Abstract: This paper presents design and implements a voltage
source inverter type space vector pulse width modulation (SVPWM)
for control a speed of induction motor. This scheme leads to be able
to adjust the speed of the motor by control the frequency and
amplitude of the stator voltage, the ratio of stator voltage to
frequency should be kept constant. The fuzzy logic controller is also
introduced to the system for keeping the motor speed to be constant
when the load varies. The experimental results in testing the 0.22 kW
induction motor from no-load condition to rated condition show the
effectiveness of the proposed control scheme.
Abstract: The aim of this paper is to identify an optimum
control strategy of three-phase shunt active filters to minimize the total harmonic distortion factor of the supply current. A classical PIPI cascade control solution of the output current of the active filterand the voltage across the DC capacitor based on Modulus–Optimum
criterion is taken into consideration. The control system operation
has been simulated using Matlab-Simulink environment and the results agree with the theoretical expectation. It is shown that there is
an optimum value of the DC-bus voltage which minimizes the supply current harmonic distortion factor. It corresponds to the equality of the apparent power at the output of the active filter and the apparent power across the capacitor. Finally, predicted results are verified experimentally on a MaxSine active power filter.
Abstract: This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature.
Abstract: Automotive suspension system is important part of car
comfort and safety. In this article automotive active suspension with
linear motor as actuator is designed using H-infinity control. This
paper is focused on comparison of different controller designed for
quart, half or full-car model (and always used for “full" car). Special
attention is placed on energy demand of the whole system. Each
controller configuration is simulated and then verified on the
hydraulic quarter car test bed.
Abstract: With a rapid growth in 3D graphics technology over the last few years, people are desired to see more flexible reacting motions of a biped in animations. In particular, it is impossible to anticipate all reacting motions of a biped while facing a perturbation. In this paper, we propose a three-level tracking method for animating a 3D humanoid character. First, we take the laws of physics into account to attach physical attributes, such as mass, gravity, friction, collision, contact, and torque, to bones and joints of a character. The next step is to employ PD controller to follow a reference motion as closely as possible. Once the character cannot tolerate a strong perturbation to prevent itself from falling down, we are capable of tracking a desirable falling-down action to avoid any falling condition inaccuracy. From the experimental results, we demonstrate the effectiveness and flexibility of the proposed method in comparison with conventional data-driven approaches.
Abstract: In-situ chemical oxidation (ISCO) has been widely
used for source zone remediation of Dense Nonaqueous Phase
Liquids (DNAPLs) in subsurface environments. DNAPL source
zones for karst aquifers are generally located in epikarst where the
DNAPL mass is trapped either in karst soil or at the regolith contact
with carbonate bedrock. This study aims to investigate the
performance of oxidation of residual trichloroethylene found in such
environments by potassium permanganate. Batch and flow cell
experiments were conducted to determine the kinetics and the mass
removal rate of TCE. pH change, Cl production, TCE and MnO4
destruction were monitored routinely during experiments. Nonreactive
tracer tests were also conducted prior and after the oxidation
process to determine the influence of oxidation on flow conditions.
The results show that oxidant consumption rate of the calcareous
epikarst soil was significant and the oxidant demand was determined
to be 20 g KMnO4/kg soil. Oxidation rate of residual TCE (1.26x10-3
s-1) was faster than the oxidant consumption rate of the soil (2.54 -
2.92x10-4 s-1) at only high oxidant concentrations (> 40 mM
KMnO4). Half life of TCE oxidation ranged from 7.9 to 10.7 min.
Although highly significant fraction of residual TCE mass in the
system was destroyed by permanganate oxidation, TCE
concentration in the effluent remained above its MCL. Flow
interruption tests indicate that efficiency of ISCO was limited by the
rate of TCE dissolution and the rate-limited desorption of TCE. The
residence time and the initial concentration of the oxidant in the
source zone also controlled the efficiency of ISCO in epikarst.
Abstract: Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.
Abstract: This paper presents the voltage regulation scheme of
D-STATCOM under three-phase faults. It consists of the voltage
detection and voltage regulation schemes in the 0dq reference. The
proposed control strategy uses the proportional controller in which
the proportional gain, kp, is appropriately adjusted by using genetic
algorithms. To verify its use, a simplified 4-bus test system is situated
by assuming a three-phase fault at bus 4. As a result, the DSTATCOM
can resume the load voltage to the desired level within
1.8 ms. This confirms that the proposed voltage regulation scheme
performs well under three-phase fault events.
Abstract: The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.
Abstract: The optimal control is one of the possible controllers
for a dynamic system, having a linear quadratic regulator and using
the Pontryagin-s principle or the dynamic programming method .
Stochastic disturbances may affect the coefficients (multiplicative
disturbances) or the equations (additive disturbances), provided that
the shocks are not too great . Nevertheless, this approach encounters
difficulties when uncertainties are very important or when the probability
calculus is of no help with very imprecise data. The fuzzy
logic contributes to a pragmatic solution of such a problem since it
operates on fuzzy numbers. A fuzzy controller acts as an artificial
decision maker that operates in a closed-loop system in real time.
This contribution seeks to explore the tracking problem and control
of dynamic macroeconomic models using a fuzzy learning algorithm.
A two inputs - single output (TISO) fuzzy model is applied to the
linear fluctuation model of Phillips and to the nonlinear growth model
of Goodwin.
