EVOLUTIONARY FUZZY GUIDANCE LAW WITH SELF-ADAPTIVE REGION

Effective guidance is one of the most important tasks to the performance of air-to-air missile. The fuzzy logic controller is able to perform effectively even in situations where the information about the plant is inaccurate and the operating conditions are uncertain. Based on the proportional navigation, the fuzzy logic and the genetic algorithm are combined to develop an evolutionary fuzzy navigation law with self-adapt region for the air-to-air missile guidance. The line of sight (LOS) rate and the closing speed between the missile and the target are inputs of the fuzzy controller. The output of the fuzzy controller is the commanded acceleration. Then a nonlinear function based on the conventional fuzzy logic control is imported to change the region. This nonlinear function can be changed with the input variables. So the dynamic change of the fuzzy variable region is achieved. The guidance law is optimized by the genetic algorithm. Simulation results of air-to-air missile attack using MATLAB show that the method needs less acceleration and shorter flying time, and its realization is simple.[KH*3/4D]

阴阳平衡液防治慢性支气管炎和支气管哮喘的研究

目的 探讨防治慢性支气管炎 (慢支 )和支气管哮喘 (哮喘 )的有效药物和方法。方法 182例慢支和哮喘患者随机分成观察组和对照组 ,观察组均以阴阳平衡液为主要预防药物 ,预防用药时间每年不少于 5 0天 ,连续2年以上 ,用药方法用患者自调法 ;而对照组则采用相应的西医治疗。对阴阳平衡液的作用机制和长期毒性也进行了动物试验。结果 以阴阳平衡液预防慢支的显效率为 5 2 6 5 % ,总有效率为 90 6 3% ,阴阳平衡液加必可酮预防哮喘的显效率为 86 6 7% ,均优于单纯以西药预防的效果 (P <0 0 5 ) ;慢支和哮喘以阴阳平衡液预防治疗后 ,肺功能发生明显改善 (P <0 0 5 ) ,而对照组则无此变化。试验研究显示阴阳平衡液可增高 6 -Keto -PGF1α/TXB2值 ,且无明显毒副作用。结论 阴阳平衡液为高效低毒制剂 。

GLOBAL CONVERGENCE OF A CLASS OF OPTIMALLY CONDITIONED SSVM METHODS

This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are globally convergent for general convex functions.

Analysis and Modeling of the Central Air-Conditioning System in Intelligent Buildings

The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.

INDUCTION MOTOR SPEED CONTROL SYSTEM BASED ON FUZZY NEURAL NETWORK

A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teaching controller are described. The parameters of the membership function are regulated by an on-line learning algorithm. The speed responses of the system under the condition, where the target functions are chosen as I qs and ω, are analyzed. The system responses with the variant of parameter moment of inertial J, viscous coefficients B and torque constant K tare also analyzed. Simulation results show that the control scheme and the controller have the advantages of rapid speed response and good robustness.

Fuzzy adaptive genetic algorithm based on auto-regulating fuzzy rules

There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.

Improved adaptive filter and its application in acoustic emission signals

In order to de-noise and filter the acoustic emission(AE) signal, the adaptive filtering technology is applied to AE signal processing in view of the special attenuation characteristics of burst AE signal. According to the contradiction between the convergence speed and steady-state error of the traditional least mean square(LMS) adaptive filter, an improved LMS adaptive filtering algorithm with variable iteration step is proposed on the basis of the existing algorithms. Based on the Sigmoid function, an expression with three parameters is constructed by function translation and symmetric transformation.As for the error mutation, e(k) and e(k-1) are combined to control the change of the iteration step. The selection and adjustment process of each parameter is described in detail, and the MSE is used to evaluate the performance. The simulation results show that the proposed algorithm significantly increases the convergence speed, reduces the steady-state error, and improves the performance of the adaptive filter. The improved algorithm is applied to the AE signal processing, and the experimental signal is demodulated by an empirical mode decomposition(EMD) envelope to obtain the upper and lower envelopes. Then, the expected function related to the AE signal is established. Finally, the improved algorithm is substituted into the adaptive filter to filter the AE signal. A good result is achieved, which proves the feasibility of adaptive filtering technology in AE signal processing.

