الفهرس 
Chapter (1) INTRODUCTION AND LITERATURE REVIEWOnly 14 pages are availabe for public view
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Abstract
The elastic coupled multi-motor systems (ECMMS), and the elastic coupled twomass
systems (ECTMS), elastic coupled multi-mass systems are common examples of
the nonlinear, multi-input / multi-output (MIMO) complicated systems used in
industry. In such system mechanical vibrations are resulted due to mechanical
coupling through shafts which are coupling among multi-motors and single or multiloads
of the system. One source of nonlinearity in such type of systems is mechanical
coulomb friction which may be associated to the operation of ECMMS or ECTMS.
Another source of nonlinearity is the limitations of electrical or mechanical actuators.
Also, the backlash in the gear box coupling the motor shaft to the load is another
source of nonlinearity.
Moreover, the torsional oscillations and torsional resonance which can arise
within the MMS can cause various damages in the system. The source of such
torsional oscillations is the elastic long and / or short shafts of the mechanically
coupled motors and the rotating large or variable inertias included in the system. So,
this thesis presents proposed control algorithms in order to equalize against or reduce
the resulted damaging resonance oscillation by designing a decentralized control
system for speed control of the multi-mass systems (MMS).
The core controllers employed in the proposed decentralized control system is the
self-adaptive, intelligent, and simple structure proportional, integral, and derivative
(PID) controllers. The thesis presents a proposed algorithm to auto-tune the parameters
of the included PID controllers. The proposed algorithm depends on searching a whole
defined space of the control parameters in order to acquire the best values for optimum
control effect and maintain better performance index as possible.
One of the algorithms is off-line; it is applied on the model of the ECMMS
system. The main objective is to perform a searching mechanism in the predefined
subspace of the entire space of controller parameters and computing the cost function
for each vector of experienced parameters. The final emerged output of the algorithm
is to deliver the vector of controller parameters for which the value of
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the is minimized, over the total period of operation. The values of the cost function
obtained for each subspace are collected in a table to be compared and, then to get the
optimal values of the controller parameters over the entire space.
This off-line algorithm is modified to the optimal parameters of controller
parameter vector depending on the initial value of the error at the start of system
excitation or re-excitation, the controller parameters are clustered in a reference table.
The reference table is passed to be employed by one of the proposed practical
algorithms to be referenced automatically for the optimal parameters depending on the
measured values of the reference and the actual variable of the system.
Two additional proposed practical algorithms which are intelligent and selfadaptive
are presented through this thesis, with the practical results obtained from their
application on the system. These algorithms combine altogether the advantages of
using the common used PID and the intelligent neural network based controller (neuro
-controller) or (NC). An additional algorithm of adaptation of an important parameter
of the employed (NC) is applied practically to improve the transient and the steady
state response of the system. The adapted parameter is the learning factor of the NC.
The proposed adaptation algorithm is based on Lyapunov stability analysis in order to
guarantee bounded characteristic of system response.
The results emerged from adopting the proposed control techniques either the
simulation or the practical results have supported each other towards the success to
suppress the evolution of oscillatory frequencies and mechanical vibration modes. The
results also supported the capability of the proposed control algorithms to effectively
compensate against the load disturbances which are introduced to the related ECMMs.
Although the results provided are better for some techniques rather the others, but all
of those proposed techniques won to restrict the effect of mechanical elasticity and
stiffness on the ECMMS. The proposed techniques have shared the common
characteristic of having simpler structure, processed rapidly to conform to the short
time constant motors of ECMMS.