الفهرس 
Background to research workOnly 14 pages are availabe for public view
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Abstract
Different methods are used to control first order systems with time delay. Control of process with exactly known parameters is relatively straightforward. Practically there is a parameter mismatch between the real process parameters and its modeled parameters. This mismatch causes poor response. The objective of this thesis is to study the behavior of the process with unknown parameters and how to design an estimator that has the ability to calculate the process parameters such as time delay and static gain. The proposed method has a simple structure that is based on method to estimate the plant parameters. The estimator parameters are studied in details. Several controllers can be combined with the proposed method such as PID, FUZZY, Smith Predictor. The controller parameter PID is tuned to obtain high performance .The performance and robustness of the controller are studied under uncertainty. Simulation results are provided for illustration, and show the good performance of the proposed controller scheme.
The estimation and compensation of processes with time delays have been of interest to academics for several decades. A full review of the literature for both model parameter and time delay estimation is presented. [1]
The objectives of this work are to review identification methods for processes with time delays and to develop appropriate identification and compensation strategies. The large time-varying delay systems with time-varying parameters are common in the industrial processes, and this is a difficult point of control domain [2]. A fuzzy Smith control algorithm of time-varying process based on variable time delay identification is proposed. Simulation results show that the approach is effective. A time delay may be defined as the time interval between the start of an event at one point in a system and its resulting action at another point in the system. Time delays are also known as transport lags, dead times or time lags; they arise in physical, chemical, biological and economic systems, as well as in the process of measurement and computation. A time delay also arises in signal processing applications, where a time delay is also known as a time difference of arrival (TDOA) between two signals; such a measurement arises in biomedicine, geophysics, astronomy, and telecommunications. Most of these processes can be presented as first order lag plus time delay (FOLPD). The parameters of (FOLPD) are function of the operating condition and parameters identification for the process [3].
Time delay is a common phenomenon in many industrial processes. If the time delay is larger than or equal to the main time constant, it may have a significant
effect on the performance of the control system. Many design techniques and conventional control algorithms such as Proportional Integrated Derivative (PID) cannot be directly applied to processes with a dominant time delay, especially when the time delay and other parameters of the system are unknown and vary with time. [4]
By minimizing the error between the process output and the process model output, the variable delay parameter is identified, based on the on-line parameter estimation. [5]
Different methods are applied to control the first order system plus time delay such as PID and Smith - predictor, these methods have a drawback that the control performance is sensitive to process model (time delay, and static gain) [6]. There are different adaptive methods to deal with this kind of plant whose parameters changed with time [7], such as:
1) A self-tuning controller may be designed to allow appropriate variation in the controller parameters as the process parameters vary; explicit self-tuning controllers are normally designed if the variations in the process parameters are known.
2) The controller may be designed to be robust to process parameter variations. There is a certain complete robust design strategy based on.
3) A unique Fuzzy Logic Controller (FLC) structure with an efficient realization and a small rule base that can be easily implemented in existing industrial controllers was proposed.
4) An adaptive fuzzy Smith control method is proposed to control time-varying processes with dominant and variable time delay.
5) Smith predictor (SP) is an effective method to control a process with a known and fixed time delay. But Smith predictor has an inherent drawback that its control performance is sensitive to the process model, especially to time delay.