Abstract: The approach proposed here is oriented in the direction of fuzzy system for the analysis and the synthesis of intelligent climate controllers, the simulation of the internal climate of the greenhouse is achieved by a linear model whose coefficients are obtained by identification. The use of fuzzy logic controllers for the regulation of climate variables represents a powerful way to minimize the energy cost. Strategies of reduction and optimization are adopted to facilitate the tuning and to reduce the complexity of the controller.
Abstract: The interline power flow controller (IPFC) is one of
the latest generation flexible AC transmission systems (FACTS)
controller used to control power flows of multiple transmission lines.
This paper presents a mathematical model of IPFC, termed as power
injection model (PIM). This model is incorporated in Newton-
Raphson (NR) power flow algorithm to study the power flow control
in transmission lines in which IPFC is placed. A program in
MATLAB has been written in order to extend conventional NR
algorithm based on this model. Numerical results are carried out on a
standard 2 machine 5 bus system. The results without and with IPFC
are compared in terms of voltages, active and reactive power flows to
demonstrate the performance of the IPFC model.
Abstract: This paper presents the DC voltage control design of D-STATCOM when the D-STATCOM is used for load voltage regulation. Although, the DC voltage can be controlled by active current of the D-STATCOM, reactive current still affects the DC voltage. To eliminate this effect, the control strategy with elimination effect of the reactive current is proposed and the results of the control with and without the elimination the effect of the reactive current are compared. For obtaining the proportional and integral gains of the PI controllers, the symmetrical optimum and genetic algorithms methods are applied. The stability margin of these methods are obtained and discussed in detail. In addition, the performance of the DC voltage control based on symmetrical optimum and genetic algorithms methods are compared. Effectiveness of the controllers designed was verified through computer simulation performed by using Power System Tool Block (PSB) in SIMULINK/MATLAB. The simulation results demonstrated that the DC voltage control proposed is effective in regulating DC voltage when the DSTATCOM is used for load voltage regulation.
Abstract: In this paper we consider a nonlinear feedback control
called augmented automatic choosing control (AACC) using the
gradient optimization automatic choosing functions for nonlinear
systems. Constant terms which arise from sectionwise linearization
of a given nonlinear system are treated as coefficients of a stable
zero dynamics. Parameters included in the control are suboptimally
selected by expanding a stable region in the sense of Lyapunov
with the aid of the genetic algorithm. This approach is applied to
a field excitation control problem of power system to demonstrate
the splendidness of the AACC. Simulation results show that the new
controller can improve performance remarkably well.
Abstract: In this paper the performance of unified power flow
controller is investigated in controlling the flow of po wer over the
transmission line. Voltage sources model is utilized to study the
behaviour of the UPFC in regulating the active, reactive power and
voltage profile. This model is incorporated in Newton Raphson
algorithm for load flow studies. Simultaneous method is employed
in which equations of UPFC and the power balance equations of
network are combined in to one set of non-linear algebraic equations.
It is solved according to the Newton raphson algorithm. Case studies
are carried on standard 5 bus network. Simulation is done in Matlab.
The result of network with and without using UPFC are compared in
terms of active and reactive power flows in the line and active and
reactive power flows at the bus to analyze the performance of UPFC.
Abstract: The steady-state operation of maintaining voltage
stability is done by switching various controllers scattered all over
the power network. When a contingency occurs, whether forced or
unforced, the dispatcher is to alleviate the problem in a minimum
time, cost, and effort. Persistent problem may lead to blackout. The
dispatcher is to have the appropriate switching of controllers in terms
of type, location, and size to remove the contingency and maintain
voltage stability. Wrong switching may worsen the problem and that
may lead to blackout. This work proposed and used a Fuzzy CMeans
Clustering (FCMC) to assist the dispatcher in the decision
making. The FCMC is used in the static voltage stability to map
instantaneously a contingency to a set of controllers where the types,
locations, and amount of switching are induced.
Abstract: This paper presents preliminary results on modeling
and control of a quadrotor UAV. With aerodynamic concepts, a
mathematical model is firstly proposed to describe the dynamics
of the quadrotor UAV. Parameters of this model are identified by
experiments with Matlab Identify Toolbox. A group of PID controllers
are then designed based on the developed model. To verify
the developed model and controllers, simulations and experiments for
altitude control, position control and trajectory tracking are carried
out. The results show that the quadrotor UAV well follows the
referenced commands, which clearly demonstrates the effectiveness
of the proposed approach.
Abstract: Model Predictive Control (MPC) is increasingly being
proposed for real time applications and embedded systems. However
comparing to PID controller, the implementation of the MPC in
miniaturized devices like Field Programmable Gate Arrays (FPGA)
and microcontrollers has historically been very small scale due to its
complexity in implementation and its computation time requirement.
At the same time, such embedded technologies have become an
enabler for future manufacturing enterprises as well as a transformer
of organizations and markets. Recently, advances in microelectronics
and software allow such technique to be implemented in embedded
systems. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and
applied control technique in the industrial engineering. In fact in
this paper, we propose an efficient framework for implementation
of Generalized Predictive Control (GPC) in the performed STM32
microcontroller. The STM32 keil starter kit based on a JTAG interface
and the STM32 board was used to implement the proposed GPC
firmware. Besides the GPC, the PID anti windup algorithm was
also implemented using Keil development tools designed for ARM
processor-based microcontroller devices and working with C/Cµ
langage. A performances comparison study was done between both
firmwares. This performances study show good execution speed and
low computational burden. These results encourage to develop simple
predictive algorithms to be programmed in industrial standard hardware.
