Abstract

A frequent problem in inertial stabilization control systems is the rejection of disturbances associated with moving components. Very often such disturbances are nonlinear and time varying. A prime example is the relative motion of components within a gimbal; in this case, nonlinear bearing friction induces a destabilizing torque from base motion to the component being stabilized. This paper presents a linear quadratic Gaussian algorithm, based on a simple first-order linear stochastic differential equation, for estimating and compensating in real time a particular class of disturbances that can be modeled as a plus or minus unknown slowly changing random value which is characterized by nonlinear Coulomb friction. Results of computer simulations testing the control algorithm are presented along with actual measurements from a laboratory brassboard system. The results reveal a noteworthy improvement in disturbance rejection as compared with a conventional PI controller with notch filters.

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