Robust Control Design for Wheeled Mobile Robotic Systems with Predictive Model

This paper presents a novel approach to address the challenges associated with the trajectory tracking control of wheeled mobile robots (WMRs). The proposed control approach is based on an indirect adaptive control PID using a neural network and discrete extended Kalman filter (IAPIDNN-DEKF). The proposed IAPIDNN-DEKF scheme uses the NN to identify the system Jacobian, which is used for tuning the PID gains using the stochastic gradient descent algorithm (SGD). The DEKF is proposed for state estimation (localization), and the NN adaptation improves the tracking error performance. By augmenting the state vector, the NN captures higher-order dynamics, enabling more accurate estimations, which improves trajectory tracking. Simulation studies in which a WMR is used in different scenarios are conducted to evaluate the effectiveness of the IAPIDNN-DEKF control. In order to demonstrate the effectiveness of the IAPIDNN-DEKF control, its performance is compared with direct adaptive NN (DA-NN) control, backstepping control (BSC) and an adaptive PID. On lemniscate, IAPIDNN-DEKF achieves RMSE values of 0.078769, 0.12086 and 0.1672. On sinusoidal trajectories, the method yields RMSE values of 0.01233, 0.015138 and 0.088707, and on sinusoidal with perturbation, RMSE values are 0.021495, 0.016504 and 0.090142 in x, y and θ, respectively. These results demonstrate the superior performance of IAPIDNN-DEKF for achieving accurate control and state estimation. The proposed IAPIDNN-DEKF offers advantages in terms of accurate estimation, adaptability to dynamic environments and computational efficiency. This research contributes to the advancement of robust control techniques for WMRs and showcases the potential of IAPIDNN-DEKF to enhance trajectory tracking and state estimation capabilities in real-world applications.

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 andCartesian 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 theCartesian frame as the base of theNCresults in perfect compensation of large position off‐tracks and unbiased estimation of the plant's unknown parameters. However, using theWMR'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 theNCby 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 theNCresults 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 theWMR'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 theNCs are evaluated through simulations.

This work focuses on the trajectory tracking control of Wheeled Mobile Robots (WMRs) through neural networks and feedback control techniques. We employ different neural network architectures to analyze the environment, divide the road into segments, and generate reference trajectories for the WMR. For control purposes, we consider the nonlinear kinematic model of the WMR considering the nonholonomic constraints. Then, this kinematic model is fully linearized through a dynamic controller, which accomplishes the trajectory tracking objective. The reference trajectory procedure and control scheme combination are used to attain the desired trajectory tracking objective. To this end, we utilize a numerical simulator for a scale vehicle, namely the Autominy car. Numerical simulations using Matlab and the Robotic Operative System (ROS) demonstrate the performance of the proposed control methodology.

In this paper, perfect trajectory tracking control of a non-holonomic Wheeled Mobile Robot (WMR) is tackled. First, a Sliding Mode Controller (SMC) is proposed to convergence of WMR on desired position, velocity and orientation trajectories. Due to the weak performance of the SMC against exogenous inputs, a Mamdani-type fuzzy system is designed to improve the tracking performance of the controller. However, the Fuzzy SMC (FSMC) cannot remove the chattering phenomena completely. Therefore, a supervisory Adaptive FSMC (AFSMC) is proposed to suppress the chattering effects. The superiority of the adaptive approach to the non-adaptive methods has been revealed through simulations.

This article presents the development of a Computed Torque Control (CTC) scheme for Cartesian velocity control of Wheeled Mobile Robots (WMRs). The literature presents extensive study on the need and suitability of the CTC scheme for robot arms. Many researchers have identified the benefits of using a CTC scheme for mobile robots. There is however very little information on CTC schemes for controlling mobile robots. The need for the CTC scheme stems from the fact that mobile robots (industrial AGVs) employing conventional velocity control schemes experience side slip due to suspended loads while negotiating curves, and the controller gains and accelerations need to be modified for changes in the dynamics. The structure of the proposed control scheme can be employed to control any mobile robot for which an inverse dynamic model exists, as a CTC scheme requires an inverse dynamic model to compute unique values for the motor current for a given trajectory. It is demonstrated that the existence of the inverse dynamic model is guaranteed for all differentially driven WMRs for all operating conditions, and is not affected by the number of castor wheels in the WMR. In the proposed CTC scheme, the linear and angular velocities of the WMR are controlled by adjusting the WMR accelerations, which are computed based on the motor torques required to follow a given trajectory. The motor torque is pre-computed based on a dynamic model of the mobile robotic system. The simulation and experimental results presented for a differentially driven WMR demonstrate that a computed-torque control scheme provides adaptive cruising and steering control for nominally tuned controller gains compared to a conventional velocity controller to achieve proper road following in the presence of changes in the dynamics. © 1997 John Wiley & Sons, Inc.