The main features of the proposed framework are illustrated
through two examples and compared with the anti windup PID
controller.
Abstract: The application of a simple microcontroller to deal
with a three variable input and a single output fuzzy logic controller,
with Proportional – Integral – Derivative (PID) response control
built-in has been tested for an automatic voltage regulator. The
fuzzifiers are based on fixed range of the variables of output voltage.
The control output is used to control the wiper motor of the auto
transformer to adjust the voltage, using fuzzy logic principles, so that
the voltage is stabilized. In this report, the author will demonstrate
how fuzzy logic might provide elegant and efficient solutions in the
design of multivariable control based on experimental results rather
than on mathematical models.
Abstract: IMCS is Integrated Monitoring and Control System for
thermal power plant. This system consists of mainly two parts; controllers and OIS (Operator Interface System). These two parts are
connected by Ethernet-based communication. The controller side of communication is managed by CNet module and OIS side is managed
by data server of OIS. CNet module sends the data of controller to data
server and receives commend data from data server. To minimizes or
balance the load of data server, this module buffers data created by controller at every cycle and send buffered data to data server on request of data server. For multiple data server, this module manages
the connection line with each data server and response for each request
from multiple data server. CNet module is included in each controller
of redundant system. When controller fail-over happens on redundant system, this module can provide data of controller to data sever
without loss. This paper presents three main features – separation of get task, usage of ring buffer and monitoring communication status –of CNet module to carry out these functions.
Abstract: This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.
Abstract: This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: This paper proposes a prototype of a lower-limb
rehabilitation system for recovering and strengthening patients-
injured lower limbs. The system is composed of traction motors for
each leg position, a treadmill as a walking base, tension sensors,
microcontrollers controlling motor functions and a main system with
graphic user interface. For derivation of reference or normal velocity
profiles of the body segment point, kinematic method is applied based
on the humanoid robot model using the reference joint angle data of
normal walking.
Abstract: It is well known that a linear dynamic system including
a delay will exhibit limit cycle oscillations when a bang-bang sensor
is used in the feedback loop of a PID controller. A similar behaviour
occurs when a delayed feedback signal is used to train a neural
network. This paper develops a method of predicting this behaviour
by linearizing the system, which can be shown to behave in a manner
similar to an integral controller. Using this procedure, it is possible
to predict the characteristics of the neural network driven limit cycle
to varying degrees of accuracy, depending on the information known
about the system. An application is also presented: the intelligent
control of a spark ignition engine.
Abstract: Demand of energy is increasing faster than the
generation. It leads shortage of power in all sectors of society. At
peak hours this shortage is higher. Unless we utilize energy efficient
technology, it is very difficult to minimize the shortage of energy. So
energy efficiency program and energy conservation has an important
role. Energy efficient technologies are cost intensive hence it is
always not possible to implement in country like India. In the recent
study, an educational building with operating hours from 10:00 a.m.
to 05:00 p.m. has been selected to quantify the possibility of lighting
energy conservation. As the operating hour is in daytime, integration
of daylight with artificial lighting system will definitely reduce the
lighting energy consumption. Moreover the initial investment has
been given priority and hence the existing lighting installation was
unaltered. An automatic controller has been designed which will be
operated as a function of daylight through windows and the lighting
system of the room will function accordingly. The result of the study
of integrating daylight gave quite satisfactory for visual comfort as
well as energy conservation.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.
Abstract: The object of this paper is to design and analyze a
proportional – integral (PI) control for positive output elementary
super lift Luo converter (POESLLC), which is the start-of-the-art
DC-DC converter. The positive output elementary super lift Luo
converter performs the voltage conversion from positive source
voltage to positive load voltage. This paper proposes a
development of PI control capable of providing the good static and
dynamic performance compared to proportional – integralderivative
(PID) controller. Using state space average method
derives the dynamic equations describing the positive output
elementary super lift luo converter and PI control is designed. The
simulation model of the positive output elementary super lift Luo
converter with its control circuit is implemented in
Matlab/Simulink. The PI control for positive output elementary
super lift Luo converter is tested for transient region, line changes,
load changes, steady state region and also for components
variations.
Abstract: In this paper, we present an experimental testing for
a new algorithm that determines an optimal controller-s coefficients
for output variance reduction related to Linear Time Invariant (LTI)
Systems. The algorithm features simplicity in calculation, generalization
to minimal and non-minimal phase systems, and could be
configured to achieve reference tracking as well as variance reduction
after compromising with the output variance. An experiment of DCmotor
velocity control demonstrates the application of this new
algorithm in designing the controller. The results show that the
controller achieves minimum variance and reference tracking for a
preset velocity reference relying on an identified model of the motor.
Abstract: The three-time-scale plant model of a wind power
generator, including a wind turbine, a flexible vertical shaft, a Variable
Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB)
unit and the applied wind sequence, is constructed. In order to make
the wind power generator be still able to operate as the spindle speed
exceeds its rated speed, the VIF is equipped so that the spindle speed
can be appropriately slowed down once any stronger wind field is
exerted. To prevent any potential damage due to collision by shaft
against conventional bearings, the AMB unit is proposed to regulate
the shaft position deviation. By singular perturbation order-reduction
technique, a lower-order plant model can be established for the
synthesis of feedback controller. Two major system parameter
uncertainties, an additive uncertainty and a multiplicative uncertainty,
are constituted by the wind turbine and the VIF respectively.
Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed
to account for these uncertainties and suppress the unmodeled
higher-order plant dynamics. At last, the efficacy of the FSSMC is
verified by intensive computer and experimental simulations for
regulation on position deviation of the shaft and counter-balance of
unpredictable wind disturbance.