My research interests span broad areas of control theory and dynamic systems. I am an
interdisciplinary system researcher with academic and industrial training in both
electrical and mechanical engineering disciplines. My research includes
mathematical analysis as well as experimental methods. I am primarily
interested in working on existing and emerging problems related to sustainable energy
systems [4-8]. Also, I am enthusiastic about electric machine theory and servo-system
design and improvement [2,3,7,10,11]. My recent work includes design and implementation of
high-precision contouring of servo-systems , and theoretical development of modular
control design over networks [1, 2]. My future research plans are directed toward
achieving accessible economic renewable energy and distributed manufacturing.
Control and Optimization
Component swapping modularity is a recently
proposed concept in control networks
to guarantee desired closed-loop performance using low-order modular controllers for smart
components. Conventionally, complete control redesign is inevitable when swapping a
system's component with a dynamically different counterpart. However, our proposed
algorithm achieves desired closed-loop performance only by tuning the low-order controller
of the swapped component. The major part of the control remains unchanged for all the
variants of the swappable component. The proposed algorithm dramatically simplifies
control design and reduces calibration time and effort, particularly, in applications
from automotive industry and power networks [1,2].
Multivariable Newton-based extremum seeking (ES)
extends the conventional
gradient-based ES designs so uniform transients are achieved for all channels of a
multivariable optimization problem. The proposed design governs the system to its optimal
point on a straight path so control effort is also minimized. The Newton-based ES is
robust under external disturbances or model uncertainties. Moreover, ES algorithms in
general, and the Newton-based design specifically, are real-time continuous and do not
require processing units which further simplifies algorithm implementation and reduces
manufacturing and maintenance cost .
Aggregate modeling and control of thermostatically
controlled loads (TCLs) provides a
promising avenue to improve energy efficiency and the stability margin of power networks.
We proposed a novel analytical model for a large population of heterogeneous heating/cooling
units. As shown in Fig. 1(c), averaged accumulated error of the model is less than 0.3%.
Simple and yet effective power control algorithms were designed using the proposed model.
Our model is beneficial to utility managers as well as the end-user to increase power
efficiency and reduce energy cost . We designed and
installed a wireless sensor network, illustrated in Fig. 1(a), to verify the effectiveness
of our proposed model, experimentally.
Power optimization of photovoltaic (PV) energy
generators are essential to fully exploit
PV power resources. The proposed algorithm is non-model-based, and hence can be
applied to different PV systems with minimal redesign. It offers the advantages
of fast convergence and guaranteed stability over a wide range of environmental conditions,
and yet is simple and cost effective to implement. Thus, power efficiency is increased and
energy cost is reduced [5,6
Nonlinear control and power optimization of wind energy
conversion systems (WECS) guarantees maximum
feasible wind power extraction under fast changing wind speeds. We use a nonlinear
controller, based on the field-oriented control concept and feedback linearization, to
achieve instantaneous wind power tracking. Extremum seeking maintains wind turbine energy
yield at its feasible peak and also improves system robustness versus dynamic disturbances.
Thus, higher power efficiency is achieved and ultimately energy cost is reduced
Mechatronics and Manufacturing Systems
High-precision contour error estimation and contouring
algorithms improve the
accuracy of machine tools, defined using unmeasurable contour error which equals the
shortest distance from actual position to the reference contour. Hence, we proposed a
precise dynamic contour error estimate (CEE) and a novel integrated contouring algorithm to
govern the contour error of a wide range of reference feedrates to zero. Our experiments
showed as much as 50% reduction in contour error for highly curved fast references
Robust nonlinear control of flexible-link
robots comprises a modified sliding mode
control using global stabilization and nonlinear optimization. The proposed algorithm
constructed based on the sliding mode control because the flexible-link nominal model has
order uncertainty and is sensitive to external load disturbances. The research was
conducted to exploit benefits of high-order switching surfaces to improve closed-loop
system performance of a sliding mode control designed based on a low order nominal model
of the flexible-link [10,11].
A. Ghaffari and A. G. Ulsoy, Swapping modularity for distributed precision contouring;
analysis and experiments, ASME Journal of Dynamic Systems, Measurement, and Control, Submitted.
A. Ghaffari and A. G. Ulsoy, LMI-based design of distributed controllers to achieve component
swapping modularity, IEEE Transactions on Control Systems Technology, Submitted.