2006 (Volume 16)
Laplace transforms for MIMO SD systems with delay
(University of Rostock, Department of Computer Science and Electrical Engineering, Rostock, Germany)
(St. Petersburg State University of Ocean Technology, Department of Automation, St. Petersburg, Russia)
The paper constructs the Laplace transform of the solution with zero initial energy for a MIMO sampled-data system containing pure time-delays in its stationary elements. The properties of the Laplace transform as a function of the complex variable are studied.
keywords: sampled-data systems, linear control systems, MIMO, Laplace transforms, time delay
General adaptive observer-based fuzzy control of uncertain nonaffine systems
(Department of Automatic Control, University of Jijel, Jijel, Algeria)
(Department of the Electric Engineering, LCP, ENP, Algiers, Algeria)
|M. M'Saad, M. Farza|
(GREYC, CNRS, Université de Caen, Cedex, France)
This paper focuses on the construction of an adaptive fuzzy output feedback control based on any adaptive fuzzy observer (adaptive fuzzy high-gain observer, adaptive fuzzy sliding mode observer, ...) for a class of single-input-single-output SISO uncertain or ill-defined nonaffine nonlinear system. Indeed, the corrective term of the proposed observer involves a well defined design function which is shown to be satisfied by the commonly used high-gain based observers, namely for the usual high-gain observers and the sliding modes observers together with their implementable versions. The design of the underlying update law as well as the robust control term is based on an appropriate filtering of the output tracking error. This particularly allows to overcome the output observation error filtering or the necessity of the famous strictly positive real (SPR) condition.
keywords: general observer, fuzzy adaptive control, nonaffine systems
On controversial superiority of delta operator models for small sampling periods
(Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland)
It is noted that for small sampling periods the superiority of the delta operator (DO) models over the shift operator (SO) concerns only the recording of model coefficients and some analytical calculations. It is also noted that in the simulations, making it possible to obtain the time response of the output for any input, as well as in the model identification under limited measurement accuracy, the superiority of the DO over SO models, for small sampling periods, disappears. These observations have an essential meaning since the mentioned problems of simulation and identification are important for applications.
keywords: digital control, discrete-time systems, delta operator models, shift operator models
Optimal control strategy of variable wind speed generator based on Artificial Neural Networks
|Lilia Jerbi, Lotfi Krichen, Abderrazak Ouali|
(National School of Engineering of Sfax, Advanced Control and Energy Management, Tunisia)
Currently, the use of the doubly-fed induction generators is more and more justified for the aero-generators which develop electric power greater than a few megawatts. These aero-generators characterized by their variable speed enable to capture the maximum power of the wind and ensure the production of a high quality electric power. The interest of this paper is to control an aero-generator including a doubly-fed induction machine directly connected to the grid at the stator side and via a reversible converter at the rotor side. The state control feedback law is established by considering a third reduced model with stator flux oriented simultaneously assures the dynamic decoupling of the two d-q rotor flux components and eliminates the mechanical transitory oscillations. A neuronal network radial basis function is used to approximate the control law parameters for any varying wind speed and any reactive power being imposed by the power network load flow computation. This control law permits to enhance the robustness stability of the aero-generator for any abrupt fluctuations of the wind speed and to supply the grid at the same time with a high quality of electric power.
keywords: wind energy, doubly fed induction generator, radial basis neural network, active and reactive power control
Robust linear controller for dynamic object with two-dimensional uncertain parameters space
(AGH University of Science and Technology, Cracow, Poland)
Robust linear controller for an uncertain parameter linear dynamic system is presented in the paper. Plant is described by finite dimensional linear state-space equation with interval diagonal state matrix, known control and output matrices and two-dimensional uncertain parameters space. The controllable and observable part of the system can be described by equivalent transfer function. To control the plant a general linear controller is used. General robustness indices and idea of robustness areas are defined for the control system. First order uncertain parameter system with the PID controller is presented as an illustrative example.
keywords: uncertain-parameter systems, interval systems, robust control
Multiobjective optimization of a fuzzy PID controller
(Department of Electronics, University of Jijel, Jijel, Algeria)
(Department of Electronics, Setif University, Algeria)
(Department of Electrotechnics, Skikda University, Algeria)
A fuzzy logic controller (FLC) with multilayer neural network whose synaptic weights represent the fuzzy knowledge base and its application to the highly nonlinear systems is presented in this work. The scaling factors of the input variables, membership functions and the rule sets are optimized by the use of the multiobjective genetic algorithms (MGA). The fuzzy network structure is specified by a combination of the mixed Takagi-Sugeno's (TS) and Mamdani's fuzzy reasoning. The mixed, Binary-Real-Integer, optimal coding is utilized to construct the chromosomes, which define the same of necessary prevailing parameters for the conception of the desired controller. This new controller stands out by a non-standard gain, which varies linearly with the fuzzy inputs. Under certain conditions, it becomes similar to the conventional PID controller with non-linearly variable coefficients. Computer simulation indicates that the designed fuzzy controller is satisfactory in control of a nonlinear system 'Inverted Pendulum'.
keywords: neural networks, genetic algorithms, fuzzy-PID control, nonlinear PI/PD
State estimation for nonlinear discrete-time delay systems
|El Houssine Labriji, Fouad Lahmidi, Abdelwahed Namir|
(Département de Mathématiques et Informatique, Faculté des Sciences Ben M'sik, Casablanca, Morocco)
The problem of reconstructing the state of a nonlinear, discrete-time, distributed-parameter system with delays using the information given by an output equation is considered. First, we establish conditions that assure the existence of a unique state corresponding to the given output. Then, more generally, the set of all states which correspond to the given observation is characterized. The methods used to solve these problems are based on the state-space technique and the fixed-point theorems.
keywords: delay, discrete-time system, distributed-parameter system, fixed-point theory, observability, nonlinear system