Mobile robot nonlinear feedback control based on Elman neural network observer

Abstract

This article presents a new approach to control a wheeled mobile robot without velocity measurement. The controller developed is based on kinematic model as well as dynamics model to take into account parameters of dynamics. These parameters related to dynamic equations are identified using a proposed methodology. Input-output feedback linearization is considered with a slight modification in the mathematical expressions to implement the dynamic controller and analyze the nonlinear internal behavior. The developed controllers require sensors to obtain the states needed for the closed-loop system. However, some states may not be available due to the absence of the sensors because of the cost, the weight limitation, reliability, induction of errors, failure, and so on. Particularly, for the velocity measurements, the required accuracy may not be achieved in practical applications due to the existence of significant errors induced by stochastic or cyclical noise. In this article, Elman neural network is proposed to work as an observer to estimate the velocity needed to complete the full state required for the closed-loop control and account for all the disturbances and model parameter uncertainties. Different simulations are carried out to demonstrate the feasibility of the approach in tracking different reference trajectories in comparison with other paradigms.

Trajectory Tracking and Stabilization of Nonholonomic Wheeled Mobile Robot Using Recursive Integral Backstepping Control

“…In the literature, various nonlinear control techniques have been suggested for posture stabilization that can be categorized into exact and dynamic feedback linearization [6,8], continuous time-varying feedback controller [9], and discontinuous feedback controller [10]. Similarly, for the trajectory tracking problem, various approaches have been presented, such as static and dynamic-based input-output feedback linearization [2,5,6,[11][12][13][14][15][16][17][18][19], backstepping control [20][21][22][23][24][25][26], and sliding mode control [27].…”

“…Because of the peculiar nature and structural obstruction of the nonholonomic system, input-output feedback linearization has proved to be an effective and successful technique to control mobile robots [11][12][13][14][15][16][17][18]. The basic idea of this approach is to apply coordinates transformation to transform the overall system into nonlinear internal and linear external dynamics [28].…”

“…To date, some of the research papers have analyzed the stability of internal dynamics. In [16][17][18], the authors examined the behavior of internal dynamics of type (2,0) WMR using the dynamic model. They showed that the internal dynamics of WMR is stable but not asymptotically stable during the stabilization of the position vector.…”

“…We have proposed a novel generalized nontriangular normal form by a suitable change of coordinates (diffeomorphism) transformation. During the formulation of generalized nontriangular normal form, the output vector is selected in such a way that the decoupling matrix would be nonsingular, even when the look-ahead distance (coordinates of virtual reference point in front of the mobile robot) or linear velocity is zero, as compared with previous work [5,6,8,[16][17][18][19]. The proposed internal dynamics of WMR is one dimension, where nonholonomic constraints of WMR has been sensibly exploited to reduce the complexity of nonlinear internal dynamics, with structural properties that provide ease to the design controller.…”

Hybrid position/virtual-force control for obstacle avoidance of wheeled robots using Elman neural network training technique

“…One method that can take into account the effects of time is the local recursive Elman NN (ENN) 19 which means to use internal memory. 20 It possesses the favorable ability to predict time series because of its neural nodes as well as recursive connections. In the last few years, scientific research worker has already done efforts in this area.…”