Abstract: This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.
Abstract: Radiant heating systems work fundamentally differently from air systems by taking advantage of both radiant and convective heat transfer to remove space heating load. There are rare studies on differences of heating systems between all-air system and radiant floor system. This paper uses the method of simulation based on state-space to calculate the indoor temperature and wall temperature of each system and shows how the dynamic heat transfer in rooms conditioned by a radiant system is different from an air system. Then this paper analyses the changes of indoor temperature of these two systems, finding out the differences between all-air heating system and radiant floor heating system to help the designer choose a more suitable heating system.
Abstract: This paper investigated the simulation of two-phase interleaved boost converter (IBC) with free and open-source software Scilab/Xcos. By using interleaved method, it can reduce current stress on components, components size, input current ripple and output voltage ripple. The required mathematical model is obtained from the equivalent circuit of its different four modes of operation for simulation. The equivalent circuits are considered in continuous conduction mode (CCM). The average values of the system variables are derived from the state-space equation to find the equilibrium point. Scilab is now becoming more and more popular among students, engineers and scientists because it is open-source software and free of charge. It gives a great convenience because it has powerful computation and simulation function. The waveforms of output voltage, input current and inductors current are obtained by using Scilab/Xcos.
Abstract: Minimizing the weight in flexible structures means
reducing material and costs as well. However, these structures could
become prone to vibrations. Attenuating these vibrations has become
a pivotal engineering problem that shifted the focus of many research
endeavors. One technique to do that is to design and implement
an active control system. This system is mainly composed of a
vibrating structure, a sensor to perceive the vibrations, an actuator
to counteract the influence of disturbances, and finally a controller to
generate the appropriate control signals. In this work, two different
techniques are explored to create two different mathematical models
of an active control system. The first model is a finite element model
with a reduced number of nodes and it is called a super-element.
The second model is in the form of state-space representation, i.e.
a set of partial differential equations. The damping coefficients are
calculated and incorporated into both models. The effectiveness of
these models is demonstrated when the system is excited by its first
natural frequency and an active control strategy is developed and
implemented to attenuate the resulting vibrations. Results from both
modeling techniques are presented and compared.
Abstract: In order to monitor the thermal behavior of an
asynchronous machine with squirrel cage rotor, a 9th-order extended
Kalman filter (EKF) algorithm is implemented to estimate the
temperatures of the stator windings, the rotor cage and the stator
core. The state-space equations of EKF are established based on
the electrical, mechanical and the simplified thermal models of an
asynchronous machine. The asynchronous machine with simplified
thermal model in Dymola is compiled as DymolaBlock, a physical
model in MATLAB/Simulink. The coolant air temperature, three-phase
voltages and currents are exported from the physical model and are
processed by EKF estimator as inputs. Compared to the temperatures
exported from the physical model of the machine, three parts of
temperatures can be estimated quite accurately by the EKF estimator.
The online EKF estimator is independent from the machine control
algorithm and can work under any speed and load condition if the
stator current is nonzero current system.
Abstract: The power buck converter is the most widely used
DC/DC converter topology. They have a very large application area
such as DC motor drives, photovoltaic power system which require
fast transient responses and high efficiency over a wide range of load
current. This work proposes, the modelling of DC/DC power buck
converter using state-space averaging method and the current-mode
control using a proportional-integral controller. The efficiency of the
proposed model and control loop are evaluated with operating point
changes. The simulation results proved the effectiveness of the linear
model of DC/DC power buck converter.
Abstract: This paper discusses the general methods to saturation
in the steady-state, two axis (d & q) frame models of synchronous
machines. In particular, the important role of the magnetic coupling
between the d-q axes (cross-magnetizing phenomenon), is
demonstrated. For that purpose, distinct methods of saturation
modeling of dumper synchronous machine with cross-saturation are
identified, and detailed models synthesis in d-q axes. A number of
models are given in the final developed form. The procedure and the
novel models are verified by a critical application to prove the
validity of the method and the equivalence between all developed
models is reported. Advantages of some of the models over the
existing ones and their applicability are discussed.
Abstract: In the present work, the finite element formulation for
the investigation of the effects of a localized interfacial degeneration
on the dynamic behavior of the [90°/0°] laminated composite plate
employing the state-space technique is performed. The stiffness of
the laminate is determined by assembling the stiffnesses of subelements.
This includes an introduction of an interface layer adopting
the virtually zero-thickness formulation to model the interfacial
degeneration. Also, the kinematically consistent mass matrix and
proportional damping have been formulated to complete the free
vibration governing expression. To simulate the interfacial
degeneration of the laminate, the degenerated areas are defined from
the center propagating outwards in a localized manner. It is found
that the natural frequency, damped frequency and damping ratio of
the plate decreases as the degenerated area of the interface increases.
On the contrary, the loss factor increases correspondingly.
Abstract: This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.
