الفهرس 
EXPERIMENTAL SETUP AND SYSTEM IDENTIFICATIONOnly 14 pages are availabe for public view
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Abstract
The speed control of induction motor (IM) drives is a very important
research topic for many industrial applications. In practice, IM drives are
applied and coupled to external mechanical systems to deliver the mechanical
energy required for the operation. The mechanical system, in this context, is the
uncertain polymer extruder system. It is maybe considered a non-positive
pump. In general, the main function of a polymer extruder is the continuous
feeding of a high-quality melt output maintaining desired and consistent
temperature, pressure, and flow rate. To achieve this function, it is required to
effectively manipulate the barrel zone temperatures and the rotating screw
speed. Currently, many polymer extruders are equipped with V/f controlled IM
drives due to their valuable advantages of easy implementation and low cost.
Hence, having accurate speed control of the V/f controlled IM drive applied to
the rotating screw is highly required to accomplish stable operation and highquality products. The challenge is to consider variability, nonlinearity, and
uncertainty of material, machine, and process variables, which strongly
influence the performance of the IM drive.
Given the lack of research regarding speed control approaches for V/f
controlled IM drives applied to uncertain and perturbed systems, this study
aims to develop and validate effective robust, adaptive and intelligent-based
speed control approaches for V/f controlled three-phase squirrel cage IM drive
applied to polymer extruder system. The proposed control approaches combine
features of both fuzzy logic control (FLC) and the robust sliding mode control
(SMC) structures to overcome the aforementioned challenges. The main
objectives are ensuring stable and accurate tracking performance of the V/f
controlled IM drive in the presence of high uncertainty due to modeling errors,
parametric variations, and external disturbances. Second, improving the
performance in terms of tracking accuracy and dynamic response. Finally,
extending the applicability to applications where accurate speed control and
moderate dynamic response are required.II
In this study two intelligent-based control approaches on basis of a
robust SMC approach are proposed and validated. The first proposed controller
is the fuzzy SMC (FSMC), which is developed to overcome the chattering
problem of the conventional SMC. A fuzzy inference system (FIS) is
developed to replace the discontinuous sign function and it acts like a weighing
function to reduce the constant and large reaching control gain. However, the
control design of FSMC causes undesired overshooting and requires the bound
of uncertainties and the parameters of the nominal dynamic model to compute
the equivalent control.
The second proposed controller is the model-free adaptive gain FSMC,
which can eliminate the chattering and it can avoid the requirements of the
mathematical modeling of the real system and the knowledge of the upper
bounds of the uncertainties in advance. Besides the high performance of the
proposed control approach, it has simple structure, easy to implement, and low
cost. For the proposed control approach, an improved FIS is developed to
minimize the number of fuzzy rules. Second, a new fuzzy-based adaptation law
is developed using the improved FIS to estimate the adaptive reaching control
gain such that the sliding mode exists. Third, and finally, the equivalent control
part is approximated to avoid the requirement of the mathematical model.
The asymptotic stability and convergence of the proposed control
approaches are proved using the Lyapunov stability method. Second, the
proposed controllers are implemented practically using (Arduino Due)
embedded system, and then it is realized and tested in real-time using the
experimental setup. Third, the experimental results are analyzed using
statistical methods, specifically, MAE, MAPE, and RMSE. Finally, the
statistical quantitative comparison between the proposed controllers, secondorder SMC, and the conventional PID controller is presented. The experimental
and statistical results show and verify the good performance of the proposed
controllers in presence of uncertainties.