Generating parity relations for detecting and identifying control system component failures

1988 ◽  
Vol 11 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Mohammad-Ali Massoumnia ◽  
Wallace E. Vander Velde
Keyword(s):  
Control System ◽  
System Component ◽  
Component Failures

Research of beam control system component simulation and separation method of the kinematics coupling

2015 ◽  
Author(s):  
Yufang Yue ◽  
Xiaogang Xie ◽  
Jianzhu Zhang ◽  
Jianzhu An ◽  
Feizhou Zhang
Keyword(s):  
Control System ◽  
Separation Method ◽  
System Component ◽  
Beam Control

Application of metaheuristic algorithms in interval type-2 fractional order fuzzy TID controller for nonlinear level control process under actuator and system component faults*

2021 ◽  
Vol 14 (1) ◽  
pp. 33-53 ◽  
Author(s):  
Himanshukumar R. Patel ◽  
Vipul A. Shah
Keyword(s):  
Control System ◽  
Fractional Order ◽  
Pid Controller ◽  
System Component ◽  
Level Control ◽  
Content Type ◽  
Level Control System ◽  
Interval Type ◽  
Component Faults

PurposeThe two-tank level control system is one of the real-world's second-order system (SOS) widely used as the process control in industries. It is normally operated under the Proportional integral and derivative (PID) feedback control loop. The conventional PID controller performance degrades significantly in the existence of modeling uncertainty, faults and process disturbances. To overcome these limitations, the paper suggests an interval type-2 fuzzy logic based Tilt-Integral-Derivative Controller (IT2TID) which is modified structure of PID controller.Design/methodology/approachIn this paper, an optimization IT2TID controller design for the conical, noninteracting level control system is presented. Regarding to modern optimization context, the flower pollination algorithm (FPA), among the most coherent population-based metaheuristic optimization techniques is applied to search for the appropriate IT2FTID's and IT2FPID's parameters. The proposed FPA-based IT2FTID/IT2FPID design framework is considered as the constrained optimization problem. System responses obtained by the IT2FTID controller designed by the FPA will be differentiated with those acquired by the IT2FPID controller also designed by the FPA.FindingsAs the results, it was found that the IT2FTID can provide the very satisfactory tracking and regulating responses of the conical two-tank noninteracting level control system superior as compared to IT2FPID significantly under the actuator and system component faults. Additionally, statistical Z-test carried out for both the controllers and an effectiveness of the proposed IT2FTID controller is proven as compared to IT2FPID and existing passive fault tolerant controller in recent literature.Originality/valueApplication of new metaheuristic algorithm to optimize interval type-2 fractional order TID controller for nonlinear level control system with two type of faults. Also, proposed method will compare with other method and statistical analysis will be presented.

Fault-Tolerant Control of Mechanical Systems Using Neural Networks

2012 ◽  
pp. 187-205
Author(s):  
Sunan Huang ◽  
Kok Kiong Tan ◽  
Tong Heng Lee
Keyword(s):  
Control System ◽  
Failure Modes ◽  
Fault Tolerant ◽  
A Priori ◽  
Mechanical Systems ◽  
Fault Tolerant Control ◽  
Working Environment ◽  
Harsh Environment ◽  
Environment Control ◽  
Component Failures

Due to harsh working environment, control systems may degrade to an unacceptable level, causing more regular fault occurrences. In this case, it is necessary to provide the fault-tolerant control for operating the system continuously. The existing control techniques have given some ways to solve this problem, but if the system behaves in an unanticipated manner, then the control system may need to be modified, so that it handles the modified system. In this chapter, the authors are concerned with how this control system can be done automatically, and when it can be done successfully. They aimed in this work at handling unanticipated failure modes, for which solutions have not been solved completely. The model-based fault-tolerant controller with a self-detecting algorithm is proposed. Here, the radial basis function neural network is used in the controller to estimate the unknown failures. Once the failure is detected, the re-configured control is activated and then maintains the system continously. The fault-tolerant control is illustrated in two cases. It is shown that the proposed method can cope with different failure modes which are unknown a priori. The result indicates that the solution is suitable for a class of mechanical systems whose dynamics are subject to sudden changes resulting from component failures when working in a harsh environment.

Ethics as a control system component

1996 ◽  
Vol 2 (3) ◽  
pp. 259-262 ◽  
Author(s):  
R. E. Spier
Keyword(s):  
Control System ◽  
System Component

The microprocessor as a railway control system component

1976 ◽  
Vol 1 (1) ◽  
pp. 41-47 ◽  
Author(s):  
AH Cribbens ◽  
DH Newing ◽  
HA Ryland
Keyword(s):  
Control System ◽  
System Component

Beam control system component simulation and separation method of kinematic coupling

2014 ◽  
Vol 26 (9) ◽  
pp. 91006
Author(s):  
岳玉芳 Yue Yufang ◽  
谢晓钢 Xie Xiaogang ◽  
张建柱 Zhang Jianzhu ◽  
安建祝 An Jianzhu ◽  
张飞舟 Zhang Feizhou
Keyword(s):  
Control System ◽  
Separation Method ◽  
System Component ◽  
Beam Control ◽  
Kinematic Coupling
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