scholarly journals LPV modeling of nonlinear systems: A multi‐path feedback linearization approach

2021 ◽  
Author(s):  
Hossam S. Abbas ◽  
Roland Tóth ◽  
Mihály Petreczky ◽  
Nader Meskin ◽  
Javad Mohammadpour Velni ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Feedback Linearization ◽  
Feedback Linearization Approach

A Robust Control Design Approach Combining Exact Linearization and High-Gain PI-Observer

2007 ◽  
Author(s):  
Yan Liu ◽  
Dirk So¨ffker
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
High Gain ◽  
Observer Design ◽  
Input State ◽  
Exact Linearization ◽  
Practical Applications ◽  
Robust Control Design ◽  
Nonlinear Control Method ◽  
Feedback Linearization Approach

This paper introduces a robust nonlinear control method combining classical feedback linearization and a high-gain PI-Observer (Proportional-Integral Observer) approach that can be applied to control a nonlinear single-input system with uncertainties or unknown effects. It is known that the lack of robustness of the feedback linearization approach limits its practical applications. The presented approach improves the robustness properties and extends the application area of the feedback linearization control. The approach is developed analytically and fully illustrated. An example which uses input-state linearization and PI-Observer design is given to illustrate the idea and to demonstrate the advantages.

Dynamic modeling and design of controller for the 2-DoF serial chain actuated by a cable-driven robot based on feedback linearization

2021 ◽  
pp. 095440622110279
Author(s):  
Vahid Bahrami ◽  
Ahmad Kalhor ◽  
Mehdi Tale Masouleh
Keyword(s):  
Dynamic Modeling ◽  
Pid Controller ◽  
Feedback Linearization ◽  
Tracking Error ◽  
Pid Controllers ◽  
Serial Chain ◽  
Simulation Results ◽  
The Stability ◽  
Feedback Linearization Approach ◽  
Bounded Disturbance

This study intends to investigate a dynamic modeling and design of controller for a planar serial chain, performing 2-DoF, in interaction with a cable-driven robot. The under study system can be used as a rehabilitation setup which is helpful for those with arm disability. The latter goal can be achieved by applying the positive tensions of the cable-driven robot which are designed based on feedback linearization approach. To this end, the system dynamics formulation is developed using Lagrange approach and then the so-called Wrench-Closure Workspace (WCW) analysis is performed. Moreover, in the feedback linearization approach, the PD and PID controllers are used as auxiliary controllers input and the stability of the system is guaranteed as a whole. From the simulation results it follows that, in the presence of bounded disturbance based on Roots Mean Square Error (RMSE) criteria, the PID controller has better performance and tracking error of the 2-DoF robot joints are improved 15.29% and 24.32%, respectively.

scholarly journals Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

2011 ◽  
Vol 8 (3) ◽  
pp. 307-323 ◽  
Author(s):  
Mohamed Bahita ◽  
Khaled Belarbi
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Feedback Linearization ◽  
Pendulum System ◽  
Rbf Network ◽  
Inverted Pendulum System ◽  
Neural Network Controller ◽  
Control Gain ◽  
On Line ◽  
Neural Feedback

In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

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