Abstract: The Purdue University Research Reactor-1 (PUR-1) is a 10 kWth pool-type research reactor located at Purdue University’s West Lafayette campus. The reactor was recently upgraded to use entirely digital instrumentation and control systems. However, currently, there is no automated control system to regulate the power in the reactor. We propose a fuzzy logic controller as a form of digital twin to complement the existing digital instrumentation system to monitor and stabilize power control using existing experimental data. This work assesses the feasibility of a power controller based on a Fuzzy Rule-Based System (FRBS) by modelling and simulation with a MATLAB algorithm. The controller uses power error and reactor period as inputs and generates reactivity insertion as output. The reactivity insertion is then converted to control rod height using a logistic function based on information from the recorded experimental reactor control rod data. To test the capability of the proposed fuzzy controller, a point-kinetic reactor model is utilized based on the actual PUR-1 operation conditions and a Monte Carlo N-Particle simulation result of the core to numerically compute the neutronics parameters of reactor behavior. The Point Kinetic Equation (PKE) was employed to model dynamic characteristics of the research reactor since it explains the interactions between the spatial and time varying input and output variables efficiently. The controller is demonstrated computationally using various cases: startup, power maneuver, and shutdown. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the reactor power to follow demand power without compromising nuclear safety measures.
Abstract: Today, the treatment of cancer, in a relatively short
period, with minimum adverse effects is a great concern for
oncologists. In this paper, based on a recently used mathematical
model for cancer, a guideline has been proposed for the amount
and duration of drug doses for cancer treatment by immunotherapy.
Dynamically speaking, the mathematical ordinary differential
equation (ODE) model of cancer has different equilibrium points;
one of them is unstable, which is called the no tumor equilibrium
point. In this paper, based on the number of tumor cells an
intelligent soft computing controller (a combination of fuzzy logic
controller and genetic algorithm), decides regarding the amount
and duration of drug doses, to eliminate the tumor cells and
stabilize the unstable point in a relatively short time. Two different
immunotherapy approaches; active and adoptive, have been studied
and presented. It is shown that the rate of decay of tumor cells is
faster and the doses of drug are lower in comparison with the result
of some other literatures. It is also shown that the period of
treatment and the doses of drug in adoptive immunotherapy are
significantly less than the active method. A recommendation to
oncologists has also been presented.
Abstract: This paper presents a comparative study of various
controllers for the speed control of DC motor. The most commonly
used controller for the speed control of dc motor is Proportional-
Integral (P-I) controller. However, the P-I controller has some
disadvantages such as: the high starting overshoot, sensitivity to
controller gains and sluggish response due to sudden disturbance. So,
the relatively new Integral-Proportional (I-P) controller is proposed to
overcome the disadvantages of the P-I controller. Further, two Fuzzy
logic based controllers namely; Fuzzy control and Neuro-fuzzy
control are proposed and the performance these controllers are
compared with both P-I and I-P controllers. Simulation results are
presented and analyzed for all the controllers. It is observed that
fuzzy logic based controllers give better responses than the traditional
P-I as well as I-P controller for the speed control of dc motor drives.
Abstract: On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.
Abstract: This paper considers an H∞ TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an H∞ TS fuzzy state-derivative feedback control law which guarantees L2-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and H∞ performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller.
Abstract: A microcontroller-based fan coil unit (FCU) fuzzy controller is designed and implemented in this paper. The controller employs the concept of duty ratio on the electric valve control, which could make full use of the cooling and dehumidifying capacity of the FCU when the valve is off. The traditional control method and its limitations are analyzed. The hardware and software design processes are introduced in detail. The experimental results show that the proposed method is more energy efficient compared to the traditional controlling strategy. Furthermore, a more comfortable room condition could be achieved by the proposed method. The proposed low-cost FCU fuzzy controller deserves to be widely used in engineering applications.
Abstract: Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H2S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. New design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.