Using Adaptive Gain Scheduling LQR Method Control of Arm Driven Inverted Pendulum System Based on PIC18F4431

The arm driven inverted pendulum system is a highly nonlinear model, muhivariable and absolutely unstable dynamic system so it is very difficult to obtain exact mathematical model and balance the inverted pendulum with variable position of the ann. To solve this problem, this paper presents a mathematical model for arm driven inverted pendulum in mid-position configuration and an adaptive gain scheduling linear quadratic regulator control method for the stabilizing the inverted pendulum. The proposed controllers for arm driven inverted pendulum are simulated using MATLAB-SIMULINK and implemented on an experiment system using PIC 18F4431 mieroeontroller. The result of experiment system shows the control performance to be very good in a wide range stabilization of the arm position.

Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms

The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.

AN ADAPTIVE DIGITAL IMAGE WATERMARK ALGORITHM BASED ON GRAY-SCALE MORPHOLOGY

An adaptive digital image watermark algorithm with strong robustness based on gray-scale morphology is proposed in this paper.The embedded strategies include:The algorithm seeks and extracts adaptively the image strong texture regions.The algorithm maps the image strong texture region to the wavelet tree structures, and embeds adaptively watermark into the wavelet coefficients corresponding to the image's strong texture regions.According to the visual masking features, the algorithm adjusts adaptively the watermark-embedding intensity.Experimental results show the algorithm is robust to compression, filtering, noise as well as strong shear attacks.The algorithm is blind watermark scheme.The image strong texture region extraction method based on morphology in this algorithm is simple and effective and adaptive to various images.

A new artificial immune algorithm and its application for optimization problems

A new artificial immune algorithm （AIA） simulating the biological immune network system with selfadjustment function is proposed in this paper. AIA is based on the modified immune network model in which two methods of affinity measure evaluated are used, controlling the antibody diversity and the speed of convergence separately. The model proposed focuses on a systemic view of the immune system and takes into account cell-cell interactions denoted by antibody affinity. The antibody concentration defined in the immune network model is responsible directly for its activity in the immune system. The model introduces not only a term describing the network dynamics, but also proposes an independent term to simulate the dynamics of the antigen population. The antibodies＇ evolutionary processes are controlled in the algorithms by utilizing the basic properties of the immune network. Computational amount and effect is a pair of contradictions. In terms of this problem, the AIA regulating the parameters easily attains a compromise between them. At the same time, AIA can prevent premature convergence at the cost of a heavy computational amount （the iterative times）. Simulation illustrates that AIA is adapted to solve optimization problems, emphasizing muhimodal optimization.

A New Tuning Method for Two-Degree-of-Freedom Internal Model Control under Parametric Uncertainty

Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.

An optimal method for prediction and adjustment on gasholder level and self-provided power plant gas supply in steel works

An optimal method for prediction and adjustment on byproduct gasholder level and self-provided power plant gas supply was proposed.This work raises the HP-ENN-LSSVM model based on the Hodrick-Prescott filter,Elman neural network and least squares support vector machines.Then,according to the prediction,the optimal adjustment process came up by a novel reasoning method to sustain the gasholder within safety zone and the self-provided power plant boilers in economic operation,and prevent unfavorable byproduct gas emission and equipment trip as well.The experiments using the practical production data show that the proposed method achieves high accurate predictions and the optimal byproduct gas distribution,which provides a remarkable guidance for reasonable scheduling of byproduct gas.

