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The estimation accuracy of the inertial navigation system integrated with the global positioning system (GPS) through multiple kinds of Kalman filters (KFs) has been widely considered. Since the classical KFs could not overcome environmental disturbances and noises, adaptive and robust structures are utilised in sensor fusion techniques. Here, different types of adaptive structures have been assumed. The fuzzy inference system benefits the adaption of the measurement covariance matrix, a scale factor employed to tune the process covariance matrix and the Chi-square algorithm to detect and bound the disturbances. The estimation accuracy and robustness of the adaptive fuzzy extended Kalman filter (AFEKF) are compared with the unscented Kalman filter (UKF) and extended Kalman filter (EKF) structure in various scenarios involving position, velocity, attitude, accelerometer and gyroscope bias estimation errors. Likewise, in order to evaluate the AFEKF approach practically, an embedded electronic board is designed involving an ARM microcontroller, an inertial measurement unit sensor, and a GPS receiver, which was installed on a land vehicle. The results demonstrated the superiority of the AFEKF over the UKF and EKF in the case of lower estimation error and higher robustness against disturbances and outliers.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

In this research, a novel extension of the passivity-based output feedback trajectory tracking controller is developed for internally damped Euler-Lagrange systems with input saturation. Compared with the previous output feedback controllers, this new design of a combined adaptive controller-observer system will reduce the risk of actuator saturation effectively via generalized saturation functions. Semi-global uniform ultimate boundedness stability of the tracking errors and state estimation errors is guaranteed by Lyapunov stability analysis. An application of the proposed saturated output feedback controller is the stabilization of a nonholonomic wheeled mobile robot with saturated actuators towards desired trajectories. Simulation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.