Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : PID controller


Simulation Model of Al-Dura Electro-station Plant of 160 MW with Genetic Algorithm Method

Shaker H.Aljanabi; Alaa Siham Hamid

Engineering and Technology Journal, 2016, Volume 34, Issue 11, Pages 1928-1943

In the present paper, a thermodynamic analysis of Al-Dura, Baghdad station type (K– 160–13.34–0.0068), power plant has been carried out. The power plant system was simulated and a detailed parametric study undertaken. This study can be helpful to identify the plant site conditions that cause losses of useful energy taken place and also helpful to resolve some problems encountered in steam turbine, capacity unit. Developing nonlinear mathematical models based on system identification approaches during normal operation without any external excitation or disruption is always a hard effort, assuming that parametric models are available. This study included on using soft computing methods that would be helpful in order to adjust model parameters over full range of input–output operational data. In this case, the model parameters are adjusted by applying genetic algorithms as optimization methods. Comparison between the responses of the turbine – generator model with the responses of real system validates the accuracy of the proposed model in steady state and transient conditions. Simulation results shows that the efficiencies and feasibility of the developed model in term of more accurate and less deviation with the responses of read system in the steady and transient conditions, and the error of proposed function is less than 0.37%. This study presents the usage of the Cycle – tempo and Matlab/Simulink package to implement the model of the power plant. Finally, many recommendations have been suggested for improved plant performance.

Study the Robustness of Automatic Voltage Regulator for Synchronous Generator Based on Neuro-Fuzzy Network

Abdulrahim Thiab Humod; Yasir Thaier Haider

Engineering and Technology Journal, 2015, Volume 33, Issue 3, Pages 612-627

Modern power systems are complex and non-li¬near and their operating conditions can vary over a wide range, and since neuro - fuzzy networkcan be used as intelligent controllers to control non-li¬near dynamic systems through learning, which can easily accommodate the non-linearity, time dependencies, model uncertainty and external disturbances.ANeuro-Fuzzy model system is proposed as an effective neural network controller model to achieve the desired robust Automatic Voltage Regulator (AVR) for Synchronous Generator (SG) to maintain constant terminal voltage. TheconcernedNeuro-fuzzy controller for AVRis examined on different models of SG andloads. The results show that the Neuro-Fuzzy -controllers have excellent responses for all SG models and loads in the view point of transientresponse and system stability compared with optimal PID controllers tuned by practical swarm optimization.They also show that the margins of robustness for Neuro-Fuzzy -controller aregreater thanPID controller.

Comparative Study of Temperature Control in a Heat Exchanger Process

Afraa H. Al-Tae; Safa A. Al-Naimi

Engineering and Technology Journal, 2012, Volume 30, Issue 10, Pages 1707-1731

In the present work the dynamic behavior of a plate heat exchanger (PHE)
(single pass counter current consists of 24 plates) studied experimentally and
theoretically to control the system. Different control strategies; conventional
feedback control, classical fuzzy logic control, artificial neural network (NARMAL2)
control and PID fuzzy logic control were implemented to control the outlet
cold water temperature. A step change was carried in the hot water flow rate which
was considered as a manipulated variable. The experimental heat transfer
measurements of the PHE showed that the overall heat transfer coefficient (U) is
related to the hot water flow rate (mh) by a correlation having the form:
U mh
0.7158 =11045
In this work the PHE model was found theoretically as a first order lead and
second order overdamped lag while the experimental PHE represented dynamically
(by PRC method) as a first order with negligible dead time value. A comparison
between the experimental and the theoretical model is carried out and good
agreement is obtained. The performance criteria used for different control modes
are the integral square error (ISE) and integral time-weighted absolute error (ITAE)
where the ITAE gave better performance. As well as the parameters of the step
performance of the system such as overshoot value, settling time and rise time are
used to evaluate the performance of different control strategies. The PID fuzzy
controller gave better control results of temperature rather than PI, PID and
artificial neural network controller since PID fuzzy controller combines the
advantages of a fuzzy logic controller and a PID controller. MATLAB program
version 7.10 was used as a tool of simulation for all the studies mentioned in this
work.

