Output-feedback formation control of wheeled mobile robots with actuators saturation compensation

Nonlinear Dynamics - This paper addresses output-feedback formation control of a group of wheeled mobile robots with saturating actuators. A virtual leader–follower strategy and a...     

Orientation-error observer-based tracking control of nonholonomic mobile robots

In this paper, a novel trajectory tracking controller is proposed for mobile robots with unknown orientation angle by employing the orientation-error observer (OEO). In order to overcome the local stability resulted from linearization design methods, an asymptotically stable controller is designed using Lyapunov’s direct method. This method breaks down nonlinear systems into low-dimensional systems and simplifies the controller design using virtual auxiliary error function and partial Lyapunov functions. A state-feedback controller for the nonlinear error dynamics of the mobile robot is combined with an observer that estimates the orientation-error based on available trajectory information and measurement of the position coordinates. The stability of the system is easily proved via the Lyapunov theory. Abundant simulation and experiment results validate the effectiveness and superiority of the proposed control method.     

A random-profile approach for trajectory planning of wheeled mobile robots

We present a random-profile approach to treat the optimal free-trajectory planning problem for nonholonomic wheeled mobile robots subjected to move in a constrained workspace. This versatile method is based on a simultaneous search for the robot path and for the time evolution on this path. It handles obstacle avoidance issues while considering kinodynamic constraints (bounded velocities, accelerations and torques). It may be applied to treat problems with various forms of optimization criteria involving travel time, efforts and power. Numerical results, obtained via the simulated-annealing technique of optimization, are presented for two- and three-wheel mobile robots and are compared to those available in the literature.     

Robust trajectory tracking control of cable-driven parallel robots

Nonlinear Dynamics - In this paper, a robust tracking controller is designed for fully constrained cable-driven parallel robots (CDPRs). One of the main challenges of controller design for this...     

Adaptive reactionless control strategy via the PSO-ELM algorithm for free-floating space robots during manipulation of unknown objects

Nonlinear Dynamics - The operation of free-floating space robots causes significant challenges to the attitude control of a spacecraft body, resulting from the strong dynamic coupling existing in...     

A low-complexity tracker design for uncertain nonholonomic wheeled mobile robots with time-varying input delay at nonlinear dynamic level

A low-complexity design problem of tracking scheme for uncertain nonholonomic mobile robots is investigated in the presence of unknown time-varying input delay. It is assumed that nonlinearities and parameters of robots and their bounds are unknown. Based on a nonlinear error transformation, a tracking control scheme ensuring preassigned bounds of overshoot, convergence rate, and steady-state values of a tracking error is firstly presented in the absence of input delay, without using any adaptive and function approximation mechanism to estimate unknown nonlinearities and model parameters and computing repeated time derivatives of certain signals. Then, we develop a low-complexity tracking scheme to deal with unknown time-varying input delay of mobile robots where some auxiliary signals and design conditions are derived for the design and stability analysis of the proposed tracking scheme. The boundedness of all signals in the closed-loop system and the guarantee of tracking performance with preassigned bounds are established through Lyapunov stability analysis. The validity of the proposed theoretical result is shown by a simulation example.     

Continuously asymptotic tracking of disturbed interconnected systems with unknown control directions

Nonlinear Dynamics - Recently, the fruitful results on robust control for large-scale interconnected systems have been reported, but most of them are contingent upon “known control...     

Studies of dynamics of a lightweight wheeled mobile robot during longitudinal motion on soft ground

The paper is concerned with the study of longitudinal motion of a lightweight wheeled mobile robot on soft ground. The study is focused on the influence of the desired longitudinal velocity of a robot on both the longitudinal slip of the wheels and the ratio of wheel-terrain contact angles. Design of the four-wheeled skid-steered robot and research environment are described. Experimental investigations were conducted on a dedicated test stand with dry sand. A dynamics model of the robot-ground system taking into account properties of soft ground is presented. The classical terramechanics models of Bekker and Janosi-Hanamoto are used. Results of simulation research of robot motion and of the analogous experimental investigations are presented. Actual motion parameters of the robot and the values of longitudinal slip ratio of the wheels are determined. The results of simulation and experimental investigations are compared and discussed. A formula to describe front-to-back wheel-terrain contact angle ratio dependency on the desired velocity is proposed.     

