From Nonlinear to Fuzzy Approaches in Trajectory Tracking Control of Wheeled Mobile Robots

Abstract

In this paper, two knowledge based controllers are proposed to overcome the difficulties of a computed torque nonlinear controller (NC) in perfect trajectory tracking of nonholonomic wheeled mobile robots (WMRs). First, the effects of different dynamic models developed in angular and Cartesian coordinate systems are fully examined on the persistent excitation condition and consequently on the trajectory tracking performance of WMRs. Using the dynamic model coordinated in the Cartesian frame as the base of the NC results in perfect compensation of large position off-tracks and unbiased estimation of the plant's unknown parameters. However, using the WMR's dynamic model with rotation angles of driving wheels as the base of nonlinear and fuzzy controllers leads to accurate orientation tracking. Through replacing the proportional and differential terms of the NC by fuzzy functions, a fuzzy nonlinear controller (FNC) is generated. Due to the complicated dynamics of the WMR in which the center of mass does not coincide with the center of rotation, the expert knowledge of fuzzy controllers is extracted considering the rotation angles and rates of driving wheels as input variables. Fuzzy tuning of the NC results in a superior tracking performance against measurement noises, though the control torques are decreased and smoothed significantly. Second, a complete fuzzy controller (FC) is generated to make perfect tracking of the WMR's position and orientation. The local stability analysis of fuzzy controllers is examined considering the corresponding analytical structures as nonlinear controllers. The superior performances of the proposed fuzzy controllers compared to those of the NCs are evaluated through simulations. in Persian. His main research interests are: theory of computational intelligence, learning automata, adaptive filtering and their applications in control, power systems, image processing, pattern recognition, and communications, and other areas of interests are: theory of rough set and knowledge discovery.

Dynamic Based SMC of Nonholonomic Mobile Robots

“…According to the recent research works [5] and [8], considering the WMR kinematics, the holonomic and nonholonomic constraints are given as:…”

“…In a research work done by Sun, the kinematic model of a mobile robot has been transformed into a linear time invariant system by state and input transformation, then, the pole-assignment method has been applied to design the controller [4]. Keighobadi, Menhaj and Kabganian have designed a mixed feedback-linearization and fuzzy controller for perfect trajectory tracking control of the WMR [5], see also [6][7][8] for more robust and intelligent applications.…”

Adaptive fuzzy sliding mode controller for Wheeled Mobile Robots

“…Furthermore, the performance of FL controllers is limited due to persistent Manuscript excitation condition, parameter uncertainties, external disturbances, measurement noises, and other imperfections affecting a real system. Therefore, even if the FL controllers can be designed based on the mathematical model, the controller may be too complicated to be implemented with software [4].…”

“…This paper is dealing with perfect trajectory tracking of mobile robots in which the center of mass doesn't coincide with the center of rotation. So a more general kind of WMRs is considered to widen the industrial applications [4].…”

Biologically Inspired Control Of A Fleet Of Uavs With Threat Evasion Strategy

“…This is particularly because such models can usually have a structure with three states and only two inputs to control the system, hence, fail to satisfy Brockett's Condition [1,2]. Keighobadi et al in [8] discussed the problem of achieving complete tracking of a wheeled robot using a torque nonlinear controller. Discontinuous feedback control laws [4,5] and also continuous feedback laws [2,6,7] have been proposed.…”