Experimental Verification of Discrete Linear-Quadratic-Gaussian Control System of Electro-Hydraulic Servodrive

In this paper, the CVT shifting control system based on vehicle operating conditions is modeled and simulated using MATLAB/SIMULINK. The modeling stage begins with the derivation of required mathematical model to illustrate the CVT shifting control system. Then, Linear Quadratic Gaussian (LQG), Proportional- Integrated-Derivative (PID) and Pole Placement are applied for controlling the shifting speed ratio of the modeled CVT shifting system. Simulation results of shifting controllers are presented in time domain and the results obtained with LQG are compared with the results of PID and Pole placement technique. Finally, the performances of shifting speed ratio controller systems are analyzed in order to choose which control method offers the better performance with respect to the desired speed ratio. According to simulation results, the LQG controller delivers better performance than PID and Pole Placement controller.

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Linear quadratic Gaussian controller design for plasma current, position and shape control system in ITER

Fusion Engineering and Design ◽

10.1016/s0920-3796(98)00431-1 ◽

1999 ◽

Vol 45 (1) ◽

pp. 55-64 ◽

Cited By ~ 26

Author(s):

V Belyakov ◽

A Kavin ◽

V Kharitonov ◽

B Misenov ◽

Y Mitrishkin ◽

...

Keyword(s):

Control System ◽

Shape Control ◽

Controller Design ◽

Plasma Current ◽

Current Position ◽

Linear Quadratic ◽

Linear Quadratic Gaussian

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Real-Time Simulation of Non-Linear Quadratic Gaussian Adaptive Control System

Advances in Simulation - Systems Analysis and Simulation I ◽

10.1007/978-1-4684-6389-7_67 ◽

1988 ◽

pp. 319-322

Author(s):

Andrzej Dzieliński

Keyword(s):

Adaptive Control ◽

Control System ◽

Real Time ◽

Adaptive Control System ◽

Linear Quadratic ◽

Linear Quadratic Gaussian ◽

Real Time Simulation ◽

Time Simulation ◽

Non Linear

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A linear quadratic Gaussian framework for optimal networked control system design

2008 American Control Conference ◽

10.1109/acc.2008.4587086 ◽

2008 ◽

Cited By ~ 3

Author(s):

Mohammad Tabbara ◽

Dragan Nesic ◽

Nuno C. Martins

Keyword(s):

Control System ◽

System Design ◽

Networked Control System ◽

Networked Control ◽

Control System Design ◽

Linear Quadratic ◽

Linear Quadratic Gaussian

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Neuromorphic Smart Controller for Seismically Excited Structures

Design Optimization of Active and Passive Structural Control Systems ◽

10.4018/978-1-4666-2029-2.ch009 ◽

2013 ◽

pp. 216-233

Author(s):

Yeesock Kim ◽

Changwon Kim ◽

Reza Langari

Keyword(s):

Control System ◽

Orbitofrontal Cortex ◽

Mr Damper ◽

Dynamic Responses ◽

Building Structure ◽

Linear Quadratic ◽

Seismic Excitations ◽

Linear Quadratic Gaussian ◽

The One ◽

Brain Emotional Learning

In this chapter, an application of a neuromorphic controller is proposed for hazard mitigation of smart structures under seismic excitations. The new control system is developed through the integration of a brain emotional learning-based intelligent control (BELBIC) algorithm with a proportional-integral-derivative (PID) compensator and a clipped algorithm. The BELBIC control is based on the neurologically inspired computational model of the amygdala and the orbitofrontal cortex. A building structure employing a magnetorheological (MR) damper under seismic excitations is investigated to demonstrate the effectiveness of the proposed hybrid clipped BELBIC-PID control algorithm. The performance of the proposed hybrid neuromorphic controller is compared with the one of a variety of conventional controllers such as a passive, PID, linear quadratic Gaussian (LQG), and emotional control systems. It is shown that the proposed hybrid neuromorphic controller is effective in improving the dynamic responses of structure-MR damper systems under seismic excitations, compared to the benchmark controllers.

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