The Model of Speaking in Teaching Indonesian to Foreign Speakers Based on Self-Regulated Learning and Anxiety Reduction Approaches

Model for spoken is expected to overcome difficulties in teaching and learning Indonesian language for foreign speakers. Language anxiety is the anxiety that arises when a person learns foreign language. Foreign Language Anxiety （anxiety to learn a foreign language） is of concern or negative emotional reactions that arise when studying or using foreign language. Self-regulated learning is an active and constructive process undertaken by learners in setting goals for their learning and trying to monitor, regulate, and control of cognition, motivation, and behavior, then everything is directed and driven by purpose and adapted to the context and environment. The research method used is an R and D （research and development） method with a sample of foreign speakers of Chinese. Variables that receive interference are the ability to speak in Indonesian, while the variables used to interfere with the self-regulated learning and language anxiety as a variable controller. Intrapersonal factors become barriers that cause stuttering speech limited due to the mastering subject content. On the basis of that, this speaking model applies the principle of self-regulated learning in the learning process, using a communicative and contextual approach. This model intended for foreign speakers who learn Indonesian language outside of Indonesia, so to bring the atmosphere mandated in sociolinguistic built through media and relevant teaching methods.

Steering Multiple Reverse Current into Unidirectional Current in Deterministic Ratchets

Recent investigations have shown that with varying the amplitude of the external force, the deterministic ratchets exhibit multiple current reversals, which are undesirable in certain circumstances. To control the multiple reverse current to unidirectional current, an adaptive control law is presented inspired from the relation between multiple reversaJs current and the chaos-periodic/quasiperiodic transition of the transport velocity. The designed controller can stabilize the transport velocity of ratchets to steady state and suppress any chaos-periodic/quasiperiodic transition, namely, the stable transport in ratchets is achieved, which makes the current sign unchanged.

Joint detection method of pornographic images with skin-like color background

A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： the first one is to quickly detect the potential human skin-color regions; and the second one is to use an off-the-shelf face detector to locate a human face and then apply hypothesis testing based on series of assumptions which take into account the face-height ratio, body orientation and modem photograph composition common sense, etc. After that, a template matching method is used to further discriminate normal images or pornographic ones. Experimental results show that the proposed method has high precision and real time speed.

Climate Change Impacts and Adaptation Strategies in Kenya

To determine the climate changes that are due to natural variability and those due to human activities is quite challenging,just like delineating the impacts.Moreover,it is equally difficult to ascertain the adaptive strategies for coping with the climate changes and in particular for developing countries like Kenya.While climate change is a global phenomenon,the impacts are more or less specific to local areas such as observed in Kenyan case.Therefore climate change impacts adaptation strategies are appropriately applicable to a given local perspective.The study investigated the main indicators of climate change and effective adaptive strategies that can be employed in Kenya.Based on online questionnaire survey,the study established unpredictable rainfall patterns as the major indicator of climate change in the country,while water harvesting and change of cropping methods are the best adaptive strategies.

An Adaptive Genetic Algorithm for Multiprocessor Real-time Task Scheduling

Real-time task scheduling is of primary significance in multiprocessor systems.Meeting deadlines and achieving high system utilization are the two main objectives of task scheduling in such systems.In this paper,we represent those two goals as the minimization of the average response time and the average task laxity.To achieve this,we propose a genetic-based algorithm with problem-specific and efficient genetic operators.Adaptive control parameters are also employed in our work to improve the genetic algorithms' efficiency.The simulation results show that our proposed algorithm outperforms its counterpart considerably by up to 36% and 35% in terms of the average response time and the average task laxity,respectively.

自身调节防治近视法的探讨和应用

“自身调节防治近视法”实验研究表明，实验组的防治假性近视有效率高于眼保健操对照组，其差别具有统计学意义（P＜0．05）。神经功能检测表明，该方法不仅无任何副作用，且“静能益智”。通过对微循环，心功能，皮肤温度等检测，发现该方法能促使人体发生一系列的生理变化。该方法具有科学性、先进性、实用性，表明确有切实可行的应用价值。

Mechanism of Integrative Body-Mind Training

Integrative Body-Mind Training（IBMT） originates from ancient Eastern tradition.The method stresses no effort to control thoughts,but instead a state of restful alertness that allows a high degree of awareness of the body,breathing,and external instructions.A series of studies indicates that IBMT improves attention and self-regulation through interaction between the central（brain） and the autonomic（body） nervous systems.The present review mainly summarizes the recent results of IBMT studies and proposes how it changes the state of brain and body to lead to positive outcomes.Future directions in this field are also discussed.