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Control of Robots and Manipulators
Published in William S. Levine, Control System Applications, 2018
Mark W. Spong, Joris De Schutter, Herman Bruyninckx, John Ting-Yung Wen
The notion of feedback linearization of nonlinear systems is a relatively recent idea in control theory, whose practical realization has been made possible by the rapid development of microprocessor technology. The basic idea of feedback linearization control is to transform a given nonlinear system into a linear system by use of a nonlinear coordinate transformation and nonlinear feedback. Feedback linearization is a useful paradigm because it allows the extensive body of knowledge from linear systems to be brought to bear to design controllers for nonlinear systems. The roots of feedback linearization in robotics predate the general theoretical development by nearly a decade, going back to the early notion of feedforward-computed torque [8].
Feedback Linearization Control
Published in Mourad Boufadene, Nonlinear Control Systems Using MATLAB®, 2018
A Feedback linearization is a common approach used in controlling nonlinear systems. The approach involves coming up with a transformation to the nonlinear system into equal linear system that could be controlled easily using a new input control. Feedback linearization could be applied to nonlinear systems of the form: () x˙=f(x)+g(x)uy=h(x)
Background on Dynamic Systems
Published in F.L. Lewis, S. Jagannathan, A. Yeşildirek, Neural Network Control of Robot Manipulators and Nonlinear Systems, 2020
F.L. Lewis, S. Jagannathan, A. Yeşildirek
There are basically two feedback linearization techniques-'— input-state feedback linearization and input-output (i/o) feedback linearization. The former requires a complex set of mathematical tools including Frobenius7 Theorem and Lie algebra. The control laws derived are often complex due to the need to determine nonlinear state-space transformations and their inverses. On the other hand, i/o feedback linearization is direct to apply and represents more of an engineering approach to control systems design. It is very useful for large classes of nonlinear controls problems including those treated in this book, which encompass robot manipulators, mechanical systems, and other Lagrangian systems.
Trajectory-tracking of 6-RSS Stewart-Gough manipulator by feedback-linearization control using a novel inverse dynamic model based on the force distribution algorithm
Published in Mathematical and Computer Modelling of Dynamical Systems, 2020
Zafer Mahmoud, Mohammad Reza Arvan, Vahab Nekoukar, Mohammad Rezaei
As it is clear in the derived inverse dynamic models, this parallel manipulator is highly nonlinear and coupled by nature. Therefore, the feedback linearization control, also known as the inverse dynamic control, can be employed to compensate for this nonlinearity and coupling and enable us to apply linear control strategies to the linearized system that results from applying feedback linearization.
Design and realization of an auto-tuned modified neuro-fuzzy sliding-mode-based IM drive deploying feedback linearization
Published in EPE Journal, 2018
Rabi Narayan Mishra, Kanungo Barada Mohanty
Feedback linearization control is an approach where the linear control theory can be implemented efficiently with naturally nonlinear system dynamics. This contrasts absolutely from conventional linearization frameworks as this linearization technique is satisfied universally, rather than the vicinity of an equilibrium point [28]. The theoretical approach and a methodology are given in [28].