An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

Active disturbance rejection control (ADRC) is applied to a one-axis gimbal mechanism. The dynamic model of the system is derived and validated from mathematical modeling and practical experiments. Disturbances acting on the complete model of the gimbal mechanism are introduced via base lateral acceleration and angular motion. The ADRC is designed by utilizing an extended state observer for observing and suppressing the effects of external disturbances and internal parameter uncertainties. A PID controller is used to form a basis of comparison for set-point tracking and disturbance rejection performance. The effects of identification errors and observer bandwidth are experimentally investigated. Based on simulation and experimental results, the effectiveness of ADRC in the presence of external disturbances and parameter uncertainties is illustrated.

Hardware Implementation of an ADRC Controller on a Gimbal Mechanism

To realize high-performance control for a two-axis inertially stabilized platform (ISP), a nonlinear dynamic model based on the geographic coordinate and a compound control method based on the back-stepping sliding mode control and adaptive radial basis function neural network (RBFNN) are proposed. Compared with the traditional dynamic model based on the inertial coordinate, the nonlinear dynamic model based on the geographic coordinate constructs the direct relationship among the control inputs and criteria of the ISP. Moreover, the back-stepping sliding mode control method is proposed to handle the system nonlinearity, parameter variations, and disturbances. Furthermore, the adaptive RBFNN is constructed and optimized to estimate the upper bound of the residual error on line to reduce the chatting phenomenon. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The effectiveness of the proposed method is validated by a series of simulations and flight tests.

A Dynamic Model and Control Method for a Two-Axis Inertially Stabilized Platform

This paper presents a dual-rate-loop control method based on disturbance observer (DOB) of angular acceleration for a three-axis ISP for aerial remote sensing applications, by which the control accuracy and stabilization of ISP are improved obviously. In stabilization loop of ISP, a dual-rate-loop strategy is designed through constituting inner rate loop and the outer rate loop, by which the capability of disturbance rejection is advanced. Further, a DOB-based on angular acceleration is proposed to attenuate the influences of the main disturbances on stabilization accuracy. Particularly, an information fusion method is suggested to obtain accurate angular acceleration in DOB design, which is the key for the disturbance compensation. The proposed methods are theoretically analyzed and experimentally validated to illustrate the effectiveness.

Dual-rate-loop control based on disturbance observer of angular acceleration for a three-axis aerial inertially stabilized platform

The use of an inertially stabilized platform (ISP) as a key component in electro-optical tracking instruments to control the sensor’s line of sight (LOS) has been investigated for over decades. Its aim is to achieve an accurate tracking for a target and isolate the LOS from the carrier vibrations. A typical assumption in such a system is that the mass distribution of the ISP is symmetrical with respect to the frame axes under consideration. This assumption is rarely satisfied in practice. This paper explores the development of an output feedback controller for an ISP while considering dynamic mass unbalance , where the controller derivation is based on the assumption that all parameters used in the system modeling are unknown , but bounded in size. This assumption implies that the ISP is affected by both matched and unmatched uncertainties. The research, in this paper, illustrates how an indirect robust control can be incorporated with a modified extended state observer-based feedforward term to achieve a high performance on the tracking in the presence of uncertainties, mass imbalance, kinematic coupling, carrier vibrations, and external disturbances. Simulation results are presented to confirm the effectiveness of the proposed scheme.

Rui Yin

Papers

An adaptive decoupling control for three-axis gyro stabilized platform based on neural networks