Abstract: This paper examines the problem of designing a robust H8 state-feedback controller for a class of nonlinear two-time scale systems with Markovian Jumps described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain Markovian jump nonlinear two-time scale systems to have an H8 performance are derived. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard nonlinear two-time scale systems. A numerical example is provided to illustrate the design developed in this paper.
Abstract: We present a simulation and realization of a battery
charge regulator (BCR) in microsatellite earth observation. The tests
were performed on battery pack 12volt, capacity 24Ah and the solar array open circuit voltage of 100 volt and optimum power of about
250 watt. The battery charge is made by solar module. The principle is to adapt the output voltage of the solar module to the battery by
using the technique of pulse width modulation (PWM). Among the different techniques of charge battery, we opted for the technique of
the controller ON/OFF is a standard technique and simple, it-s easy to
be board executed validation will be made by simulation "Proteus Isis
Professional software ". The circuit and the program of this prototype
are based on the PIC16F877 microcontroller, a serial interface connecting a PC is also realized, to view and save data and graphics
in real time, for visualization of data and graphs we develop an interface tool “visual basic.net (VB)--.
Abstract: This paper presents a fuzzy logic controlled shunt
active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a
simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able
to operate in both balanced and unbalanced load conditions. A fuzzy
logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity
of the presented approach in harmonic mitigation is verified via
simulation results of the proposed test system under different loading
conditions.
Abstract: The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.
Abstract: This paper presents the averaging model of a buck
converter derived from the generalized state-space averaging method.
The sliding mode control is used to regulate the output voltage of the
converter and taken into account in the model. The proposed model
requires the fast computational time compared with those of the full
topology model. The intensive time-domain simulations via the exact
topology model are used as the comparable model. The results show
that a good agreement between the proposed model and the switching
model is achieved in both transient and steady-state responses. The
reported model is suitable for the optimal controller design by using
the artificial intelligence techniques.
Abstract: The Proton Exchange Membrane Fuel Cell (PEMFC)
control system has an important effect on operation of cell.
Traditional controllers couldn-t lead to acceptable responses because
of time- change, long- hysteresis, uncertainty, strong- coupling and
nonlinear characteristics of PEMFCs, so an intelligent or adaptive
controller is needed. In this paper a neural network predictive
controller have been designed to control the voltage of at the
presence of fluctuations of temperature. The results of
implementation of this designed NN Predictive controller on a
dynamic electrochemical model of a small size 5 KW, PEM fuel cell
have been simulated by MATLAB/SIMULINK.
Abstract: This paper is described one of the intelligent control method in Autonomous systems, which is called fuzzy control to correct the three wheel omnidirectional robot movement while it make mistake to catch the target. Fuzzy logic is especially advantageous for problems that can not be easily represented by mathematical modeling because data is either unavailable, incomplete or the process is too complex. Such systems can be easily up grated by adding new rules to improve performance or add new features. In many cases , fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. The fuzzy controller designed here is more accurate and flexible than the traditional controllers. The project is done at MRL middle size soccer robot team.
Abstract: This paper examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.
Abstract: The performance of a sucrose-based H2 production in
a completely stirred tank reactor (CSTR) was modeled by neural
network back-propagation (BP) algorithm. The H2 production was
monitored over a period of 450 days at 35±1 ºC. The proposed model
predicts H2 production rates based on hydraulic retention time
(HRT), recycle ratio, sucrose concentration and degradation, biomass
concentrations, pH, alkalinity, oxidation-reduction potential (ORP),
acids and alcohols concentrations. Artificial neural networks (ANNs)
have an ability to capture non-linear information very efficiently. In
this study, a predictive controller was proposed for management and
operation of large scale H2-fermenting systems. The relevant control
strategies can be activated by this method. BP based ANNs modeling
results was very successful and an excellent match was obtained
between the measured and the predicted rates. The efficient H2
production and system control can be provided by predictive control
method combined with the robust BP based ANN modeling tool.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller
Abstract: The paper presents the virtual model of the active
suspension system used for improving the dynamic behavior of a
motor vehicle. The study is focused on the design of the control
system, the purpose being to minimize the effect of the road
disturbances (which are considered as perturbations for the control
system). The analysis is performed for a quarter-car model, which
corresponds to the suspension system of the front wheel, by using the
DFC (Design for Control) software solution EASY5 (Engineering
Analysis Systems) of MSC Software. The controller, which is a PIDbased
device, is designed through a parametric optimization with the
Matrix Algebra Tool (MAT), considering the gain factors as design
variables, while the design objective is to minimize the overshoot of
the indicial response.
Abstract: Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.
Abstract: A novel low-cost impedance control structure is
proposed for monitoring the contact force between end-effector and
environment without installing an expensive force/torque sensor.
Theoretically, the end-effector contact force can be estimated from the
superposition of each joint control torque. There have a nonlinear
matrix mapping function between each joint motor control input and
end-effector actuating force/torques vector. This new force control
structure can be implemented based on this estimated mapping matrix.