Abstract: The stop watch is used to measure the time required
for a certain event. This is different from normal clocks in many
ways, one of which is the accuracy of time. The stop watch requires
much more accuracy than the normal clocks. In this paper, an
ATmega8535 microcontroller was used to control the stop watch, by
which perfect accuracy can be ensured. For compiling the C code and
for loading the compiled .hex file into the microcontroller, AVR
studio and PonyProg were used respectively. The stop watch is also
different from traditional stop watches, as it contains two different
timing modes namely 'Split timing' and 'Lap timing'.
Abstract: Collaborative planning, forecasting and
replenishment (CPFR) coordinates the various supply chain
management activities including production and purchase planning,
demand forecasting and inventory replenishment between supply
chain trading partners. This study proposes a systematic way of
analyzing CPFR supporting factors using fuzzy cognitive map
(FCM) approach. FCMs have proven particularly useful for solving
problems in which a number of decision variables and
uncontrollable variables are causally interrelated. Hence the FCMs
of CPFR are created to show the relationships between the factors
that influence on effective implementation of CPFR in the supply
chain.
Abstract: In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions 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: A new and cost effective RP-HPLC method was
developed and validated for simultaneous analysis of non steroidal
anti inflammatory dugs Diclofenac sodium (DFS), Flurbiprofen
(FLP) and an opioid analgesic Tramadol (TMD) in advanced drug
delivery systems (Liposome and Microcapsules), marketed brands
and human plasma. Isocratic system was employed for the flow of
mobile phase consisting of 10 mM sodium dihydrogen phosphate
buffer and acetonitrile in molar ratio of 67: 33 with adjusted pH of
3.2. The stationary phase was hypersil ODS column (C18, 250×4.6
mm i.d., 5 μm) with controlled temperature of 30 C°. DFS in
liposomes, microcapsules and marketed drug products was
determined in range of 99.76-99.84%. FLP and TMD in
microcapsules and brands formulation were 99.78 - 99.94 % and
99.80 - 99.82 %, respectively. Single step liquid-liquid extraction
procedure using combination of acetonitrile and trichloroacetic acid
(TCA) as protein precipitating agent was employed. The detection
limits (at S/N ratio 3) of quality control solutions and plasma samples
were 10, 20, and 20 ng/ml for DFS, FLP and TMD, respectively.
The Assay was acceptable in linear dynamic range. All other
validation parameters were found in limits of FDA and ICH method
validation guidelines. The proposed method is sensitive, accurate and
precise and could be applicable for routine analysis in
pharmaceutical industry as well as in human plasma samples for
bioequivalence and pharmacokinetics studies.
Abstract: This paper proposes an adaptive sliding mode
controller which combines adaptive control and sliding
mode control to control a nonlinear robotic manipulator
with uncertain parameters. We use an adaptive algorithm
based on the concept of sliding mode control to alleviate the
chattering phenomenon of control input. Adaptive laws are
developed to obtain the gain of switching input and the
boundary layer parameters. The stability and convergence
of the robotic manipulator control system are guaranteed
by applying the Lyapunov theorem. Simulation results
demonstrate that the chattering of control input can be
alleviated effectively. The proposed controller scheme can
assure robustness against a large class of uncertainties and
achieve good trajectory tracking performance.
Abstract: In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.
Abstract: Rotor Flux based Model Reference Adaptive System
(RF-MRAS) is the most popularly used conventional speed
estimation scheme for sensor-less IM drives. In this scheme, the
voltage model equations are used for the reference model. This
encounters major drawbacks at low frequencies/speed which leads to
the poor performance of RF-MRAS. Replacing the reference model
using Neural Network (NN) based flux estimator provides an
alternate solution and addresses such drawbacks. This paper
identifies an NN based flux estimator using Single Neuron Cascaded
(SNC) Architecture. The proposed SNC-NN model replaces the
conventional voltage model in RF-MRAS to form a novel MRAS
scheme named as SNC-NN-MRAS. Through simulation the proposed
SNC-NN-MRAS is shown to be promising in terms of all major
issues and robustness to parameter variation. The suitability of the
proposed SNC-NN-MRAS based speed estimator and its advantages
over RF-MRAS for sensor-less induction motor drives is
comprehensively presented through extensive simulations.
Abstract: This paper describes identification of the two poles
unstable SOPDT process, especially with large time delay. A new
modified relay feedback identification method for two poles unstable
SOPDT process is proposed. Furthermore, for the two poles unstable
SOPDT process, an additional Derivative controller is incorporated
parallel with relay to relax the constraint on the ratio of delay to the
unstable time constant, so that the exact model parameters of
unstable processes can be identified. To cope with measurement
noise in practice, a low pass filter is suggested to get denoised output
signal toimprove the exactness of model parameter of unstable
process. PID Lead-lag tuning formulas are derived for two poles
unstable (SOPDT) processes based on IMC principle. Simulation
example illustrates the effectiveness and the simplicity of the
proposed identification and control method.
Abstract: Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.
Abstract: Adsorption of proteins onto a solid surface is believed to be the initial and controlling step in biofouling. A better knowledge of the fouling process can be obtained by controlling the formation of the first protein layer at a solid surface. A number of methods have been investigated to inhibit adsorption of proteins. In this study, the adsorption kinetics of