Abstract
In order to improve the tracking performance of gyro stabilized platform with disturbances and uncertainties, an adaptive nonlinear control based on neural networks and reduced-order disturbance observer for disturbance compensation is developed. First the reduced-order disturbance observer estimates the disturbance directly. The error of the estimated disturbance caused by parameter variation and measurement noise is then approximated by neural networks. The phase compensation is also introduced to the proposed control law for the desired sinusoidal tracking. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Experimental results show the validity of the proposed control approach.
Highlights
In order to obtain high resolution and definition imaging for many applications including surveillance, target tracking, and missile guidance, gyro stabilized platform (GSP) is used to stabilize and point the line-of-sight (LOS) of cameras, sensors, or other payload [1,2,3,4,5,6]
In [7], a reduced-order observer was designed according to linear control theory for an inertially stabilized line-of-sight control system
+ KgGg − ω load disturbances and equivalent disturbance caused by unmodeled dynamics, parameter variation, gyro and sensor noise, and gear reactions are considered a total disturbance, which is estimated by the reduced-order disturbance observer first
Summary
In order to obtain high resolution and definition imaging for many applications including surveillance, target tracking, and missile guidance, gyro stabilized platform (GSP) is used to stabilize and point the line-of-sight (LOS) of cameras, sensors, or other payload [1,2,3,4,5,6]. The disturbance observer based internal-loop compensator was introduced in [8] to estimate the disturbance of GSP. This method is dependent on the accurate system model. Parameters uncertainty, and sensor noise considered as the internal disturbance are estimated together with the external disturbance and are compensated to the control system as feed-forward control. Load disturbances and equivalent disturbance caused by unmodeled dynamics, parameter variation, gyro and sensor noise, and gear reactions are considered a total disturbance, which is estimated by the reduced-order disturbance observer first.
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