scholarly journals A Multiple Control System for a Non-Linear Object with Uncertainty

2017 ◽  
Vol 6 (55) ◽  
pp. 114 ◽  
Author(s):  
Svetlana Ivanovna Kolesnikova
Keyword(s):  
Control System ◽  
Multiple Control ◽  
Non Linear ◽  
Linear Object

scholarly journals The control system of the yeast drying process

2018 ◽  
Vol 241 ◽  
pp. 01022 ◽  
Author(s):  
Piotr Wolszczak ◽  
Waldemar Samociuk
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Temperature Control ◽  
Object Identification ◽  
Control Methods ◽  
Drying Process ◽  
Process Flow ◽  
Non Linear ◽  
Linear Object

The article presents the results of choosing how to control a real non-linear object. Yeast drying requires a precise temperature control due to the possibility of overheating. The object changes properties during of the process flow. Object identification is used and a mathematical model is developed. The model is used to select roboust control methods. The results are compared to the system of two PID regulators used in practice.

Investigation of the stability of periodic motions in a nonlinear automatic control system based on the fast fourier transform

2003 ◽  
Vol 3 ◽  
pp. 297-307
Author(s):  
V.V. Denisov
Keyword(s):  
Fourier Transform ◽  
Control System ◽  
Automatic Control ◽  
Fast Fourier Transform ◽  
Automatic Control System ◽  
Resonance Phenomenon ◽  
Periodic Motions ◽  
Multiply Connected ◽  
Non Linear ◽  
The Stability

An approach to the study of the stability of non-linear multiply connected systems of automatic control by means of a fast Fourier transform and the resonance phenomenon is considered.

Scheduling Strategy of Multiple Semi-Active Controllers With Information on the Disturbance and the Structural Response

2016 ◽  
Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Katsuaki Sunakoda
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Active Control ◽  
Structural Response ◽  
Design Parameters ◽  
Control Law ◽  
Control Performance ◽  
Multiple Control ◽  
Control Laws ◽  
Scheduling Strategy

A scheduling strategy of multiple semi-active control laws for various earthquake disturbances is proposed to maximize the control performance. Generally, the semi-active controller for a given structural system is designed as a single control law and the single control law is used for all the forthcoming earthquake disturbances. It means that the general semi-active control should be designed to achieve a certain degree of the control performance for all the assumed disturbances with various time and/or frequency characteristics. Such requirement on the performance robustness becomes a constraint to obtain the optimal control performance. We propose a scheduling strategy of multiple semi-active control laws. Each semi-active control law is designed to achieve the optimal performance for a single earthquake disturbance. Such optimal control laws are scheduled with the available data in the control system. As the scheduling mechanism of the multiple control laws, a command signal generator (CSG) is defined in the control system. An artificial neural network (ANN) is adopted as the CSG. The ANN-based CSG works as an interpolator of the multiple control laws. Design parameters in the CSG are optimized with the genetic algorithm (GA). Simulation study shows the effectiveness of the approach.

Simple System Dynamics and Control System Project Models

2014 ◽  
pp. 113-133
Author(s):  
A. S. White
Keyword(s):  
Control System ◽  
Software Project ◽  
Software Projects ◽  
Initial State ◽  
Control Models ◽  
Non Linear ◽  
Dynamics And Control ◽  
Control System Model ◽  
System Project ◽  
And Control

This chapter examines the established Systems Dynamics (SD) methods applied to software projects in order to simplify them. These methods are highly non-linear and contain large numbers of variables and built-in decisions. A SIMULINK version of an SD model is used here and conclusions are made with respect to the initial main controlling factors, compared to a NASA project. Control System methods are used to evaluate the critical features of the SD models. The eigenvalues of the linearised system indicate that the important factors are the hiring delay time, the assimilation time, and the employment time. This illustrates how the initial state of the system is at best neutrally stable with control only being achieved with complex non-linear decisions. The purpose is to compare the simplest SD and control models available required for “good” simulation of project behaviour with the Abdel-Hamid software project model. These models give clues to the decision structures that are necessary for good agreement with reality. The final simplified model, with five states, is a good match for the prime states of the Abdel-Hamid model, the NASA data, and compares favourably to the Ruiz model. The linear control system model has a much simpler structure, with the same limitations. Both the simple SD and control models are more suited to preliminary estimates of project performance.

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