Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

A control strategy for real-time target tracking for wheeled mobile robots is presented.Using a modified Kalman filter for environment perception,a novel tracking control law derived from Lyapunov stability theory is introduced.Tuning of linear velocity and angular velocity with mechanical constraints is applied.The proposed control system can simultaneously solve the target trajectory prediction,real-time tracking,and posture regulation problems of a wheeled mobile robot.Experimental results illustrate the effectiveness of the proposed tracking control laws.

Kinematic Control of Wheeled Snake-Like Mobile Robot

From a bionics viewpoint , this paper proposes a mechanical model of a wheeled snake like mobile mechanism. On the hypothesis of the existing non holonomic constraints on the robot kinematics, we set up the relationship among the kinetic control parameters in the snake like movement using Lie group and Lie algebra of the principle fiber bundle and provide some theoretical control methods to realize the snake like locomotion.

Data-driven iterative learning trajectory tracking control for wheeled mobile robot under constraint of velocity saturation

Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic model.Second,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative domain.Based on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop controller.The authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking process.Notably,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking performance.The authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative domain.Finally,the authors used a simulation to demonstrate the effectiveness of the algorithm.

Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the desired.The fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy model.The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed.In addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics controller.The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is improved.Compared with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller.The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin.Additionally,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.

Robust model predictive tracking control for the wheeled mobile robot with boundary uncertain based on linear matrix inequalities

In this study,a robust model predictive controller is designed for the trajectory tracking problem of non-holonomic constrained wheeled mobile robot based on an elliptic invariant set approach.The controller is based on a time-varying error model of robot kinematics and uses linear matrix inequalities to solve the robust tracking problem taking uncertainties into account.The uncertainties are modelled by linear fractional transform form to contain both parameter perturbations and external disturbances.The control strategy consists of a feedforward term that drives the centre of the ellipse to the reference point and a feedback term that converges the uncertain system state error to the equilibrium point.The strategy stabilises the nominal system and ensures that all states of the uncertain system remain within the ellipsoid at each step,thus achieving robust stability of the uncertain system.Finally,the robustness of the algorithm and its resistance to disturbances are verified by simulation and experiment.

Analytical modeling and multi-objective optimization(MOO) of slippage for wheeled mobile robot(WMR) in rough terrain

Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots （AWMR） in rough terrain. A model and analysis of relationship among wheel slippage （S）, rotation angle （0）, sinkage （z） and wheel radius （r） are presented. It is found that wheel rotation angle, sinkage and radius have some influence on wheel slippage. A multi-objective optimization problem with slippage as utility function was formulated and solved in MATLAB. The results reveal the optimal values of wheel-terrain parameters required to achieve optimum slippage on dry sandy terrain. A method of slippage estimation for a five-wheeled mobile robot was presented through comparing the odometric measurements of the powered wheels with those of the fifth non-powered wheel. The experimental result shows that this method is feasible and can be used for online slippage estimation in a sandy terrain.

Robust simultaneous tracking and stabilization of wheeled mobile robots not satisfying nonholonomic constraint

A robust unified controller was proposed for wheeled mobile robots that do not satisfy the ideal rolling without slipping constraint.Practical trajectory tracking and posture stabilization were achieved in a unified framework.The design procedure was based on the transverse function method and Lyapunov redesign technique.The Lie group was also introduced in the design.The left-invariance property of the nominal model was firstly explored with respect to the standard group operation of the Lie group SE(2).Then,a bounded transverse function was constructed,by which a corresponding smooth embedded submanifold was defined.With the aid of the group operation,a smooth control law was designed,which fulfills practical tracking/stabilization of the nominal system.An additional component was finally constructed to robustify the nominal control law with respect to the slipping disturbance by using the Lyapunov redesign technique.The design procedure can be easily extended to the robot system suffered from general unknown but bounded disturbances.Simulations were provided to demonstrate the effectiveness of the robust unified controller.

Adaptive trajectory tracking control of two-wheeled self-balance robot

Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

Modeling and Adaptive Control of an Omni-Mecanum-Wheeled Robot

The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adaptive control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term is included in the control law, and the parameter update law with σ-modification is considered for the uncertainty estimation. Computer simulations are conducted to illustrate the suggested control approach.

Tracking Control of Wheeled Mobile Robots with Communication Delay and Data Loss

This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.

Research on point stabilization of a wheeled mobile robot using fuzzy control optimized by GA

A point stabilization scheme of a wheeled mobile robot （WMR） which moves on uneven surface is presented by using tuzzy control. Taking the kinematics and dynamics of the vehicle into account, the fuzzy controller is employed to regulate the robot based on a kinematic nonlinear state feedback control law. Herein, the fuzzy strategy is composed of two velocity control laws which are used to adjust the speed and angular velocity, respectively. Subsequently, genetic algorithm （GA） is applied to optimize the controller parameters. Through the self-optimization, a group of optimum parameters is gotten. Simulation results are presented to show the effectiveness of the control strategy.

Longitudinal and lateral slip control of autonomous wheeled mobile robot for trajectory tracking

This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.

CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots

A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.

Robust Finite-Time Trajectory Tracking Control of Wheeled Mobile Robots with Parametric Uncertainties and Disturbances

In this paper, a robust finite-time tracking control scheme is proposed for wheeled mobile robots with parametric uncertainties and disturbances. To eliminate the effect of lumped uncertainties,a nonlinear extended state observer(NESO) is employed to estimate the unknown states as well as uncertainties, and the corresponding coefficients are tuned via pole placement technique. Based on the observation values, the finite-time sliding mode controller is presented to guarantee that both the sliding mode variables and tracking errors converge to zero within finite time. Simulation results are given to demonstrate the effectiveness of the proposed control method.

Formation Control and Obstacle Avoidance for Multiple Mobile Robots

这篇论文为一组 nonholonomic 考虑形成控制和障碍回避的问题活动机器人。根据非最优的模型预兆的控制，二个控制算法被建议。当解决费用在工作的最佳的控制问题被结合，两个算法被提出以便他们解决每个交往的机器人的动力学。潜在的功能被用来定义终端状态惩罚术语，和一个相应终端声明区域被加到优化限制。而且，包括稳定性和安全的主要问题也被讨论。模拟结果显示出建议控制策略的可行性。

Adaptive Tracking Control of an Uncertain Nonholonomic Robot

In this paper, a new controller is proposed by using backstepping method for the trajectory tracking problem of nonholonomic dynamic mobile robots with nonholonomic constraints under the condition that there is a distance between the mass center and the geometrical center and the distance is unknown. And an adaptive feedback controller is also proposed for the case that some kinematic parameters and dynamic parameters are uncertain. The asymptotical stability of the control system is proved with Lyapunov stability theory. The simulation results show the effectiveness of the proposed controller. The comparison with the previous methods is made to show the effectiveness of the method in this article.

Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect

Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.