Precision State Space Resonant Filter Structures for Digital Fixed-Point Converter Control Systems

2018 ◽  
Author(s):  
B. P. McGrath ◽  
C. A. Teixeira ◽  
D. G. Holmes
Keyword(s):  
Fixed Point ◽  
State Space ◽  
Control Systems ◽  
Filter Structures

scholarly journals Results on the approximate controllability of fractional hemivariational inequalities of order $1< r<2$

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
M. Mohan Raja ◽  
V. Vijayakumar ◽  
Le Nhat Huynh ◽  
R. Udhayakumar ◽  
Kottakkaran Sooppy Nisar
Keyword(s):  
Fixed Point ◽  
Control Systems ◽  
Approximate Controllability ◽  
Hemivariational Inequalities ◽  
Evolution Inclusions ◽  
Fractional Systems ◽  
Cosine Families ◽  
Fixed Point Approach ◽  
Semilinear Control Systems ◽  
Theoretical Results

AbstractIn this paper, we investigate the approximate controllability of fractional evolution inclusions with hemivariational inequalities of order $1< r<2$ 1 < r < 2 . The main results of this paper are verified by using the fractional theories, multivalued analysis, cosine families, and fixed-point approach. At first, we discuss the existence of the mild solution for the class of fractional systems. After that, we establish the approximate controllability of linear and semilinear control systems. Finally, an application is presented to illustrate our theoretical results.

Quantitative Models for Complex Physical Systems

2014 ◽  
Vol 1061-1062 ◽  
pp. 1144-1147
Author(s):  
Jun Fu ◽  
Jin Zhao Wu ◽  
Ning Zhou ◽  
Hong Yan Tan
Keyword(s):  
Quantitative Analysis ◽  
State Space ◽  
Control Systems ◽  
Chemical Reaction ◽  
Metric Space ◽  
Manufacturing Systems ◽  
Quantitative Model ◽  
Hybrid Automata ◽  
Physical Systems ◽  
The Difference

We present a quantitative model, called metric hybrid automata, for quantifying the behaviors of complex physical systems, such as chemical reaction control systems, manufacturing systems etc. Due to the introduction of a metric, the state space of hybrid automata forms a metric space, in which the difference of states can be quantified. Furthermore, in order to reveal the distance of system behaviors, we construct the simulation distance and the bisimulation distance, which quantify the similarity of system behaviors. Our model provides the basis for quantitative analysis for those complex physical systems.

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