Fuzzy adaptive iterative sliding mode control for sail-assisted ship trajectory tracking

2017 ◽  
Author(s):  
Ru Wang ◽  
Zhipeng Shen
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Mode Control ◽  
Fuzzy Adaptive

Fuzzy adaptive sliding mode control of a direct drive robot

1996 ◽  
Vol 19 (2) ◽  
pp. 215-227 ◽  
Author(s):  
Kemalettin Erbatur ◽  
Okyay Kaynak ◽  
Asif Sabanovic ◽  
Imre Rudas
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
Direct Drive ◽  
Adaptive Sliding Mode ◽  
Mode Control ◽  
Fuzzy Adaptive

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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