Abstract: This paper describes a simple way to control the speed
of PMBLDC motor using Fuzzy logic control method. In the
conventional PI controller the performance of the motor system is
simulated and the speed is regulated by using PI controller. These
methods used to improve the performance of PMSM drives, but in
some cases at different operating conditions when the dynamics of
the system also vary over time and it can change the reference speed,
parameter variations and the load disturbance. The simulation is
powered with the MATLAB program to get a reliable and flexible
simulation. In order to highlight the effectiveness of the speed control
method the FLC method is used. The proposed method targeted in
achieving the improved dynamic performance and avoids the
variations of the motor drive. This drive has high accuracy, robust
operation from near zero to high speed. The effectiveness and
flexibility of the individual techniques of the speed control method
will be thoroughly discussed for merits and demerits and finally
verified through simulation and experimental results for comparative
analysis.
Abstract: The growth in the demand of electrical energy is
leading to load on the Power system which increases the occurrence
of frequent oscillations in the system. The reason for the oscillations
is due to the lack of damping torque which is required to dominate
the disturbances of Power system. By using FACT devices, such as
Unified Power Flow Controller (UPFC) can control power flow,
reduce sub-synchronous resonances and increase transient stability.
Hence, UPFC is used to damp the oscillations occurred in Power
system. This research focuses on adapting the neuro fuzzy controller
for the UPFC design by connecting the infinite bus (SMIB - Single
machine Infinite Bus) to a linearized model of synchronous machine
(Heffron-Phillips) in the power system. This model gains the
capability to improve the transient stability and to damp the
oscillations of the system.
Abstract: Hybrid electric vehicles can reduce pollution and
improve fuel economy. Power-split hybrid electric vehicles (HEVs)
provide two power paths between the internal combustion engine
(ICE) and energy storage system (ESS) through the gears of an
electrically variable transmission (EVT). EVT allows ICE to operate
independently from vehicle speed all the time. Therefore, the ICE can
operate in the efficient region of its characteristic brake specific fuel
consumption (BSFC) map. The two-mode powertrain can operate in
input-split or compound-split EVT modes and in four different fixed
gear configurations. Power-split architecture is advantageous because
it combines conventional series and parallel power paths. This
research focuses on input-split and compound-split modes in the
two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an
internal combustion engine (ICE) and PI control for electric machines
(EMs) are derived for the urban driving cycle simulation. These
control algorithms reduce vehicle fuel consumption and improve ICE
efficiency while maintaining the state of charge (SOC) of the energy
storage system in an efficient range.
Abstract: This article presents two methods for the
compensation of harmonics generated by a nonlinear load. The first is
the classic method P-Q. The second is the controller by modern
method of artificial intelligence specifically fuzzy logic. Both
methods are applied to a shunt Active Power Filter (sAPF) based on a
three-phase voltage converter at five levels NPC topology. In
calculating the harmonic currents of reference, we use the algorithm
P-Q and pulse generation, we use the intersective PWM. For
flexibility and dynamics, we use fuzzy logic. The results give us clear
that the rate of Harmonic Distortion issued by fuzzy logic is better
than P-Q.
Abstract: In this paper, we discuss the performance of applying
hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation
algorithm on an intelligent controller for a differential drive robot. A
unicycle class of differential drive robot is utilised to serve as a basis
application to evaluate the performance of the HSDBC algorithm. A
hybrid fuzzy logic controller is developed and implemented for the
unicycle robot to follow a predefined trajectory. Trajectories of
various frictional profiles and levels were simulated to evaluate the
performance of the robot at different operating conditions. Controller
gains and scaling factors were optimised using HSDBC and the
performance is evaluated in comparison to previously adopted
optimisation algorithms. The HSDBC has proven its feasibility in
achieving a faster convergence toward the optimal gains and resulted
in a superior performance.
Abstract: Diabetes is a growing health problem in worldwide.
Especially, the patients with Type 1 diabetes need strict glycemic
control because they have deficiency of insulin production. This
paper attempts to control blood glucose based on body mathematical
body model. The Bergman minimal mathematical model is used to
develop the nonlinear controller. A novel back-stepping based sliding
mode control (B-SMC) strategy is proposed as a solution that
guarantees practical tracking of a desired glucose concentration. In
order to show the performance of the proposed design, it is compared
with conventional linear and fuzzy controllers which have been done
in previous researches. The numerical simulation result shows the
advantages of sliding mode back stepping controller design to linear
and fuzzy controllers.
