The Design of LQR and Fuzzy Logic Controller for a Thermal System with Large Time Delay

2010 ◽  
pp. 293-298 ◽  
Author(s):  
Seiyed Zareh ◽  
Ali Jahromi ◽  
Atabak Sarafan ◽  
Amir Khayyat
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Fuzzy Logic Controller ◽  
Large Time ◽  
Thermal System

MUSCLE RELAXATION CONTROLLED BY AUTOMATED ADMINISTRATION OF CISATRACURIUM

2006 ◽  
Vol 18 (06) ◽  
pp. 284-295 ◽  
Author(s):  
CHEN-TSE CHUANG ◽  
SHOU-ZEN FAN ◽  
JIANN-SHING SHIEH
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Automatic Control ◽  
Fuzzy Logic Controller ◽  
Muscle Relaxation ◽  
Manual Control ◽  
Logic Control ◽  
Long Term Effect ◽  
Clinical Control ◽  
The Mean

In this paper, the muscle relaxant agent (i.e., cisatracurium) and three clinical control methods (i.e., 13 patients undergoing intermitted bolus control, 15 patients undergoing intensive manual control and 15 patients) undergoing automatic fuzzy logic control (FLC), were used for maintaining depth of muscle relaxation (DOM) during surgery. Cisatracurium, a muscle relaxation drug with long-term effect, low metabolic loading, but long delay time, is widely used in operating rooms and ICUs. Meanwhile, the rules for the FLC were developed from the experimental experience of intensive manual control after learning from 15 patient trials. According to experts' experimental experience, our FLC inputs were chosen from T1% error and trend of T1% which differ from other previous studies on eliminating the effect of time delay from cisatracurium. In individual clinical experimental results, the mean(SD) of the mean T1% error in 13 patients for intermitted bolus control, in 15 patients for intensive manual control, and in 15 patients for automatic control was 8.76(1.46), 1.65(1.67), and 0.48(1.43), respectively. The t test results show that automatic control is not significantly different from intensive manual control. The results show that a simple fuzzy logic controller derived from anesthetists ' clinical trials can provide good accuracy without being affected by the pharmacological time delay problem.

Eigenvalue, Robustness and Time Delay Analysis of Hierarchical Control Scheme in Multi-DER Microgrid to Enhance Small/Large-Signal Stability Using Complementary Loop and Fuzzy Logic Controller

2017 ◽  
Vol 26 (06) ◽  
pp. 1750099 ◽  
Author(s):  
Hamid Reza Baghaee ◽  
Mojtaba Mirsalim ◽  
Gevork B. Gharehpetian ◽  
Heidar Ali Talebi
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Fuzzy Logic Controller ◽  
Reactive Power ◽  
Hierarchical Control ◽  
System Stability ◽  
Delay Analysis ◽  
Large Signal ◽  
Control Scheme ◽  
Real Time Digital Simulator

In this paper, the proposed hierarchical control scheme adds new control loop to control the reactive power reference by a fuzzy logic controller to have the benefit of increasing the system stability margins and moreover, eigenvalue, robustness and time delay analysis of proposed control scheme are presented. The reported droop-based control methods of VSI-based microgrids including hierarchical droop-based control scheme are limited to primary and secondary control levels while the proposed control scheme is completely analyzed so that the three hierarchical control levels modeled for both grid-connected mode and islanded mode. This scheme maintains the stability of microgrids not only for the small-signal events, but also for large-signal disturbances such as three phase and single phase to ground faults, heavy motor starting, etc. However, power sharing to loads and network is sufficiently done. To demonstrate the effectiveness of the proposed hierarchical controller, simulation studies have been performed on a microgrid consisting of four units of distributed generation with local loads and in presence of main grid using MATLAB/SIMULINK software and validated using OPAL RT real-time digital simulator.

Application of Cooperative Control to Petroleum Plants Using Fuzzy Supervisory Control and Model Predictive Multi-variable Control

2001 ◽  
Vol 5 (6) ◽  
pp. 333-337 ◽  
Author(s):  
Takahiro Kobayashi ◽  
◽  
Tetsuji Tani
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Statistical Model ◽  
Supervisory Control ◽  
Cooperative Control ◽  
Large Time ◽  
Hierarchical Control ◽  
Oil Refinery ◽  
Variable Control ◽  
Petroleum Plant

This paper describes hierarchical control with fuzzy supervisory control and model predictive multivariable control (MPC) in a petroleum plant. MPC is effective in time delay, interference, and handling constraints. Fuzzy logic controllers are effective for plants with large time delay and non-linearity. Our proposed hierarchical control combines their advantages. Fuzzy supervisory control, which determines set points for MPC, consists of an estimation block and a compensation block. We use a statistical model with multi-regression analysis for the estimation block to estimate parameters of plant operation, and fuzzy logic for the compensation block to correct output of the statistical model. Hierarchical control has been applied to an actual plant in an oil refinery, and showed satisfactory performance.

scholarly journals A Robust Fuzzy Logic Controller Design for Load Frequency Control of Hydro Thermal Power Generating Stations

2020 ◽  
Vol 9 (4) ◽  
pp. 997-1002
Keyword(s):  
Fuzzy Logic ◽  
System Parameter ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Thermal Power ◽  
Pi Controller ◽  
Load Frequency Control ◽  
Thermal System ◽  
Parameter Change ◽  
Tie Line

This article analyses the contribution of Fuzzy logic controller in a two source two area hydro thermal system aimed at load frequency control of the system. The proposed two area two source hydro thermal system is observed for different system parameter change to realize the dynamic behavior of frequency along with the interchanged power through tie line. To begin with, hydro and thermal power plants in a single control area for a step load variation is reviewed and the results for PI along with fuzzy logic controller are compared. Additionally a two source two area system is considered and the frequency and tie line power deviation with fuzzy logic controller is matched with results of PI controller. To witness the superiority of fuzzy logic controller, the connected generating system is run for different system parameter change. Simulation outcomes revealed that the recommended fuzzy logic controller put in enhanced output response when compared with conventional PI controller. The offsets found with the conventional controller can be estimably fell off with the suggested fuzzy logic controller.

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