Abstract: In this paper, we present a neural-network (NN) based
approach to represent a nonlinear Tagagi-Sugeno (T-S) system. A
linear differential inclusion (LDI) state-space representation is utilized
to deal with the NN models. Taking advantage of the LDI
representation, the stability conditions and controller design are
derived for a class of nonlinear structural systems. Moreover, the
concept of utilizing the Parallel Particle Swarm Optimization (PPSO)
algorithm to solve the common P matrix under the stability criteria is
given in this paper.
Abstract: This paper proposes a video-based framework for face recognition to identify which faces appear in a video sequence. Our basic idea is like a tracking task - to track a selection of person candidates over time according to the observing visual features of face images in video frames. Hence, we employ the state-space model to formulate video-based face recognition by dividing this problem into two parts: the likelihood and the transition measures. The likelihood measure is to recognize whose face is currently being observed in video frames, for which two-dimensional linear discriminant analysis is employed. The transition measure estimates the probability of changing from an incorrect recognition at the previous stage to the correct person at the current stage. Moreover, extra nodes associated with head nodes are incorporated into our proposed state-space model. The experimental results are also provided to demonstrate the robustness and efficiency of our proposed approach.
Abstract: A challenged control problem is when the
performance is pushed to the limit. The state-derivative feedback
control strategy directly uses acceleration information for feedback
and state estimation. The derivative part is concerned with the rateof-
change of the error with time. If the measured variable approaches
the set point rapidly, then the actuator is backed off early to allow it
to coast to the required level. Derivative action makes a control
system behave much more intelligently. A sensor measures the
variable to be controlled and the measured in formation is fed back to
the controller to influence the controlled variable. A high gain
problem can be also formulated for proportional plus derivative
feedback transformation. Using MATLAB Simulink dynamic
simulation tool this paper examines a system with a proportional plus
derivative feedback and presents an automatic implementation of
finding an acceptable controlled system. Using feedback
transformations the system is transformed into another system.
Abstract: This paper presents a new problem solving approach
that is able to generate optimal policy solution for finite-state
stochastic sequential decision-making problems with high data
efficiency. The proposed algorithm iteratively builds and improves
an approximate Markov Decision Process (MDP) model along with
cost-to-go value approximates by generating finite length trajectories
through the state-space. The approach creates a synergy between an
approximate evolving model and approximate cost-to-go values to
produce a sequence of improving policies finally converging to the
optimal policy through an intelligent and structured search of the
policy space. The approach modifies the policy update step of the
policy iteration so as to result in a speedy and stable convergence to
the optimal policy. We apply the algorithm to a non-holonomic
mobile robot control problem and compare its performance with
other Reinforcement Learning (RL) approaches, e.g., a) Q-learning,
b) Watkins Q(λ), c) SARSA(λ).
Abstract: Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.
Abstract: A cart-ball system is a challenging system from the
control engineering point of view. This is due to the nonlinearities,
multivariable, and non-minimum phase behavior present in this
system. This paper is concerned with the problem of modeling and
control of such system. The objective of control strategy is to place
the cart at a desired position while balancing the ball on the top of the
arc-shaped track fixed on the cart. A State-Feedback Controller
(SFC) with a pole-placement method will be designed in order to
control the system. At first, the mathematical model of a cart-ball
system in the state-space form is developed. Then, the linearization of
a model will be established in order to design a SFC. The integral
control strategy will be performed as to control the cart position of a
system. Simulation work is then performed using
MATLAB/SIMULINK software in order to study the performance of
SFC when applied to the system.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.
Abstract: In this paper, a novel approach is presented
for designing multiplier-free state-space digital filters. The
multiplier-free design is obtained by finding power-of-2 coefficients
and also quantizing the state variables to power-of-2
numbers. Expressions for the noise variance are derived for the
quantized state vector and the output of the filter. A “structuretransformation
matrix" is incorporated in these expressions. It
is shown that quantization effects can be minimized by properly
designing the structure-transformation matrix. Simulation
results are very promising and illustrate the design algorithm.
Abstract: Dynamic models of power converters are normally
time-varying because of their switching actions. Several approaches
are applied to analyze the power converters to achieve the timeinvariant
models suitable for system analysis and design via the
classical control theory. The paper presents how to derive dynamic
models of the power system consisting of a three-phase controlled
rectifier feeding an uncontrolled buck converter by using the
combination between the well known techniques called the DQ and
the generalized state-space averaging methods. The intensive timedomain
simulations of the exact topology model are used to support
the accuracies of the reported model. The results show that the
proposed model can provide good accuracies in both transient and
steady-state responses.
Abstract: A new method identifies coupled fluid-structure system with a reduced set of state variables is presented. Assuming that the structural model is known a priori either from an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically given a finite set of structural modes the method extracts generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. The resulting reduced-order model is suitable for constant Mach, varying density analysis.
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.