scholarly journals Non-linear stimulus-response behavior of the human stance control system is predicted by optimization of a system with sensory and motor noise

2010 ◽  
Vol 30 (3) ◽  
pp. 759-778 ◽  
Author(s):  
Herman van der Kooij ◽  
Robert J. Peterka
Keyword(s):  
Control System ◽  
Response Behavior ◽  
Stimulus Response ◽  
Motor Noise ◽  
Stance Control ◽  
Non Linear

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.

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.

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.

A pole placement controller for non-linear dynamic plants

2002 ◽  
Vol 216 (6) ◽  
pp. 467-476 ◽  
Author(s):  
Q M Zhu ◽  
L Z Guo
Keyword(s):  
Control System ◽  
System Design ◽  
Discrete Time ◽  
Linear Control System ◽  
Linear Control ◽  
Pole Placement ◽  
Hammerstein Model ◽  
Control System Design ◽  
Non Linear ◽  
Pole Placement Controller

In this study a control-oriented model is proposed to represent a wide range of non-linear discrete-time dynamic plants. As a testimony to the efficiency of the model structure for control system design, a pole placement controller is designed for non-linear discrete-time plants. Mathematically the solution of the controller output is converted into resolving a polynomial equation in the current control term u( t), which significantly reduces the difficulties encountered in non-linear control system synthesis and computational complexities. The integrated procedure provides a straightforward methodology to use in linear control system design techniques when designing non-linear control systems. For a demonstration of the effectiveness of the proposed methodology used to deal with practical problems, pole placement controllers are designed for three non-linear plants, including the Hammerstein model, a laboratory-scale liquid level system and a continuous stirred tank reactor. The simulation results are presented with graphical illustrations.

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