Abstract: This paper presents a nonlinear differential model,
for a three-bladed horizontal axis wind turbine (HAWT) suited
for control applications. It is based on a 8-dofs, lumped
parameters structural dynamics coupled with a quasi-steady sectional
aerodynamics. In particular, using the Euler-Lagrange Equation
(Energetic Variation approach), the authors derive, and successively
validate, such model. For the derivation of the aerodynamic model,
the Greenbergs theory, an extension of the theory proposed by
Theodorsen to the case of thin airfoils undergoing pulsating flows,
is used. Specifically, in this work, the authors restricted that theory
under the hypothesis of low perturbation reduced frequency k,
which causes the lift deficiency function C(k) to be real and equal
to 1. Furthermore, the expressions of the aerodynamic loads are
obtained using the quasi-steady strip theory (Hodges and Ormiston),
as a function of the chordwise and normal components of relative
velocity between flow and airfoil Ut, Up, their derivatives, and
section angular velocity ε˙. For the validation of the proposed model,
the authors carried out open and closed-loop simulations of a 5
MW HAWT, characterized by radius R =61.5 m and by mean chord
c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec.
The first analysis performed is the steady state solution, where
a uniform wind Vw = 11.4 m/s is considered and a collective
pitch angle θ = 0.88◦ is imposed. During this step, the authors
noticed that the proposed model is intrinsically periodic due to
the effect of the wind and of the gravitational force. In order
to reject this periodic trend in the model dynamics, the authors
propose a collective repetitive control algorithm coupled with a PD
controller. In particular, when the reference command to be tracked
and/or the disturbance to be rejected are periodic signals with a
fixed period, the repetitive control strategies can be applied due to
their high precision, simple implementation and little performance
dependency on system parameters. The functional scheme of a
repetitive controller is quite simple and, given a periodic reference
command, is composed of a control block Crc(s) usually added
to an existing feedback control system. The control block contains
and a free time-delay system eτs in a positive feedback loop, and a
low-pass filter q(s). It should be noticed that, while the time delay
term reduces the stability margin, on the other hand the low pass
filter is added to ensure stability. It is worth noting that, in this
work, the authors propose a phase shifting for the controller and
the delay system has been modified as e^(−(T−γk)), where T is the
period of the signal and γk is a phase shifting of k samples of the
same periodic signal. It should be noticed that, the phase shifting
technique is particularly useful in non-minimum phase systems, such
as flexible structures. In fact, using the phase shifting, the iterative
algorithm could reach the convergence also at high frequencies.
Notice that, in our case study, the shifting of k samples depends
both on the rotor angular velocity Ω and on the rotor azimuth
angle Ψ: we refer to this controller as a spatial repetitive controller.
The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades.
The performance of the spatial repetitive controller is compared
with an industrial PI controller. In particular, starting from wind
speed velocity Vw = 11.4 m/s the controller is asked to maintain the
nominal angular velocity Ωn = 1.266rad/s after an instantaneous
increase of wind speed (Vw = 15 m/s). Then, a purely periodic
external disturbance is introduced in order to stress the capabilities
of the repetitive controller. The results of the simulations show that,
contrary to a simple PI controller, the spatial repetitive-PD controller
has the capability to reject both external disturbances and periodic
trend in the model dynamics. Finally, the nominal value of the
angular velocity is reached, in accordance with results obtained with
commercial software for a turbine of the same type.
Abstract: A strategy of fault diagnosis and tolerance for
asynchronous sequential machines is discussed in this paper. With
no synchronizing clock, it is difficult to diagnose an occurrence
of permanent or stuck-in faults in the operation of asynchronous
machines. In this paper, we present a fault detector comprised of
a timer and a set of static functions to determine the occurrence
of faults. In order to realize immediate fault tolerance, corrective
control theory is applied to designing a dynamic feedback controller.
Existence conditions for an appropriate controller and its construction
algorithm are presented in terms of reachability of the machine and
the feature of fault occurrences.
Abstract: A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M0 development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).
Abstract: This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.
Abstract: Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.
Abstract: Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.
Abstract: In this paper, the problem of stability and stabilization
for neutral delay-differential systems with infinite delay is
investigated. Using Lyapunov method, new delay-independent
sufficient condition for the stability of neutral systems with infinite
delay is obtained in terms of linear matrix inequality (LMI).
Memory-less state feedback controllers are then designed for the
stabilization of the system using the feasible solution of the resulting
LMI, which are easily solved using any optimization algorithms.
Numerical examples are given to illustrate the results of the proposed
methods.
