scholarly journals Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3673 ◽  
Author(s):  
Nur Ahmad
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Tracking Performance ◽  
Model Parameters ◽  
Control Law ◽  
System Modelling ◽  
Nonlinear Perturbations ◽  
Model Errors ◽  
Dc Motors

Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.

Exponential Stabilization of a Wheeled Mobile Robot Via Discontinuous Control

1999 ◽  
Vol 121 (1) ◽  
pp. 121-126 ◽  
Author(s):  
A. Astolfi
Keyword(s):  
Mobile Robot ◽  
State Feedback ◽  
Wheeled Mobile Robot ◽  
State Feedback Control ◽  
Exponential Stabilization ◽  
Control Law ◽  
Model Errors ◽  
Closed Loop System ◽  
Noisy Measurements ◽  
Time Invariant

In the present work the problem of exponential stabilization of the kinematic and dynamic model of a simple wheeled mobile robot is addressed and solved using a discontinuous, bounded, time invariant, state feedback control law. The properties of the closed-loop system are studied in detail and its performance in presence of model errors and noisy measurements are evaluated and discussed.

Adaptive fuzzy logic-based sliding mode control for a nonholonomic mobile robot in the presence of dynamic uncertainties

2014 ◽  
Vol 229 (11) ◽  
pp. 1979-1988 ◽  
Author(s):  
Ming Yue ◽  
Shuang Wang ◽  
Yongshun Zhang
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Sliding Mode ◽  
Tracking Error ◽  
Wheeled Mobile Robot ◽  
Robot Kinematics ◽  
Practical Implementation ◽  
Robot Dynamics ◽  
Model Errors ◽  
Uncertain Dynamics

This paper is concerned with the trajectory tracking control of wheeled mobile robot in the presence of nonholonomic constraint on the robot kinematics and unpredictable uncertainties related to robot dynamics. In this study, by analyzing the practical implementation of the wheeled mobile robot, the unavoidable model errors and external disturbances are merged into a synthesized term which is defined as uncertain dynamics. For attenuating the effects of static tracking error, a PI-type sliding mode manifold is proposed; particularly, in order to suppress inherent chattering, a fuzzy logic system is employed to estimate the uncertain dynamics due to its universal approximation capability. Also, adaptive schemes are applied which make the controllers much more adaptability to overcome the changing environment. Eventually, with the aid of a double closed-loop control structure, the coordinated control objectives of robot posture and uncertainties rejection are able to achieve simultaneously. Simulation studies verify the feasibility and effectiveness of the proposed control approaches.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

scholarly journals Adaptive Visually Servoed Tracking Control for Wheeled Mobile Robot with Uncertain Model Parameters in Complex Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fujie Wang ◽  
Yi Qin ◽  
Fang Guo ◽  
Bin Ren ◽  
John T. W. Yeow
Keyword(s):  
Mobile Robot ◽  
Visual Servoing ◽  
Dynamic Control ◽  
Kinematic Model ◽  
Image Plane ◽  
Adaptive Controller ◽  
Wheeled Mobile Robot ◽  
General Situation ◽  
Model Parameters ◽  
Complex Environment

This paper investigates the stabilization and trajectory tracking problem of wheeled mobile robot with a ceiling-mounted camera in complex environment. First, an adaptive visual servoing controller is proposed based on the uncalibrated kinematic model due to the complex operation environment. Then, an adaptive controller is derived to provide a solution of uncertain dynamic control for a wheeled mobile robot subject to parametric uncertainties. Furthermore, the proposed controllers can be applied to a more general situation where the parallelism requirement between the image plane and operation plane is no more needed. The overparameterization of regressor matrices is avoided by exploring the structure of the camera-robot system, and thus, the computational complexity of the controller can be simplified. The Lyapunov method is employed to testify the stability of a closed-loop system. Finally, simulation results are presented to demonstrate the performance of the suggested control.

Modeling and Control of Wheeled Mobile Robot With Four Mecanum Wheels

2021 ◽  
Vol 39 (5A) ◽  
pp. 779-789
Author(s):  
Sameh F. Hasana ◽  
Hassan. M. Alwan
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Mobile Robot ◽  
Dynamic Models ◽  
Particle Swarm ◽  
Wheeled Mobile Robot ◽  
Swarm Optimization ◽  
Modeling And Control

This work presents a driving control for the trajectory tracking of four mecanum wheeled mobile robot (FMWMR). The control consists of Backstepping-Type 1 Fuzzy Logic-Particle swarm optimization i.e.,(BSC-T1FLC-PSO). The kinematic and dynamic models have been derived. Backstepping controller (BSC) is used for finding controlled torques that generated from robot motors while Type-1 fuzzy logic control (T1FLC) as well as particle swarm optimization (PSO) used for finding the appropriate values of gain parameters of BSC. Square trajectory has been selected to test the performance of the control system of FMWMR. MATLAB/ Simulink is used to simulate the results. It has been concluded from the results that obtained from this control system there is a good matching between the simulated and the desired trajectories.

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