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About 5,482 papers for “Feedback linearization”

Feedback linearization

Aleksandr Voevoda, Filiushov Vladislav · Transaction of Scientific Papers of the Novosibirsk State Technical University · 2016

Cited by 0

Robust Granular Feedback Linearization

Lucas Oliveira, Valter J. S. Leite, Anderson Bento et al. · 2019

This paper addresses a novel granular feedback linearization approach to robustly and efficiently control imprecise nonlinear systems. This approach employs an evolving participatory learning algorithm to estimate the nonlinearities and to cancel their effects in the control loop. Simulation experiments with a surge tank are used to evaluate and to compare the performance of the robust granular feedback linearization with an adaptive controller based on a bacterial foraging technique, and an alternative granular evolving fuzzy robust feedback linearization mechanism. The results suggest that the robust granular feedback linearization performs better than the other approaches from the point of view the performance indexes commonly adopted in the process control practice like integral of the absolute error, the integral of the time-weighted absolute error, and the integral of the variability of the error.

Cited by 6

On nonregular feedback linearization

Zhendong Sun, Xiaohua Xia · 1997

Key Words — Nonlinear control systems; feedback linearization; linear systems; nonregular static feedback; differential geometric methods. Abstract — This paper investigates the use of nonregular (not necessarily regular) static/dynamic state feedbacks to achieve feedback linearization of affine nonlinear systems. First, we provide an example which is nonregular static feedback linearizable but is not regular dynamic feedback linearizable. Then, we present some necessary conditions as well as sufficient conditions for nonregular feedback linearization. The sufficient conditions are checkable, and if they are verified, a linearing–feedback could be calculated following a recursive procedure, provided the integrations of a set of completely integrable systems are available. 1

Cited by 0

Feedback linearization: inverted pendulum

Aleksandr Voevoda, Vladislav Filiushov · Transaction of Scientific Papers of the Novosibirsk State Technical University · 2016

. , . , , . u, u r . , ,

Cited by 0Open access

Feedback linearization - Lecture notes

Nikola Mišković, Zoran Vukić · 2013

This document follows the lectures on feedback linearization taught at the University of Zagreb, Faculty of Electrical Engineering and Computing.

Cited by 0

Nonlinear control Feedback linearization

Partial Differential Equations, Lyapunov Function · 2016

For a class of stabilizing boundary controllers for nonlinear 1D parabolic PDEs introduced (in full detail and with examples) in a companion paper (Vazquez & Krstic, 2008), we derive bounds for the gain kernels of our nonlinear Volterra controllers (in the

Cited by 0

Feedback linearization: inverted pendulum

Aleksandr Voevoda, Vladislav Filiushov · Transaction of Scientific Papers of the Novosibirsk State Technical University · 2016

ject. In order to apply the linear methods of synthesis for nonlinear objects, it is better to apply the feedback linearization, which leads the behavior of the source object to the line of sight. The possibility of such nonlinear feedback requires the fame of the whole state vector of the object in some cases and its derivative. For finding the state vector, we use the observer of a condition of a full order.

Cited by 0Open access

Algorithmic Transverse Feedback Linearization

D'Souza, Rollen · UWSpace (University of Waterloo) · 2022

The feedback equivalence problem, that there exists a state and feedback transformation between two control systems, has been used to solve a wide range of problems both in linear and nonlinear control theory. Its significance is in asking whether a particular system can be made equivalent to a possibly simpler system for which the control problem is easier to solve. The equivalence can then be utilized to transform a solution to the simpler control problem into one for the original control system.
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\nTransverse feedback linearization is one such feedback equivalence problem. It is a feedback equivalence problem first introduced by Banaszuk and Hauser for feedback linearizing the dynamics transverse to an orbit in the state-space. In particular, it asks to find an equivalence between the original nonlinear control-affine system and two subsystems: one that is nonlinear but acts tangent to the orbit, and another that is a controllable, linear system and acts transverse to the orbit. If this controllable, linear subsystem is stabilized, the original system converges upon the orbit.
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\nNielsen and Maggiore generalized this problem to arbitrary smooth manifolds of the state-space, and produced conditions upon which the problem was solvable. Those conditions do not help in finding the specific transformation required to implement the control design, but they did suggest one method to find the required transformation. It relies on the construction of a mathematical object that is difficult to do without system-specific insight.
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\nThis thesis proposes an algorithm for transverse feedback linearization that computes the required transformation. Inspired by literature that looked at the feedback linearization and dynamic feedback linearization problems, this work suggests turning to the "dual space" and using a tool known as the derived flag. The algorithm proposed is geometric in nature, and gives a different perspective on, not just transverse feedback linearization, but feedback linearization problems more broadly.

Cited by 0

Feedback linearization approach to distributed feedback manipulation

Zdeněk Hurák, Jiří Zemánek · 2012

This report formulates the problem of a distributed planar manipulation realized by shaping a spatially continuous force field. It also suggests a control strategy based on feedback linearization. Force fields derived from potential fields are considered. The potentials are “shaped” by a set of spatially discrete “actuators“ such as electrodes in the case of dielectrophoresis, electromagnets in the case of planar magnetic manipulators, or linear piezoelectric actuators in the case of deformable flat surfaces. The actuators form arrays. Distinguished feature of such force fields is that the contribution from an individual actuator usually affects the situation in the neighboring zones too, but usually not in too remote zones. As an idealization, the spatial domain is considered unbounded, which enables examination of asymptotic behavior of the manipulation scheme.

Cited by 6

Analysis of Exact Linearization and Aproximate Feedback Linearization Techniques

Gildeberto S. Cardoso, Leizer Schnitman · RePEc: Research Papers in Economics

This paper presents a study of linear control systems based on exact feedback linearization and approximate feedback linearization. As exact feedback linearization is applied, a linear controller can perform the control objectives. The approximate feedback linearization is required when a nonlinear system presents a noninvolutive property. It uses a Taylor series expansion in order to compute a nonlinear transformation of coordinates to satisfy the involutivity conditions.

Cited by 0

Error-feedback for amplifier linearization

I. Meier, J. B. De Swardt · Proceedings of the 1998 South African Symposium on Communications and Signal Processing-COMSIG '98 (Cat. No. 98EX214) · 2002

A novel general linearization topology called 'error-feedback' is presented and applied to the linearization of amplifiers. Error-feedback uses the difference/error between (linearly) scaled input and output signal in its feedback loop to reduce nonlinearity. It does not rely on main-amplifier gain for linearization as does traditional feedback. Instead an auxiliary amplifier is introduced into the feedback loop, leaving the main amplifier's linear gain unaffected. Results from theory, and simulation as well as measured results complement each other. They show that linearization takes place over a continuous band. The topology shows prospects for concurrent multi-band linearization. Internal delay and phase shifts influence design limits and overall performance.

Cited by 2