Excitation Control of Synchronous Generator Via Neural Network Based Controllers

Ekhlas M. Thajeel

Engineering and Technology Journal, 2012, Volume 30, Issue 3, Pages 378-397

Modern power systems are complex and non-linear and their operating can vary
over a wide range. This paper presents a linear mathematical model of the
synchronous generator to control the excitation system based on Neural Network to
simulate an Automatic Voltage Regulator. The voltage regulator is used to modify
terminal voltage for the purpose of tracking a reference voltage and comparative with
PID controller. ANN (NARMA-L2) system is proposed as an effective controller
model to achieve the desired enhancement. This model after training can be called as
(Identifier).The proposed technique is evaluated on a single machine infinite bus
under different operating conditions (no-load and full load condition) by using
MATLAB simulink software.

Neural Network-Based Robust Automatic Voltage Regulator (AVR) of Synchronous Generator

Abdullah Sahib Abdulsada; Abdulrahim Thiab Humod

Engineering and Technology Journal, 2011, Volume 29, Issue 7, Pages 1372-1385

The voltage stability and power quality of the electrical system depend on proper operation of AVR. Nowadays, Design technology of AVR is being broadly improved.
Nonlinearities and parametric uncertainties are unavoidable problem faced in
controlling the output voltage of Synchronous Generator (SG) when working alone or with others. This paper proposes a Nonlinear Auto Regressive-Moving Average control (NARMA-L2) as a voltage controller which is one type of Neural Network (NN) plant structure. Nonlinearities due to the effect of saturation in machine between generated voltage and field current, uncertainties arise because variation of the load connected with time and the change of rotors resistance with temperature. Due to this fact, Proportional- Integral- Derivative (PID) controller cannot be used effectively since it is developed based on linear system theory. NN controller shows less over shoot and settling time than PID controller with different conditions of load. Also NN controller shows high robust characteristic than PID controller.

Smith Predictor with Simple Control Scheme for Higher Order Systems

Qussay S.Tawfeeq; Nasir.A.Al-awad; Ekhlas H. Karam

Engineering and Technology Journal, 2011, Volume 29, Issue 3, Pages 579-594

A simple control scheme with smith predictor connection is proposed in
this paper for time delay higher order systems. The control scheme is
simply integral (I) controller with Proportional Derivative(PD)-Sliding
mode controller(SMC). The initial values for the P,I, and D parameters are
taken from the reduced model of the higher order system. Additional
feedback sliding mode control (FSMC) is also used to reduce the effect of
uncertainty in the prediction time delay values. A number of examples are
tested and compared with other control methods like robust PID controller
with smith predictor and Direct synthesis method with smith predictor to
illustrate the efficient performance for the proposed control scheme.

Excitation and Governing Control of a Power Generation Based Intelligent System

Adil H. Ahmad; Lina J. Rashad

Engineering and Technology Journal, 2010, Volume 28, Issue 5, Pages 871-889

Modern power systems are complex and non-linear and their operating conditions
can vary over a wide range. In this work, the power system (PS) transient terminal
voltage and frequency stability enhancement have been well investigated and studied
through the following efforts.
• Enhancing the responses of the transient stability by adopting conventional PID
controllers as an additional voltage controller with the Automatic Voltage Regulator
(AVR) in the excitation system for terminal voltage, and in the governing system for
frequency deviation response.
• ANN (NARMA-L2) system is proposed as an effective controller model to achieve the
desired enhancement. This model after training can be called as (Identifier). This
identifier follows the system behavior even in situation of high disturbances.
There are enhancement progress in terminal voltage Vt , and frequency deviation Δω
through the investigation for the three cases (without controller, with PID controller, and
with NN controller) for single machine infinite bus using MATLAB – Simulink software.

Speed Control of Hydraulic Motor System with Swashplate DC-Controlled Pump

Majid A. Oleiwi; Amjed J. Humaidi

Engineering and Technology Journal, 2009, Volume 27, Issue 15, Pages 2814-2834

In a previous study, speed-controlled hydraulic motor system has
employed a DC motor for changing the swashplate angle of a variable
displacement piston pump. However, the speed control has been performed by a flow modulation valve which is permitted to bypassing the flow of the hydraulic motor when the speed exceeds the set value. In the present work, another speed control configuration has been proposed with the pump and hydraulic motor are permitted to perform reversal actions. The conventional proportional, integral and derivative (PID) controller has been introduced to manipulate the speed error such
that it could achieve the required performance. The specification required by the PID controller is to reach the command speed as fast as possible with minimum peak overshoot. Also, the effectiveness of the suggested controller against changing of system parameters is considered. The modeling of the speed control system components is detailedly presented, including the dynamic of swashplate,
and one can easily see that the system is of a nonlinear nature. The state space representation of the complete system has been developed and the program codes are listed inside an m-file, which is instantaneously called by an s-function within SIMULINK library.