Nonlinear Optimal and Flatness-Based Control Methods and Applications for Complex Dynamical Systems
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Robotics, mechatronics and autonomous systems can exhibit complex nonlinear dynamics which can lead to unsatisfactory transients and steady-state performance or even to instability. A standard approach in the control of these systems had been the concept of diffeomorphism to bring a system into a linear form. However, these methods are not straightforward and depend on complicated state-space model transformations. New methods have been investigated which are not constrained by the shortcomings of global linearization-based control schemes. They can be implemented in a computationally simple m...
Robotics, mechatronics and autonomous systems can exhibit complex nonlinear dynamics which can lead to unsatisfactory transients and steady-state performance or even to instability. A standard approach in the control of these systems had been the concept of diffeomorphism to bring a system into a linear form. However, these methods are not straightforward and depend on complicated state-space model transformations. New methods have been investigated which are not constrained by the shortcomings of global linearization-based control schemes. They can be implemented in a computationally simple manner, are followed by global stability proofs, and perform better than previous optimal control approaches for a wider class of nonlinear dynamical systems and applications. In this monograph, the authors present two main proven control methods: the nonlinear optimal (H-infinity) control method, and the flatness-based control approach These methods have shown to be better suited than previous standard approaches in solving control issues. They can be applied for a broad range of applications in mechatronics, industrial robotics, space robotics, robotic cranes and pendulums, autonomous vehicles, aerospace systems and satellites, power electronics, biosystems and financial systems. This very comprehensive book is a valuable resource for academic researchers and engineers, working on control systems and estimation methods, and lecturers and advanced students in the fields of control and automation, robotics and mechatronics, electrical engineering, electric power systems and power electronics, biosystems, computer science, financial systems, and physics. The book is also a very useful reference for skilled technical professionals developing real world applications.
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