scholarly journals CONTROL SYSTEM FOR STRUCTURURALLY AND PARAMETRICALLY UNDEFINED NON-AFFINE PLANT WITH NEUTRAL TYPE DELAY AND CONTROL DELAY

2021 ◽  
pp. 110-121
Author(s):  
L.V. Nikiforova ◽  
Keyword(s):  
Control System ◽  
Direct Measurement ◽  
Neutral Type ◽  
State Variables ◽  
Control Delay ◽  
Structural Uncertainties ◽  
Neutral Type Delay ◽  
And Control

The article deals with the synthesis of a controller for non-affine in input plant with neutral type delay and control delay, whose state variables are not available for direct measurement. The controller constructed on the basis of the hyperstability criterion compensates for the effects of delays, interference, parametric and structural uncertainties in the system.

scholarly journals A MULTICONNECTED COMBINED SYSTEM FOR A FUNCTIONALLY PARAMETRIC IN-DEFINITE PLANT WITH NONАFFINITY AND CONTROL DELAY

2021 ◽  
pp. 84-97
Author(s):  
E.L. Eremin ◽  
◽  
L.V. Nikiforova ◽  
E.A. Shelenok ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Reference Model ◽  
A Priori ◽  
Combined System ◽  
External Interference ◽  
Control Delay ◽  
Combined Control ◽  
Structural Uncertainties ◽  
And Control

The paper proposes a solution to the problem of synthesizing a multi-coupled combined control system for a non-affine plant with a delay in the input variable with gradually changing dynamics. The plant functions under conditions of a priori parametric and structural uncertainties in the presence of external interference when only the regulated variable is measured. The structure of a multiconnected control system includes an implicit reference model, a preceding-compensator and filter-correctors.

Analysis of Leveling Control System via Iterative Linear Matrix Inequalities with Full Order Observer

2012 ◽  
Vol 472-475 ◽  
pp. 1473-1476
Author(s):  
Jia Sun ◽  
Yu Hou Wu ◽  
Nan Xiao
Keyword(s):  
Control System ◽  
Design Procedure ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
State Variables ◽  
Linear Matrix Inequality Approach ◽  
Structural Uncertainties ◽  
Leveling Control ◽  
Uncertain Linear Systems ◽  
Iterative Linear Matrix Inequality

Abstract. This paper investigates leveling control system of suspended access platform using an observer-based controller. Uncertain linear systems for leveling control are derived and represented in terms of a set of matrix inequalities. In the system, all state variables needn’t be measured; the perturbations of leveling control are assumed to be described by structural uncertainties. The stiff problem is avoided since the design procedure is independent of the small parameter. The control problem can be effectively solved by the proposed iterative linear matrix inequality approach. The convergence of the algorithms is also studied. Furthermore, a numerical example and simulation results are given to illustrate the effectiveness of proposed method.

Trajectory Control of an Automated Guided Vehicle Using Feedback Linearization

2006 ◽  
Author(s):  
S. M. Mehdi Ansarey M. ◽  
M. J. Mahjoob
Keyword(s):  
Control System ◽  
Feedback Linearization ◽  
Degrees Of Freedom ◽  
Automated Guided Vehicle ◽  
State Variables ◽  
Discrete Curvatures ◽  
Steering Mechanism ◽  
Dynamics And Control ◽  
And Control ◽  
Three Degrees Of Freedom

In this paper, the dynamics and control of an automated guided vehicle (AGV) is described. The objective is to control the vehicle direction and location with respect to a prescribed trajectory. This is accomplished based on an optimum control strategy using vehicle state variables. A four-wheel vehicle with three degrees of freedom including longitudinal, lateral and yaw motion is considered. The nonlinearity of the tire and steering mechanism is also included. The control system design for circular, straight forward and composite path is presented based on feedback linearization. Some trajectory simulation for discrete curvatures is carried out. The controller was implemented within MATLAB environment. The design was also evaluated using ADAMS full vehicle assembly. The results demonstrated the accuracy of the model and the effectiveness of the developed control system.

Automatically Controlled Anti-Collision Manoeuvre and its Numerical Simulation with Disturbances

2013 ◽  
Vol 210 ◽  
pp. 156-165
Author(s):  
Jerzy Graffstein
Keyword(s):  
Numerical Simulation ◽  
Control System ◽  
Automatic Control ◽  
Numerical Simulations ◽  
Abrupt Change ◽  
State Variables ◽  
Control Laws ◽  
Analysis Of Results ◽  
System Robustness ◽  
And Control

The article presents the discussion focused on specific features of the problem of flying objects motion when performing an example of anti collision manoeuvre. To realise this task, the structure of automatic control system with appropriate control laws are proposed. The nature of discussed manoeuvre needs the appropriate numerical method for computing desired values of state variables for subsequent phases of objects motion. These values are obtained adequately for their roles in several phases of motion. Numerical simulations are completed for the aircraft performing the anti collision manoeuvre consisted in abrupt change of yaw. Objects behaviour was tested in case of motion affected by disturbances. The analysis of results obtained by numerical simulations makes possible conclusions on stability of objects motion and control system robustness to assumed kind and level of disturbances.

