Balancing and Trajectory Tracking of Two-Wheeled Mobile Robot Using Backstepping Sliding Mode Control: Design and Experiments

2017 ◽  
Vol 87 (3-4) ◽  
pp. 601-613 ◽  
Author(s):  
Nasim Esmaeili ◽  
Alireza Alfi ◽  
Hossein Khosravi
Keyword(s):  
Sliding Mode Control ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Control Design ◽  
Wheeled Mobile Robot ◽  
Mode Control ◽  
Backstepping Sliding Mode Control

scholarly journals Adaptive Trajectory Tracking Control for Rotorcraft Using Incremental Backstepping Sliding Mode Control Strategy

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Moon Gyeang Cho ◽  
Useok Jung ◽  
Jun-Young An ◽  
Yoo-Seung Choi ◽  
Chang-Joo Kim
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Control Strategy ◽  
Tracking Control ◽  
Sliding Mode ◽  
Control Design ◽  
Backstepping Control ◽  
Trajectory Tracking Control ◽  
Mode Control ◽  
Backstepping Sliding Mode Control

This paper investigates the adaptive incremental backstepping sliding mode control for the rotorcraft trajectory-tracking control problem to enhance the robustness to the matched uncertainty in the model. First, the incremental dynamics is used for the control design to exclude the adverse effect of the mismatched model uncertainties on the trajectory-tracking performance. Secondly, the sliding-mode control strategy is adopted in the second design stage of the backstepping controller, and the effect of switching gains on the controller robustness is thoroughly studied using the rotorcraft model with different levels of the matched uncertainties. To clarify the robustness enhancement using the adaptive selection of switching gains, this paper chooses three different control structures consisting of the traditional backstepping control and two backstepping sliding mode controls with the fixed or adaptively adjusted switching gains. These control designs are applied to the trajectory-tracking control for the helical-turn maneuver of the Bo-105 helicopter to compare their relative robustness to the matched uncertainties. The results prove that adaptive incremental backstepping sliding mode control shows much higher robustness than other two designs, and the controller even with the fixed switching gains can be used to improve the robustness of the pure backstepping control design. Therefore, the present adaptive incremental backstepping sliding mode control is effectively applicable with the rotorcraft model which typically contains many different sources of both matched and mismatched uncertainties.

Integration of Multibody System Dynamics With Sliding Mode Control Using FPGA Technique for Trajectory Tracking Problems

2018 ◽  
Author(s):  
Ayman A. Nada ◽  
Abdullateef H. Bashiri
Keyword(s):  
Sliding Mode Control ◽  
Mobile Robot ◽  
Control Systems ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Integrated Control ◽  
Equations Of Motion ◽  
Multiple Input Multiple Output ◽  
Control Law ◽  
Mode Control

Trajectory tracking robotic systems require complex control procedures that occupy less space and need less energy. For these reasons, the development of computerized and integrated control systems is crucial. Recently, developing reconfigurable Field Programmable Gate Arrays (FPGAs) give a prominence of the complete robotic control systems. Furthermore, it has been found in the literature that the model-based control methods are most efficient and cost-effective. This model must interpret how multiple moving parts interact with each other and with their environment. On the other hand, MultiBody Dynamic (MBD) approach is considered to solve these difficulties to attain the models accurately. However, the obtained equations of motion do not match the well-developed forms of control theory. In this paper, the MBD model of a mobile robot is established; and the equations of motion are reshaped into their control canonical form. Additionally, the Sliding Mode Control (SMC) theory is used to design the control law. The constraints’ manifold, which is available in the equations of the MBD system, are imposed systematically as the switching surface. SMC is applied because of its ability to address multiple-input/multiple-output nonlinear systems without resorting any approximations. Eventually, the experimental verification of the proposed algorithm is carried out using DaNI mobile robot in which, a Reconfigurable Input/Output (RIO) board is used to reorient the control design, so that can fit the required trajectory. The control law is implemented using LabVIEW software and NI-sbRIO-9631 with acceptable performance. It is obvious that the integration of MBD/SMC/FPGA can be used successfully to develop embedded systems for the applications of trajectory tracking robotics.

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