Abstract: Semi-active Fuzzy control of quarter car system having three degrees of freedom and assembled with magneto-rheological (MR) shock absorber is studied in present paper. First, experimental work was performed on an MR shock absorber under different excitation conditions to obtain force-displacement and force-velocity curves. Then, for the application of experimental data in semi-active quarter car system, a polynomial model was selected. Finally, Fuzzy logic controller was designed having the combination of Forward fuzzy controller and Inverse fuzzy controller for integration in secondary suspension system of concerned model. The proposed controlled quarter car model was compared with uncontrolled system using simulation work under bump type of road excitation. Results obtained by simulation work shows the effectiveness of fuzzy controlled suspension system in improving the ride comfort and safety of travelling passengers compared to uncontrolled suspension system.
Abstract: In an interconnected power system, any sudden small
load perturbation in any of the interconnected areas causes the
deviation of the area frequencies, the tie line power and voltage
deviation at the generator terminals. This paper deals with the study
of performance of intelligent Fuzzy Logic controllers coupled with
Conventional Controllers (PI and PID) for Load Frequency Control.
For analysis, an isolated single area and interconnected two area
thermal power systems with and without generation rate constraints
(GRC) have been considered. The studies have been performed with
conventional PI and PID controllers and their performance has been
compared with intelligent fuzzy controllers. It can be demonstrated
that these controllers can successfully bring back the excursions in
area frequencies and tie line powers within acceptable limits in
smaller time periods and with lesser transients as compared to the
performance of conventional controllers under same load disturbance
conditions. The simulations in MATLAB have been used for
comparative studies.
Abstract: This paper presents an intention interface and controller for a wire-driven heavy object lifting system that assists the operator with moving a heavy object. The handler is designed to allow a comfortable working posture for the operator. Plus, as a human assistive system, the operator is involved in the control loop, where a fuzzy control system is used to consider the human control characteristics. The effectiveness and performance of the proposed system are proved by experiments.
Abstract: This paper is based on the bridgeless single-phase Ac–Dc Power Factor Correction (PFC) converters with Fuzzy Logic Controller. High frequency isolated Cuk converters are used as a modular dc-dc converter in Discontinuous Conduction Mode (DCM) of operation of Power Factor Correction. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the Membership Functions (MFs) and to improve the efficiency and to eliminate the power quality problems. The output of Fuzzy controller is compared with High frequency triangular wave to generate PWM gating signals of Cuk converter. The proposed topologies are designed to work in Discontinuous Conduction Mode (DCM) to achieve a unity power factor and low total harmonic distortion of the input current. The Fuzzy Logic Controller gives additional advantages such as accurate result, uncertainty and imprecision and automatic control circuitry. Performance comparisons between the proposed and conventional controllers and circuits are performed based on circuit simulations.
Abstract: This paper demonstrates the potential of applying PD-like fuzzy logic controller for active vibration control of piezoelectric Stewart platforms. Through simulation, the control authority of the piezo stack actuators for effectively damping the Stewart platform vibration can be evaluated for further implementation of the system. Each leg of the piezoelectric Stewart platform consists of a linear piezo stack actuator, a collocated velocity sensor, a collocated displacement sensor and flexible tips for the connections with the two end plates. The piezoelectric stack is modeled as a bar element and the electro-mechanical coupling property is simulated using Matlab/Simulink software. Then, the open loop and closed loop dynamic responses are performed for the system to characterize the effect of the control on the vibration of the piezoelectric Stewart platform. A significant improvement in the damping of the structure can be observed by using the PD-like fuzzy controller.
Abstract: The controller is used to improve the dynamic performance of DC-DC converter by achieving a robust output voltage against load disturbances. This paper presents the performance of PI and Fuzzy controller for a phase- shifted zero-voltage switched full-bridge PWM (ZVS FB- PWM) converters with a closed loop control. The proposed converter is regulated with minimum overshoot and good stability. In this paper phase-shift control method is used as an effective tool to reduce switching losses and duty cycle losses. A 1kW/100KHz dc/dc converter is simulated and analyzed using MATLAB. The circuit is simulated for static and dynamic load (DC motor). It has been observed that performance of converter with fuzzy controller is better than that of PI controller. An efficiency comparison of the converter with a reported topology has also been carried out.
Abstract: Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.
To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.
It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.