Adaptive robust control of Mecanum-wheeled mobile robot with uncertainties

This paper presents a novel implementation of an adaptive robust second-order sliding mode control (ARSSMC) on a mobile robot with four Mecanum wheels. Each wheel of the mobile robot is actuated by separate motors. It is the first time that higher-order sliding mode control method is implemented for the trajectory tracking control of Mecanum-wheeled mobile robot. Kinematic and dynamic modeling of the robot is done to derive an equation of motion in the presence of friction, external force disturbance, and uncertainties. In order to make the system robust, second-order sliding mode control law is derived. Further, adaptive laws are defined for adaptive estimation of switching gains. To check the tracking performance of the proposed controller, simulations are performed and comparisons of the obtained results are made with adaptive robust sliding mode control (ARSMC) and PID controller. In addition, a new and low-cost experimental approach is proposed to implement the proposed control law on a real robot. Experimental results prove that without compromising on the dynamics of the robot real-time implementation is possible in less computational time. The simulation and experimental results obtained confirms the superiority of ARSSMC over ARSMC and PID controller in terms of integral square error (ISE), integral absolute error (IAE), and integral time-weighted absolute error (ITAE), control energy and total variance (TV).     

Adaptive synchronization of chaotic systems with unknown parameters via new backstepping strategy

In this paper, a new effective approach??backstepping with Ge?CYao?CChen (GYC) partial region stability theory (called BGYC in this article) is proposed to applied to adaptive synchronization. Backstepping design is a recursive procedure that combines the choice of a Lyapunov function with the design of a controller, and it presents a systematic procedure for selecting a proper controller in chaos synchronization. We further combine the systematic backstepping design and GYC partial region stability theory in this article, Lyapunov function can be chosen as a simple linear homogeneous function of states, and the controllers and the update laws of parameters shall be much simpler. Further, it also introduces less simulation error??the numerical simulation results show that the states errors and parametric errors approach to zero much more exactly and efficiently, which are compared with the original one. Two cases are presented in the simulation results to show the effectiveness and feasibility of our new strategy.     

Fuzzy neural adaptive tracking control of unknown chaotic systems with input saturation

The contribution of this work is to study the control of unknown chaotic systems with input saturation, and the backstepping-based an adaptive fuzzy neural controller (AFNC) is proposed. In many practical dynamic systems, physical input saturation on hardware dictates that the magnitude of the control signal is always constrained. Saturation is a potential problem for actuators of control systems. It often severely limits system performance, giving rise to undesirable inaccuracy or leading instability. To deal with saturation, we construct a new system with the same order as that of the plant. With the error between the control input and saturation input as the input of the constructed system, a number of signals are generated to compensate the effect of saturation. Finally, simulation results show that the AFNC can achieve favorable tracking performances.     

Event-triggered adaptive neural tracking control of nonstrict-feedback nonlinear systems with unknown measurement

Nonlinear Dynamics - This paper studies the event-triggered control (ETC) of the nonstrict-feedback nonlinear system with unknown measurement and unknown model dynamics, where the output function...     

Adaptive finite-time event-triggered command filtered control for nonlinear systems with unknown control directions

Nonlinear Dynamics - In this article, we study an adaptive finite-time event-triggered command filtered control problem based on output feedback for a class of nonstrict-feedback nonlinear systems...     

Adaptive finite-time stabilization of uncertain non-autonomous chaotic electromechanical gyrostat systems with unknown parameters

This paper deals with the problem of robust finite-time stabilization of non-autonomous chaotic gyrostat systems. It is assumed that the parameters of the gyrostat system are completely unknown in advance and the system is perturbed by unknown uncertainties and disturbances. Some update laws are proposed to estimate the unknown parameters. Based on the finite-time control idea and the update laws, appropriate control laws are designed to ensure the stabilization of the closed-loop system in a finite time. The finite-time stability and convergence of the closed-loop system are analytically proved. A numerical simulation is given to demonstrate the applicability and robustness of the proposed finite-time controller and to verify the theoretical results.     

An adaptive critic neural network for motion control of a wheeled mobile robot

In this paper, we propose a new application of the adaptive critic methodology for the feedback control of wheeled mobile robots, based on a critic signal provided by a neural network (NN). The adaptive critic architecture uses a high-level supervisory NN adaptive critic element (ACE), to generate the reinforcement signal to optimise the associative search element (ASE), which is applied to approximate the non-linear functions of the mobile robot. The proposed tracking controller is derived from Lyapunov stability theory and can guarantee tracking performance and stability. A series of computer simulations have been used to emulate the performance of the proposed solution for a wheeled mobile robot.