Volume 65 (2014): Issue 1 (January 2014)

The paper addresses problem of designing a robust output feedback model predictive control for uncertain linear systems over networks with packet-loss. The packet-loss process is arbitrary and bounded by the control horizon of model predictive control. Networked predictive control systems with packet loss are modeled as switched linear systems. This enables us to apply the theory of switched systems to establish the stability condition. The stabilizing controller design is based on sufficient robust stability conditions formulated as a solution of bilinear matrix inequality. Finally, a benchmark numerical example-double integrator is given to illustrate the effectiveness of the proposed method.

In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.

The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.

The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic appliances. For the GMM classification, the input feature vectors comprise the basic and the complementary spectral properties as well as the supra-segmental parameters. Dependence of classification correctness on the number of the parameters in the input feature vector and on the computation complexity is also evaluated. In addition, an influence of the initial setting of the parameters for GMM training process was analyzed. Obtained recognition results are compared visually in the form of graphs as well as numerically in the form of tables and confusion matrices for tested sentences uttered using three configurations of orthodontic appliances.

In this paper we introduce a new approach to the sliding mode control design based on orthogonal models. First, we discuss the sliding mode control based on a model given in controllable canonical form. Then, we design almost orthogonal filters based on almost orthogonal polynomials of M¨untz-Legendre type. The advantage of the almost orthogonal filters is that they can be used for the modelling and analysis of systems with nonlinearities and imperfections. Herein, we use a designed filter to obtain several linearized models of an unknown system in different working areas. For each of these linearized models, corresponding sliding mode controller is designed and the switching between controls laws depends only on input signal. The experimental results and comparative analysis with relay control, already installed in laboratory equipment, verify the efficiency and excellent performance of such a control in the case of anti-lock braking system.

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

To meet the need of multi-channel DC power supply to activate multiple macro fiber composite (MFC) material simultaneously, a novel multi-channel adjustable DC supply using single-input single-output transformer based on spectral separation is proposed. A hybrid signal containing multiple frequency bands is boosted to obtain a high-voltage signal without bands change. Several frequency selection circuits are then used to separate individual signals in different frequency band from the high-voltage signal. Finally, these signals are rectified and filtered respectively to obtain multiple channel DC voltages. The feasibility of the proposed scheme is analyzed theoretically and verified by simulation. The hybrid signal containing multiple frequency bands is constructed by MCU (Micro Control Unit) and boosted using push-pull boost circuit. Low-pass, band-pass and high-pass frequency selection circuits are used to obtain the individual high-voltage signal in different frequency bands, and the amplitude frequency response characteristics of these filters are simulated using PSpice. Experimental results prove that each part of the scheme runs reliable and the output is stable and adjustable.

In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

In this study, a 3kW squirrel cage induction motor having slits in stator and rotor teeth were examined. The slit depth and width in the 56 different slitted motor models were optimized with Finite Element Method Magnetics (FEMM) software by using Finite Elements Method (FEM). What value the depth and width of optimum slit should be was determined in order to obtain maximum motor efficiency in the new motor models created with the proposed slitted structure, and how the depth and width of slit could affect the performance of motor was demonstrated.