Control Design for Maximal Capability of Disturbance Rejection under General Control Input Saturation

Author(s):  
Xiaojing Song ◽  
Wenchao Xue ◽  
Yanlong Zhao
2014 ◽  
Vol 53 (4) ◽  
pp. 1073-1080 ◽  
Author(s):  
Danyal Bustan ◽  
Naser Pariz ◽  
Seyyed Kamal Hosseini Sani

Author(s):  
W Feng ◽  
I Postlethwaite

In robotics, despite considerable effort to minimize system modelling errors, uncertainties are always present and sometimes significant. In this paper, modelling errors are first represented by a class of bounded disturbances in the input channels (torques) of the robot. A measure of the robot system's ability to reject these disturbances is formulated in an L2 gain sense and a control design is subsequently proposed to achieve optimal disturbance rejection. If more detailed information is available on the plant-model mismatch, then the control design can be modified to incorporate an adaptive scheme (with explicit parameter updating laws) in order to reduce the conservativeness of the original design and to improve robust performance of the overall system.


2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Shou-Tao Peng

This paper studies the practical stability of incorporating integral compensation into the original low-and-high gain feedback law. The motivation for the incorporation is for achieving output regulation in the presence of constant disturbances without the use of a very large high-gain parameter required in the original approach. Due to numerical accuracy, the employment of very large high-gain parameters to eliminate steady-state error has the potential for inducing undesirable chattering effect on the control signal. A set of linear matrix inequalities is formulated in this study to obtain the related design parameters, by which the incorporation can achieve both the practical stabilization and asymptotic output regulation in the presence of input saturation and constant disturbances. Furthermore, the saturation of the control input can be shown to vanish in finite time during the process of regulation. Numerical examples are given to demonstrate the effectiveness of the proposed approach.


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