First, the robot end-effector is manipulated to specified positions, then
the force controller is actuated based on the hall sensor current
feedback of each joint motor. The model-free fuzzy sliding mode
control (FSMC) strategy is employed to design the position and force
controllers, respectively. All the hardware circuits and software
control programs are designed on an Altera Nios II embedded
development kit to constitute an embedded system structure for a
retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI
and FSMC force control algorithms can achieve reasonable contact
force monitoring objective based on this hardware control structure.
Abstract: Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. Various speed control techniques like, Direct Torque Control, Sensorless Vector Control and Field Oriented Control are discussed in this paper. Soft computing technique – Fuzzy logic is applied in this paper for the speed control of induction motor to achieve maximum torque with minimum loss. The fuzzy logic controller is implemented using the Field Oriented Control technique as it provides better control of motor torque with high dynamic performance. The motor model is designed and membership functions are chosen according to the parameters of the motor model. The simulated design is tested using various tool boxes in MATLAB. The result concludes that the efficiency and reliability of the proposed speed controller is good.
Abstract: In this paper, determining the optimal proportionalintegral-
derivative (PID) controller gains of an single-area load
frequency control (LFC) system using genetic algorithm (GA) is
presented. The LFC is notoriously difficult to control optimally using
conventionally tuning a PID controller because the system parameters
are constantly changing. It is for this reason the GA as tuning strategy
was applied. The simulation has been conducted in MATLAB
Simulink package for single area power system. the simulation results
shows the effectiveness performance of under various disturbance.
Abstract: In this paper, a neural network tuned fuzzy controller
is proposed for controlling Multi-Input Multi-Output (MIMO)
systems. For the convenience of analysis, the structure of MIMO
fuzzy controller is divided into single input single-output (SISO)
controllers for controlling each degree of freedom. Secondly,
according to the characteristics of the system-s dynamics coupling, an
appropriate coupling fuzzy controller is incorporated to improve the
performance. The simulation analysis on a two-level mass–spring
MIMO vibration system is carried out and results show the
effectiveness of the proposed fuzzy controller. The performance
though improved, the computational time and memory used is
comparatively higher, because it has four fuzzy reasoning blocks and
number may increase in case of other MIMO system. Then a fuzzy
neural network is designed from a set of input-output training data to
reduce the computing burden during implementation. This control
strategy can not only simplify the implementation problem of fuzzy
control, but also reduce computational time and consume less
memory.
Abstract: A new nonlinear PID controller and its stability
analysis are presented in this paper. A nonlinear function is deduced
from the similarities between the control effort and the electric-field
effect of a capacitor. The conventional linear PID controller can be
modified into a nonlinear one by this function. To analyze the stability
of the nonlinear PID controlled system, an idea of energy equivalence
is adapted to avoid the conservativeness which is usually arisen from
some traditional theorems and Criterions. The energy equivalence is
naturally related with the conceptions of Passivity and T-Passivity. As
a result, an engineering guideline for the parameter design of the
nonlinear PID controller is obtained. An inverted pendulum system is
tested to verify the nonlinear PID control scheme.
Abstract: Pulse width modulation (PWM) techniques have been
the subject of intensive research for different industrial and power
sector applications. A large variety of methods, different in concept
and performance, have been newly developed and described. This
paper analyzes the comparative merits of Sinusoidal Pulse Width
Modulation (SPWM) and Space Vector Pulse Width Modulation
(SVPWM) techniques and the suitability of these techniques in a
Shunt Active Filter (SAF). The objective is to select the scheme that
offers effective utilization of DC bus voltage and also harmonic
reduction at the input side. The effectiveness of the PWM techniques
is tested in the SAF configuration with a non linear load. The
performance of the SAF with the SPWM and (SVPWM) techniques
are compared with respect to the THD in source current. The study
reveals that in the context of closed loop SAF control with the
SVPWM technique there is only a minor improvement in THD. The
utilization of the DC bus with SVPWM is also not significant
compared to that with SPWM because of the non sinusoidal
modulating signal from the controller in SAF configuration.
Abstract: This paper deals with the synthesis of fuzzy controller
applied to a permanent magnet synchronous machine (PMSM) with a
guaranteed H∞ performance. To design this fuzzy controller,
nonlinear model of the PMSM is approximated by Takagi-Sugeno
fuzzy model (T-S fuzzy model), then the so-called parallel
distributed compensation (PDC) is employed. Next, we derive the
property of the H∞ norm. The latter is cast in terms of linear matrix
inequalities (LMI-s) while minimizing the H∞ norm of the transfer
function between the disturbance and the error ( ) ev T . The
experimental and simulations results were conducted on a permanent
magnet synchronous machine to illustrate the effects of the fuzzy
modelling and the controller design via the PDC.
Abstract: Fractional-order controller was proven to perform better than the integer-order controller. However, the absence of a pole at origin produced marginal error in fractional-order control system. This study demonstrated the enhancement of the fractionalorder PI over the integer-order PI in a steam temperature control. The fractional-order controller was cascaded with an error compensator comprised of a very small zero and a pole at origin to produce a zero steady-state error for the closed-loop system. Some modification on the error compensator was suggested for different order fractional integrator that can improve the overall phase margin.