Sliding Mode Control for Trajectory Tracking of a Non-holonomic Mobile Robot using Adaptive Neural Networks

In this work a sliding mode control method for a non-holonomic mobile robot using an adaptive neural network is proposed. Due to this property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a nominal kinematic model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate for the dynamics of the robot. A neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold, using an online adaptation scheme. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown non-linear dynamics. Also, the proposed control technique can reduce the steady-state error using the online adaptive neural network with sliding mode control; the design is based on Lyapunov’s theory. Experimental results show that the proposed method is effective in controlling mobile robots with large dynamic uncertaintiesFil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin

Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy

Terminal Sliding Mode Control of Mobile Wheeled Inverted Pendulum System with Nonlinear Disturbance Observer

A terminal sliding mode controller with nonlinear disturbance observer is investigated to control mobile wheeled inverted pendulum system. In order to eliminate the main drawback of the sliding mode control, “chattering” phenomenon, and for compensation of the model uncertainties and external disturbance, we designed a nonlinear disturbance observer of the mobile wheeled inverted pendulum system. Based on the nonlinear disturbance observer, a terminal sliding mode controller is also proposed. The stability of the closed-loop mobile wheeled inverted pendulum system is proved by Lyapunov theorem. Simulation results show that the terminal sliding mode controller with nonlinear disturbance observer can eliminate the “chattering” phenomenon, improve the control precision, and suppress the effects of external disturbance and model uncertainties effectively

Development of robust control scheme for wheeled mobile robot in restricted environment

This research is aimed to develop a wheeled mobile robot (WMR) that is able to track reliably and robustly a certain trajectory in a constrained environments. The control of MWR in the restricted areas during path execution still a complicated problem in robot researches, since it needs to maintain the tracking errors at the zero level and the wheel mobile robot must follow robustly the pre-defined path using a suitable control system; otherwise it can cause to crash robot with other objects. A novel algorithm so called laser simulator logic (LSL) has been develo ped to estimate the inertia moment when the environment is noisy and cannot use fuzzy logic algorithm. This algorithm gives the possibility to calculate the membership function with highly overlapped linguistic variables and thus remove the noise. The proposed LSL is then integrated with existing Active Force Control (AFC) and PD to ensure good closed loop performance and reject the noise and disturbances. A simulation study of WMR control in pre-planned paths in two environments namely, zigzag and highly curved terrains, has been conducted to verify the proposed algorithm and compare it with other existed algorithms. Thus, a new WMR prototype with four wheels, two differential and two castor wheels has been designed, fabricated and inspected in the laboratory. The WMR is equipped with two sensors, encoders and current sensor, and direct current (DC) motor to perform the required path in the constrained environments. An embedded controller has been used to integrate the platform components such electronics co mponents, mechanical components and computer programs with appropriate interfacing structure. PD-AFC controller system employing the use of three feedback control loops, namely, internal, external and quick compensation loops, have been used to compensate the disturbance in constrained environments. The external loop is used to control the kinematics parameters of the control system via PD controller, However, the internal loop is used to control the dynamic of robot and disturbance rejection via AFC controller. On the other hand, a quick compensation loop has been introduced to compensate the difference between the reference and actual acceleration via PD controller. The results of simulation show that the proposed algorithm has the best performance among a ll controllers either in zigzag or circular environments, especially when the disturbances are applied. To confirm the results of simulation for the proposed algorithm, a real-time experiments in circular path has been conducted to show that the proposed controller scheme is robust enough in the real -time control and able to track the robot effectively on its reference path. The experimental results work show the capability of the proposed algorithms and the new controller to robustly move the WMR in the constrained environments, thereby it verifys the simulation counterpart

Time-Varying Integral Adaptive Sliding Mode Control for the Large Erecting System

Considering the nonlinearities, uncertainties of large erecting system, and the circumstance disturbances in erecting process, a novel sliding mode control strategy is proposed in this research. The proposed control strategy establishes the sliding mode without reaching phase using an integral sliding surface. Thus, robustness against uncertainties increases from the very beginning of the process. Furthermore, adaptive laws are used for the controller to estimate the unknown but bounded system uncertainties. Therefore, the upper bounds of the system uncertainties are not required to be known in advance. Then, the time-varying term is applied to ensure the global robustness. Moreover, the boundary layer method is used to attenuate the high frequency chattering. The experiment results demonstrated that the proposed strategy could effectively restrain parametric uncertainties and external disturbances and improve the tracking accuracy in the erecting process. In addition, the control performance of the proposed control strategy is better than that of the PID control and the conventional sliding mode control

An adaptive variable structure controller for the trajectory tracking of a nonholonomic mobile robot with uncertainties and disturbances

In this paper, a trajectory tracking control for a nonholonomic mobile robot subjected to uncertainties and disturbances in the kinematic model is proposed. An adaptive variable structure controller based on the sliding mode theory is used, and applied to compensate these uncertainties and disturbances. To minimize the problems found in practical implementation using classical variable structure controllers, and eliminate the chattering phenomenon as well as compensate disturbances a neural compensator is used, which is nonlinear and continuous, in lieu of the discontinuous portion of the control signals present in classical forms. The proposed neural compensator is designed by a modeling technique of Gaussian radial basis function neural networks and does not require the time-consuming training process. Stability analysis is guaranteed with basis on the Lyapunov method. Simulation results are provided to show the effectiveness of the proposed approach.Facultad de Informátic