z-logo
open-access-imgOpen Access
Quantitative Feedback Control of Multiple Input Single Output Systems
Author(s) -
Javier Rico-Azagra,
Montserrat GilMartínez,
Jorge Elso
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/136497
Subject(s) - control theory (sociology) , quantitative feedback theory , controller (irrigation) , robust control , hierarchy , stability (learning theory) , computer science , control engineering , disturbance (geology) , control (management) , actuator , automatic frequency control , output feedback , task (project management) , control system , engineering , artificial intelligence , paleontology , agronomy , telecommunications , machine learning , economics , electrical engineering , market economy , biology , systems engineering
This paper presents a robust feedback control solution for systems with multiple manipulated inputs and a single measurable output. A structure of parallel controllers achieves robust stability and robust disturbance rejection. Each controller uses the least possible amount of feedback at each frequency. The controller design is carried out in the Quantitative Feedback Theory framework. The method pursues a smart load sharing along the frequency spectrum,where each branch must either collaborate in the control task or be inhibitedat each frequency. This reduces useless fatigue and saturation risk of actuators. Different examples illustrate the ability to deal with complex control problemsthat current MISO methodologies cannot solve. Main control challenges arisedue to the uncertainty of plant and disturbance models and when a fast-slowhierarchy of plants cannot be uniquely established

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom