Integrated Fuzzy Robust Controller for Flight Control Design

μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementation and high computational demand due to its high order dynamics. To overcome this problem, the interaction between fuzzy logic control which is a part of intelligence control theory and μ-synthesis controller is carried out. This is called integrated fuzzy robust controller in this paper. It is obtained by coupling fuzzy pd with μ-synthesis controller through the outer loop. Using this design strategy, we can keep the system performance and robustness even a high order μ-synthesis controller is reduced into second order model. In order to test the effectiveness of this design method, the linear simulation results for a launch vehicle’s attitude control motion are presented at the end of this paper.     

声音与震动阵列的分析、实现与应用

In this paper, we consider the analysis, implementation, and application of wideband sources using both seismic and acoustic sensors. We use the approximate maximum likelihood (AML) algorithm to perform acoustic direction of arrival (DOA). For non-uniform noise spectra, whitening filtering was applied to the received acoustic signals before the AML operation. For short-range seismic DOA applications, one method was based on eigen-decomposition of the covariance matrix and a second method was based on surface wave analysis. Two well-known optimization schemes were used to estimate the source locations from the estimated DOAs at sensors of known locations. Experimental estimation of the DOAs and resulting localizations using the acoustic and seismic signals generated by striking a heavy metal plate by a hammer were reported.     

Output feedback control using reduced order models

A method is presented for designing linear output feedback controllers using reduced-order models. These reduced-order models retain only the modes that can be most affected by output feedback. A criterion for determining these modes is also derived. Examples are given to demonstrate the advantage of the proposed method over existing well-known techniques.     

New public-key cryptosystem

The development of a new public-key cryptosystem is discussed. This system is a hybrid combination of the RSA (Rivest-Shamir-Adleman) and knapsack crypto-systems. The message is encrypted in two stages using the knapsack algorithm followed by the RSA algorithm, and then decrypted in reverse order. The mathematics of the knapsack and RSA algorithms, a security analysis of the hybrid system, and a small computer simulation example are all included. The major advantages of this system, when compared with the knapsack and RSA crypto-systems, are higher speed and greater security.     

A simulation study on autonomous decentralized mechanism in fish behaviour model

The behaviour of a fish school is considered an interesting phenomenon because a fish school behaves differently in various situations. The paper considers a fish school as an autonomous decentralized system and constructs a mathematical model for the autonomous decentralized mechanism. Simulation results show that, by varying the quantity of information exchange among members in school, the present model describes fish behaviour not only for a school with fixed configuration but also for that with variable form. Furthermore, a remarkable difference in fish trajectory is found between the two schools.     

Control of a loaded induction machine using a feedforward neural network

Neural networks have been the subject of great interest in the control field. They seem to offer good ability to solve complex tasks. In this paper, some results of using a neural network for the nonlinear control of an induction machine's speed are presented. The neural controller is a feedforward neural network identified off-line. The backpropagation learning algorithm has been used for the off-line identification of the plant inverse neural model which provides the control action. Simulations under measurement noise and environmental condition variations have been investigated and comparison of performance has been made with an adaptive neural controller. The obtained results show the efficiency and the implementation simplicity of the presented strategy     

Decentralized stabilization of interconnected systems

An algorithm for the evaluation of the fixed modes of interconnected large-scale systems with respect to decentralized feedback gains is presented, as well as a procedure for the determination of decentralized stabilization and/or pole-placement feedback gains. The approach is based on eigenvalue dynamics, and closed-form expressions for eigenvalue sensitivities with respect to the decentralized feedback gains are obtained.     

Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language

Because of using traditional hand-sign segmentation and classification algorithm,many diversities of Bangla language including joint-letters,dependent vowels etc.and representing 51 Bangla written characters by using only 36 hand-signs,continuous hand-sign-spelled Bangla sign language(BdSL)recognition is challenging.This paper presents a Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language which consists of two phases.First phase is designed for hand-sign classification and the second phase is designed for Bangla language modeling algorithm(BLMA)for automatic recognition of hand-sign-spelled Bangla sign language.In first phase,we have proposed two step classifiers for hand-sign classification using normalized outer boundary vector(NOBV)and window-grid vector(WGV)by calculating maximum inter correlation coefficient(ICC)between test feature vector and pre-trained feature vectors.At first,the system classifies hand-signs using NOBV.If classification score does not satisfy specific threshold then another classifier based on WGV is used.The system is trained using 5,200 images and tested using another(5,200×6)images of 52 hand-signs from 10 signers in 6 different challenging environments achieving mean accuracy of 95.83%for classification with the computational cost of 39.972 milliseconds per frame.In the Second Phase,we have proposed Bangla language modeling algorithm(BLMA)which discovers allhidden charactersbased onrecognized charactersfrom 52 hand-signs of BdSL to make any Bangla words,composite numerals and sentences in BdSL with no training,only based on the result of first phase.To the best of our knowledge,the proposed system is the first system in BdSL designed on automatic recognition of hand-sign-spelled BdSL for large lexicon.The system is tested for BLMA using hand-sign-spelled 500 words,100 composite numerals and 80 sentences in BdSL achieving mean accuracy of 93.50%,95.50%and 90.50%respectively.     

Tests on a simply supported rhombic plate

This paper deals with tests done on a simply supported isotropic rhombic plate subjected to certain conditions of lateral loading. The loading conditions used were (i) uniformly distributed load covering the whole plate, (ii) patch load at the centre of the plate, (Hi) uniformly distributed load over a quarter of the plate. Bending moments were obtained at certain important locations on the plate, using electrical resistance strain gauges. The central deflections were also recorded. The results obtained were compared with the available theoretical results. The correlation for the case of uniformly distributed load covering the whole plate was found to be good.