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

Hendzel, Zenon

doi:10.1007/s11071-007-9234-1

Cited by 52 publications

(23 citation statements)

References 9 publications

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“…As far as control of wheeled mobile robots is concerned, usually robot motion without wheel slips and on the ground with homogenous properties is assumed, which is reflected e.g. in [3,4,11]. The works in which the tracking control algorithms take into account wheel slips and/or diverse ground properties can be found as well.…”

Section: Fig 1 Examples Of Wheeled Mobile Robots: a -Pioneer 2-dx mentioning

confidence: 99%

Dynamics Model of a Four-Wheeled Mobile Robot for Control Applications – A Three-Case Study

Trojnacki

2015

Advances in Intelligent Systems and Computing

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Abstract. The problem of dynamics modeling of a four-wheeled mobile robot is analyzed in this paper. All wheels of the robot are non-steered and the servomotors are used for driving the robot. Three cases of the robot drive system are considered. In the first case, two out of four wheels of the robot are independently driven, i.e., a pair of front or rear wheels. In the second case, the same wheels of the robot are driven but drive is also transmitted to the remaining wheels via toothed belts at each side of the robot. Finally, in the third case all four wheels are independently driven. Kinematic structure of the robot and its kinematics are described. The dynamics model of the robot dedicated for control applications is derived. It takes into account tire-ground contact conditions and wheel slips. The tire-ground contact conditions are characterized by coefficients of friction and rolling resistance. A simple form of the tire model, which considers only the most important effects of tire-ground interaction, is applied. The robot dynamics model also includes the presence of friction in kinematic pairs and the electromechanical model of servomotor drive unit. The presented robot dynamics model can be used for simulation-based investigations of control systems under development. Because the model was also formulated in a form linear with respect to parameters, it is possible to use it as a part of the robust or adaptive type control system.

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Section: Fig 1 Examples Of Wheeled Mobile Robots: a -Pioneer 2-dx mentioning

confidence: 99%

Dynamics Model of a Four-Wheeled Mobile Robot for Control Applications – A Three-Case Study

Trojnacki

2015

Advances in Intelligent Systems and Computing

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“…• Design and implementation of more advanced structure of 'Motion stabilizer' in order to further improve accuracy of the robot motion, for instance, based on neurocontroller, like in work [16].…”

Section: Directions Of Future Work Will Includementioning

confidence: 99%

Motion Stabilization System of a Four-Wheeled Mobile Robot for Teleoperation Mode: Experimental Investigations in Indoor Environment

Trojnacki

Dąbek

Kacprzyk

et al. 2015

Advances in Intelligent Systems and Computing

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Abstract. The paper is concerned with the problem of straight-line motion stabilization of a wheeled mobile robot with non-steered wheels. This system is dedicated for teleoperation mode of the robot and aims at improvement of control experience of a human operator. The structure of the robot motion stabilization system based on a PD regulator with feedback from actual linear velocity and yaw rate of a robot body is proposed. The motion stabilization system was implemented using a low-cost MEMS Inertial Measurement Unit and the PIAP SCOUT four-wheeled robot with non-steered wheels. In the present work the motion stabilization system is implemented in a form reduced to yaw angle stabilization only, with stabilization of linear velocity not taken into account. Reliable functioning of the linear velocity stabilization (e.g. wheel slip reduction) based on measurement signals from the low-cost IMU requires additional research. Functioning of the proposed robot motion stabilization system was verified in experimental research. Experiments were conducted for various robot velocities in indoor environment on a horizontal and even ground. Results of investigations without and with the motion stabilization system were compared. A significant improvement in accuracy of realization of desired motion was observed in the case when the motion stabilization system was active.

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“…Another branch of the model-free approach is neural network (NN)-based approximation. The NN training method requires a large amount of data, and the corresponding parameters are adjusted through the neurons, which cause a heavy computational burden [2]. In addition, fuzzy logic control, a widely used strategy, suffers from a slow response time and a serious dependence on the experience of selecting suitable member functions and rules [3,4].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Super-Twisting Control for Mobile Wheeled Inverted Pendulum Systems

2019

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Recently, the mobile wheeled inverted pendulum (MWIP) has gained an increasing interest in the field of robotics due to traffic and environmental protection problems. However, the MWIP system is characterized by its nonlinearity, underactuation, time-varying parameters, and natural instability, which make its modeling and control challenging. Traditionally, sliding mode control is a typical method for such systems, but it has the main shortcoming of a "chattering" phenomenon. To solve this problem, a super-twisting algorithm (STA)-based controller is proposed for the self-balancing and velocity tracking control of the MWIP system. Since the STA is essentially a second-order sliding mode control, it not only contains the merits of sliding mode control (SMC) in dealing with the uncertainties and disturbances but can also be effective in chattering elimination. Based on the STA, we develop an adaptive gain that helps to learn the upper bound of the disturbance by applying an adaptive law, called an adaptive super-twisting control algorithm (ASTA). The stability of the closed-loop system is ensured according to the Lyapunov theorem. Both nominal experiments and experiments with uncertainties are conducted to verify the superior performance of the proposed method.

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

Cited by 52 publications

References 9 publications

Dynamics Model of a Four-Wheeled Mobile Robot for Control Applications – A Three-Case Study

Dynamics Model of a Four-Wheeled Mobile Robot for Control Applications – A Three-Case Study

Motion Stabilization System of a Four-Wheeled Mobile Robot for Teleoperation Mode: Experimental Investigations in Indoor Environment

Adaptive Super-Twisting Control for Mobile Wheeled Inverted Pendulum Systems

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