Abstract: The article deals with the tool in Matlab GUI form
that is designed to analyse a mechatronic system sensitivity and
tolerance. In the analysed mechatronic system, a torque is transferred
from the drive to the load through a coupling containing flexible
elements. Different methods of control system design are used. The
classic form of the feedback control is proposed using Naslin method,
modulus optimum criterion and inverse dynamics method. The
cascade form of the control is proposed based on combination of
modulus optimum criterion and symmetric optimum criterion. The
sensitivity is analysed on the basis of absolute and relative sensitivity
of system function to the change of chosen parameter value of the
mechatronic system, as well as the control subsystem. The tolerance
is analysed in the form of determining the range of allowed relative
changes of selected system parameters in the field of system stability.
The tool allows to analyse an influence of torsion stiffness, torsion
damping, inertia moments of the motor and the load and controller(s)
parameters. The sensitivity and tolerance are monitored in terms of
the impact of parameter change on the response in the form of system
step response and system frequency-response logarithmic
characteristics. The Symbolic Math Toolbox for expression of the
final shape of analysed system functions was used. The sensitivity
and tolerance are graphically represented as 2D graph of sensitivity
or tolerance of the system function and 3D/2D static/interactive graph
of step/frequency response.
Abstract: This paper presents a model for a modified T-junction
device for microspheres generation. The numerical model is
developed using a commercial software package: COMSOL
Multiphysics. In order to test the accuracy of the numerical model,
multiple variables, such as the flow rate of cross-flow, fluid properties,
structure, and geometry of the microdevice are applied. The results
from the model are compared with the experimental results in the
diameter of the microsphere generated. The comparison shows a good
agreement. Therefore the model is useful in further optimization of the
device and feedback control of microsphere generation if any.
Abstract: Control of a semi-batch polymerization reactor using
an adaptive radial basis function (RBF) neural network method is
investigated in this paper. A neural network inverse model is used to
estimate the valve position of the reactor; this method can identify the
controlled system with the RBF neural network identifier. The
weights of the adaptive PID controller are timely adjusted based on
the identification of the plant and self-learning capability of RBFNN.
A PID controller is used in the feedback control to regulate the actual
temperature by compensating the neural network inverse model
output. Simulation results show that the proposed control has strong
adaptability, robustness and satisfactory control performance and the
nonlinear system is achieved.
Abstract: In this paper, fractional order feedback control of a ball
beam model is investigated. The ball beam model is a particular
example of the double Integrator system having strongly nonlinear
characteristics and unstable dynamics which make the control of
such system a challenging task. Most of the work in fractional order
control systems are in theoretical nature and controller design and its
implementation in practice is very small. In this work, a successful
attempt has been made to design a fractional order PIλDμcontroller
for a benchmark laboratory ball and beam model. Better performance
can be achieved using a fractional order PID controller and it is
demonstrated through simulations results with a comparison to the
classic PID controller.
Abstract: In this paper a nonlinear feedback control called augmented automatic choosing control (AACC) for a class of
nonlinear systems with constrained input is presented. When designed
the control, a constant term which arises from linearization of a
given nonlinear system is treated as a coefficient of a stable zero
dynamics. Parameters of the control are suboptimally selected by
maximizing the stable region in the sense of Lyapunov with the aid
of a 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: The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.
Abstract: This paper proposes a regulation method of back-to-back connected three-level converters in order to reduce the torque ripple in induction motor. First part is dedicated to the presentation of the feedback control of three-level PWM rectifier. In the second part, three-level NPC voltage source inverter balancing DC bus algorithm is presented. A theoretical analysis with a complete simulation of the system is presented to prove the excellent performance of the proposed technique.
Abstract: In the paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.
Abstract: This paper realized the 2-DOF controller structure for first order with time delay systems. The co-prime factorization is used to design observer based controller K(s), representing one degree of freedom. The problem is based on H∞ norm of mixed sensitivity and aims to achieve stability, robustness and disturbance rejection. Then, the other degree of freedom, prefilter F(s), is formulated as fixed structure polynomial controller to meet open loop processing of reference model. This model matching problem is solved by minimizing integral square error between reference model and proposed model. The feedback controller and prefilter designs are posed as optimization problem and solved using Particle Swarm Optimization (PSO). To show the efficiency of the designed approach different variety of processes are taken and compared for analysis.
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: Robust stability and performance are the two most
basic features of feedback control systems. The harmonic balance
analysis technique enables to analyze the stability of limit cycles
arising from a neural network control based system operating over
nonlinear plants. In this work a robust stability analysis based on the
harmonic balance is presented and applied to a neural based control
of a non-linear binary distillation column with unstructured
uncertainty. We develop ways to describe uncertainty in the form of
neglected nonlinear dynamics and high harmonics for the plant and
controller respectively. Finally, conclusions about the performance of
the neural control system are discussed using the Nyquist stability
margin together with the structured singular values of the uncertainty
as a robustness measure.
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: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.