation of the disturbance under some mild assumptions. The effectiveness of the proposed method is validated by comprehensive simulations and comparisons with the BADRC algorithm.