This paper was concerned with the trajectory tracking control of wheeled mobile robots using aperiodic intermittent control. By establishing the corresponding motion model of the wheeled mobile robot, a tracking control strategy was proposed based on the intermittent control approach and backstepping method. Compared to the controllers using continuous state feedback, the proposed control strategy was activated only on separate time intervals, which combined the features of closed- and open-loop control. An example was given to illustrate the effectiveness of the obtained result.

This paper presents a trajectory tracking control scheme for a three wheeled mobile robot using sliding mode control method system. The indoor mobile robot system is subject to parameter perturbation and external interference during trajectory tracking control, and the problem of slow tracking speed and large tracking error will occur. In order to improve the tracking precision, a sliding mode control algorithm based on new approach law is proposed. Firstly, the motion control model of mobile robot is established, and a sliding mode trajectory tracking controller is designed. Then adopting MATLAB to track the linear and circular trajectories, the tracking error converges to zero around 3s. Experimental results show that sliding mode control method effectively reduces sliding mode control input chattering, and the convergence speed and tracking accuracy improve. Finally, the effectiveness of the control method is thus verified in practice.

Extended state observer-based finite-time trajectory tracking control for wheeled mobile robots under FDI attacks

This paper considers the tracking problem of nonholonomic wheeled mobile robots with unknown dynamics. A new adaptive robust global dynamic controller is presented based on the canonical form of the wheeled mobile robots. This novel controller has low dimension and no singular points. Simulations show the effectiveness of the control scheme.

This paper deals with the development of a new strategy for the tracking control for Wheeled Mobile Robots (WMR). Mobile robots constitute a typical example of non-holonomic systems. They become progressively important in industries as a means of transport, detection and operation because of their effectiveness and flexibility. Some distinct applications of such system include instance order pick and place robots in manufacturing zone, post delivery robots in office buildings and deep see discovery robots. Wide area of research has been carried out on the tracking control problems of WMR. The kinematic tracking control schemes do not consider the dynamics of the mobile robot, so the tracking performance may not attain satisfactory. In this development a robust control law which is called backstepping sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. First and foremost the dynamic model of wheeled mobile robot is done by using Euler-Lagrange approach. Following the controller is designed to find an acceptable control law so that the tracking error asymptotically moves to zero as the time approaches infinity with an initial error. The simulation result shows the effectiveness of the proposed scheme.

Several research studies are conducted based on the control of wheeled mobile robots. Nonholonomy constraints associated with wheeled mobile robots have encouraged the development of highly nonlinear control techniques. Nonholonomic wheeled mobile robot systems might be exposed to numerous payloads as per the application requirements. This can affect statically or dynamically the complete system mass, inertia, the location of the center of mass, and additional hardware constraints. Due to the nonholonomic and motion limited properties of wheeled mobile robots, the precision of trajectory tracking control is poor. The nonholonomic wheeled mobile robot tracking system is therefore being explored. The kinematic model and sliding mode control model are analyzed, and the trajectory tracking control of the robot is carried out using an enhanced variable structure based on sliding mode. The shear and sliding mode controls are designed, and the control stability is reviewed to control the trajectory of a nonholonomic wheeled mobile robot. The simulation outcomes show that the projected trajectory track control technique is able to improve the mobile robot’s control, the error of a pose is small, and the linear velocity and angular speed can be controlled. Take the linear and angular velocity as the predicted trajectory.

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.

A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown longitudinal and lateral slipping. A kinematic model of a tracked wheeled mobile robot (WMR) is established in this paper, in which both longitudinal and lateral slipping is considered and processed as three time-varying parameters. The Unscented Kalman Filter (UKF) with the low pass filter is then introduced for real-time estimation of the slipping parameters online. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov theory. Simulation results show the effectiveness and robustness of the proposed method.

A visual servo controller is developed for a monocular camera system mounted on a wheeled mobile robot (WMR), which simultaneously solves the tracking and regulation control problems. A prerecorded image sequence (e.g., a video) or single image of four target points is used to define a desired trajectory or desired fixed position and orientation for the WMR. By comparing the target points from a stationary reference image with the corresponding target points in the live image and the prerecorded sequence of images, projective geometric relationships are exploited to construct Euclidean homographies. The information obtained by decomposing the Euclidean homographies is then used to derive a standard WMR form. The proposed result is the first visual servo control result that solves the unified tracking and regulation problem.

Describes the design and development of a heuristic fuzzy logic controller for the path tracking control of wheeled mobile robots (WMRs). The WMRs are applied in Micro Robot Soccer Tournament (MiroSot). The designed fuzzy controller is compared with a fine-tuned P-controller and a published sliding mode controller. Experimental results show an improvement of the overall performance.