A Cognitive Machine in the Organization of Study

2010 ◽  
pp. 133-152
Author(s):  
Farley Simon Nobre ◽  
Andrew M. Tobias ◽  
David S. Walker
Keyword(s):  
Control System ◽  
Quantitative Analysis ◽  
Adaptive Learning ◽  
Management Control ◽  
Process Performance ◽  
State Variables ◽  
Management Control System ◽  
Double Loop Learning ◽  
Organization Process ◽  
And Control

Chapter X is concerned with the design of a management control system whose functional elements execute cognitive tasks of analysis, decision and control of the organization process performance. The management control system works in the form of an Adaptive Learning Cycle (ALC) whose principles of operation are based on single-loop and double-loop learning. Among its elements, it includes the participation of a cognitive machine whose responsibility involves the evaluation of the organization process performance through the tasks of analysis and decision. The design of the cognitive machine is reinforced with a set of criteria along with qualitative and quantitative analysis. Chapter X is complemented with Appendixes F, G and H. Appendix F defines the state variables (X) which are used in the management control of the organization process performance. Appendix G presents linguistic descriptions of the mental models which were designed and written for the cognitive machine. Appendix H demonstrates theorem proof as part of the quantitative analysis of the cognitive machine.

scholarly journals Cone separation, quadratic control systems and control of spin dynamics in the presence of decoherence

2017 ◽  
Vol 375 (2088) ◽  
pp. 20160214
Author(s):  
Navin Khaneja
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Spin Dynamics ◽  
Resonance Spectroscopy ◽  
Control Problems ◽  
State Variables ◽  
Systems And Control ◽  
Time Optimal ◽  
Optimal Efficiency ◽  
And Control

In this paper, we study some control problems related to the control of coupled spin dynamics in the presence of relaxation and decoherence in nuclear magnetic resonance spectroscopy. The decoherence is modelled through a master equation. We study some model problems, whereby, through an appropriate choice of state variables, the system is reduced to a control system, where the state enters linearly and controls quadratically. We study this quadratic control system. Study of this system gives us explicit bounds on how close a coupled spin system can be driven to its target state and how much coherence and polarization can be transferred between coupled spins. Optimal control for the quadratic control system can be understood as the separation of closed cones, and we show how the derived results on optimal efficiency can be interpreted in this formulation. Finally, we study some finite-time optimal control problems for the quadratic control system. This article is part of the themed issue ‘Horizons of cybernetical physics’.

Development of a Jacobian Module for Advanced Pulp and Paper Simulation and Control

TAPPI Journal ◽  
2009 ◽  
Vol 8 (1) ◽  
pp. 4-11
Author(s):  
MOHAMED CHBEL ◽  
LUC LAPERRIÈRE
Keyword(s):  
Control System ◽  
Nonlinear Behavior ◽  
Simulation Software ◽  
Pulp And Paper ◽  
Pid Controllers ◽  
Tuning Parameters ◽  
Pid Tuning ◽  
Fixed Set ◽  
And Control ◽  
Operating Points

Pulp and paper processes frequently present nonlinear behavior, which means that process dynam-ics change with the operating points. These nonlinearities can challenge process control. PID controllers are the most popular controllers because they are simple and robust. However, a fixed set of PID tuning parameters is gen-erally not sufficient to optimize control of the process. Problems related to nonlinearities such as sluggish or oscilla-tory response can arise in different operating regions. Gain scheduling is a potential solution. In processes with mul-tiple control objectives, the control strategy must further evaluate loop interactions to decide on the pairing of manipulated and controlled variables that minimize the effect of such interactions and hence, optimize controller’s performance and stability. Using the CADSIM Plus™ commercial simulation software, we developed a Jacobian sim-ulation module that enables automatic bumps on the manipulated variables to calculate process gains at different operating points. These gains can be used in controller tuning. The module also enables the control system designer to evaluate loop interactions in a multivariable control system by calculating the Relative Gain Array (RGA) matrix, of which the Jacobian is an essential part.

Еlectric Drive and Control System of Flying saw of electricweld item

2015 ◽  
Vol 19 (95) ◽  
pp. 50-53
Author(s):  
Aleksej A. Kravcov ◽  
◽  
Leonid G. Limonov ◽  
Valerij V. Sinelnikov ◽  
Stanislav V. Potapov
Keyword(s):  
Control System ◽  
Drive And Control ◽  
And Control
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