This book focuses on the development and methodologies of trajectory control of differential-drive wheeled nonholonomic mobile robots. The methodologies are based on kinematic models (posture and configuration) and dynamic models, both subject to uncertainties and/or disturbances. The control designs are developed in rectangular coordinates obtained from the first-order sliding mode control in combination with the use of soft computing techniques, such as fuzzy logic and artificial neural networks. Control laws, as well as online learning and adaptation laws, are obtained using the stability…mehr
This book focuses on the development and methodologies of trajectory control of differential-drive wheeled nonholonomic mobile robots. The methodologies are based on kinematic models (posture and configuration) and dynamic models, both subject to uncertainties and/or disturbances. The control designs are developed in rectangular coordinates obtained from the first-order sliding mode control in combination with the use of soft computing techniques, such as fuzzy logic and artificial neural networks. Control laws, as well as online learning and adaptation laws, are obtained using the stability analysis for both the developed kinematic and dynamic controllers, based on Lyapunov's stability theory. An extension to the formation control with multiple differential-drive wheeled nonholonomic mobile robots in trajectory tracking tasks is also provided. Results of simulations and experiments are presented to verify the effectiveness of the proposed control strategies for trajectory tracking situations, considering the parameters of an industrial and a research differential-drive wheeled nonholonomic mobile robot, the PowerBot. Supplementary materials such as source codes and scripts for simulation and visualization of results are made available with the book.
Nardênio Almeida Martins has completed M.Sc. in Electrical Engineering from the Federal University of Santa Catarina (1997) and Ph.D. in Automation and Systems Engineering from the Federal University of Santa Catarina (2010). He is currently an associate professor in the Department of Informatics and the Graduate Program in Computer Science at the State University of Maringá and a member of the research groups "Robotics" of the Department of Automation and Systems of the Federal University of Santa Catarina-Florianópolis Campus and the "Automation of Systems and Robotics Group" at the State University of Santa Catarina-Joinville Campus, working mainly on the following research topics in robotics: robot manipulators, joint space, operational space, wheeled mobile robots, trajectory tracking, adaptive control, robust control theory, neural networks, fuzzy logic, and Lyapunov stability theory. Douglas Wildgrube Bertol has completed M.Sc. in Electrical Engineering from the FederalUniversity of Santa Catarina (2009) and Ph.D. in Automation and Systems Engineering from the Federal University of Santa Catarina (2015). He is currently an associate professor in the Department of Electrical Engineering and the Graduate Program in Electrical Engineering at the Universidade do Estado de Santa Catarina and a member of the Systems Automation and Robotics Research Group (GASR) at the same University, working mainly in subjects of applied robotics, mobile robots, trajectory tracking, sliding mode control theory, neural networks, fuzzy logic, and Lyapunov stability theory.
Inhaltsangabe
Background on DWMR System Modeling.- Background on Control Problems and Systems.- Background on Simulation and Experimentation Environments.- Backstepping control.- Robust control: first-order sliding mode control techniques.- Approximated robust control: first-order quasi-sliding mode control techniques.- Adaptive robust control: adaptive fuzzy sliding mode control technique.- Adaptive robust control: adaptive neural sliding mode control technique.- Formation Control of DWMRs: sliding mode control techniques.
Background on DWMR System Modeling.- Background on Control Problems and Systems.- Background on Simulation and Experimentation Environments.- Backstepping control.- Robust control: first-order sliding mode control techniques.- Approximated robust control: first-order quasi-sliding mode control techniques.- Adaptive robust control: adaptive fuzzy sliding mode control technique.- Adaptive robust control: adaptive neural sliding mode control technique.- Formation Control of DWMRs: sliding mode control techniques.
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