A Neural Network Controller Design for the Mecanum Wheel Mobile Robot

Abstract

Advanced controllers are an excellent choice for the trajectory tracking problem of Wheeled Mobile Robots (WMRs). However, these controllers pose a challenge to the hardware structure of WMRs due to the controller's complex structure and the large number of calculations needed. In that context, designing a controller with a simple structure and a small number of computations but good real-time performance is necessary in order to improve the tracking accuracy for the WMRs without requiring high hardware architecture. In this work, a neural network controller with a simple structure for the trajectory-tracking of a Mecanum-Wheel Mobile robot (MWMR) based on a reference controller is proposed. A two-layer feedforward neural network is designed as a tracking controller for the robot. The neural network is trained with a sample input-output data set so that the error between the neural network output and the reference control signal of the supervisory controller is minimal. The neural network parameters are trained to update over time. The simulation results verified the effectiveness of the neural network controller, whose parameters are tuned adaptively to ensure a fast convergence to the desired Bézier trajectory.

Design and Development of a Wheelchair Prototype

“…Due to advancements in science and technology, machines equipped with integrated electrical control systems have become increasingly familiar [16][17][18][19][20][21][22][23]. This study aims to establish a systematic approach to develop and produce a…”

Performance Comparison of Different Fuzzy Logic Controllers on Vehicle-Caravan Systems

“…Active control techniques are used in VC systems against instability modes [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. Active control techniques can be used in both the towing vehicle and the caravan system.…”

“…In ASC, a moment is created in the center of gravity to prevent skidding by giving a steering angle to the front or rear wheels [9], while the mechanism of the front or rear wheel must be arranged accordingly to use ASC. In the case of understeer in the ADB braking system, braking is applied to the right or left wheels, and a torque is applied in the opposite direction to the yaw moment that occurs around the center of gravity to damp the swing [7,9,[16][17][18][19][20][21]. The ADB system is often preferred, as it does not require much extra hardware compared to the ASC.…”

“…Model-based and model-independent methods are used in active control techniques developed using ADB in VC systems. The Model Predictive Control (MPC) controller was developed to increase the lateral stability of the trailer system and prevent the occurrence of unstable situations [7,[21][22]. Examining the performance of the braking controller using the Linear Quadratic Regulator (LQR) technique showed that stable responses were produced [4,6,22].…”

“…This study used the fuzzy logic method as a modelindependent control technique, as there is no need for a system model if it is used as an active control technique in the VC system. Several studies used the FLC technique in VC systems, showing that unstable states were prevented [9,[21][22][23][24]. Such studies usually compare the proposed controller with other control techniques or when the controller is turned off.…”