Search results for: control function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5548

Search results for: control function

5308 Estimating of the Renewal Function with Heavy-tailed Claims

Authors: Rassoul Abdelaziz

Abstract:

We develop a new estimator of the renewal function for heavy-tailed claims amounts. Our approach is based on the peak over threshold method for estimating the tail of the distribution with a generalized Pareto distribution. The asymptotic normality of an appropriately centered and normalized estimator is established, and its performance illustrated in a simulation study.

Keywords: Renewal function, peak-over-threshold, POT method, extremes value, generalized pareto distribution, heavy-tailed distribution.

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5307 Determination of Q and R Matrices for Optimal Pitch Aircraft Control

Authors: N. Popovich, P. Yan

Abstract:

In this paper, the process of obtaining Q and R matrices for optimal pitch aircraft control system has been described. Since the innovation of optimal control method, the determination of Q and R matrices for such system has not been fully specified. The value of Q and R for optimal pitch aircraft control application, have been simulated and calculated. The suitable results for Q and R have been observed through the performance index (PI). If the PI is small “enough", we would say the Q & R values are suitable for that certain type of optimal control system. Moreover, for the same value of PI, we could have different Q and R sets. Due to the rule-free determination of Q and R matrices, a specific method is brought to find out the rough value of Q and R referring to rather small value of PI.

Keywords: Aircraft, control, digital, optimal, Q and R matrices

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5306 Retaining Structural System Active Vibration Control

Authors: Ming-Hui Lee, Shou-Jen Hsu

Abstract:

This study presents an active vibration control technique to reduce the earthquake responses of a retained structural system. The proposed technique is a synthesis of the adaptive input estimation method (AIEM) and linear quadratic Gaussian (LQG) controller. The AIEM can estimate an unknown system input online. The LQG controller offers optimal control forces to suppress wall-structural system vibration. The numerical results show robust performance in the active vibration control technique.

Keywords: Active vibration control, AIEM, LQG, Optimal control

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5305 A Wireless Feedback Control System as a Base of Bio-Inspired Structure System to Mitigate Vibration in Structures

Authors: Gwanghee Heo, Geonhyeok Bang, Chunggil Kim, Chinok Lee

Abstract:

This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system.

Keywords: Structural vibration control, wireless system, MR damper, feedback control, embedded system.

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5304 Statistical Reliability Based Modeling of Series and Parallel Operating Systems using Extreme Value Theory

Authors: Mohamad Mahdavi, Mojtaba Mahdavi

Abstract:

This paper tries to represent a new method for computing the reliability of a system which is arranged in series or parallel model. In this method we estimate life distribution function of whole structure using the asymptotic Extreme Value (EV) distribution of Type I, or Gumbel theory. We use EV distribution in minimal mode, for estimate the life distribution function of series structure and maximal mode for parallel system. All parameters also are estimated by Moments method. Reliability function and failure (hazard) rate and p-th percentile point of each function are determined. Other important indexes such as Mean Time to Failure (MTTF), Mean Time to repair (MTTR), for non-repairable and renewal systems in both of series and parallel structure will be computed.

Keywords: Reliability, extreme value, parallel, series, lifedistribution

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5303 Transfer Function of Piezoelectric Material

Authors: C. Worakitjaroenphon, A. Oonsivilai

Abstract:

The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.

Keywords: Piezoelectric, Stability, S-Domain, Transfer function

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5302 An Approximate Lateral-Torsional Buckling Mode Function for Cantilever I-Beams

Authors: H. Ozbasaran

Abstract:

Lateral torsional buckling is a global buckling mode which should be considered in design of slender structural members under flexure about their strong axis. It is possible to compute the load which causes lateral torsional buckling of a beam by finite element analysis, however, closed form equations are needed in engineering practice for calculation ease which can be obtained by using energy method. In lateral torsional buckling applications of energy method, a proper function for the critical lateral torsional buckling mode should be chosen which can be thought as the variation of twisting angle along the buckled beam. Accuracy of the results depends on how close is the chosen function to the exact mode. Since critical lateral torsional buckling mode of the cantilever I-beams varies due to material properties, section properties and loading case, the hardest step is to determine a proper mode function in application of energy method. This paper presents an approximate function for critical lateral torsional buckling mode of doubly symmetric cantilever I-beams. Coefficient matrices are calculated for concentrated load at free end, uniformly distributed load and constant moment along the beam cases. Critical lateral torsional buckling modes obtained by presented function and exact solutions are compared. It is found that the modes obtained by presented function coincide with differential equation solutions for considered loading cases.

Keywords: Buckling mode, cantilever, lateral-torsional buckling, I-beam.

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5301 Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart

Authors: Y. Areepong

Abstract:

The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).

Keywords: Average Run Length1, Optimal parameters, Exponentially Weighted Moving Average (EWMA) control chart.

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5300 The Control Vector Scheme for Design of Planar Primitive PH curves

Authors: Ching-Shoei Chiang, Sheng-Hsin Tsai, James Chen

Abstract:

The PH curve can be constructed by given parameters, but the shape of the curve is not so easy to image from the value of the parameters. On the contract, Bézier curve can be constructed by the control polygon, and from the control polygon, we can image the figure of the curve. In this paper, we want to use the hodograph of Bézier curve to construct PH curve by selecting part of the control vectors, and produce other control vectors, so the property of PH curve exists.

Keywords: PH curve, hodograph, Bézier curve.

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5299 Estimation of Bayesian Sample Size for Binomial Proportions Using Areas P-tolerance with Lowest Posterior Loss

Authors: H. Bevrani, N. Najafi

Abstract:

This paper uses p-tolerance with the lowest posterior loss, quadratic loss function, average length criteria, average coverage criteria, and worst outcome criterion for computing of sample size to estimate proportion in Binomial probability function with Beta prior distribution. The proposed methodology is examined, and its effectiveness is shown.

Keywords: Bayesian inference, Beta-binomial Distribution, LPLcriteria, quadratic loss function.

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5298 Iterative Learning Control of Two Coupled Nonlinear Spherical Tanks

Authors: A. R. Tavakolpour-Saleh, A. R. Setoodeh, E. Ansari

Abstract:

This paper presents modeling and control of a highly nonlinear system including, non-interacting two spherical tanks using iterative learning control (ILC). Consequently, the objective of the paper is to control the liquid levels in the nonlinear tanks. First, a proportional-integral-derivative (PID) controller is applied to the plant model as a suitable benchmark for comparison. Then, dynamic responses of the control system corresponding to different step inputs are investigated. It is found that the conventional PID control is not able to fulfill the design criteria such as desired time constant. Consequently, an iterative learning controller is proposed to accurately control the coupled nonlinear tanks system. The simulation results clearly demonstrate the superiority of the presented ILC approach over the conventional PID controller to cope with the nonlinearities presented in the dynamic system.

Keywords: Iterative learning control, spherical tanks, nonlinear system.

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5297 Periodic Control of a Reverse Osmosis Water Desalination Unit

Authors: Ali Emad

Abstract:

Enhancement of the performance of a reverse osmosis (RO) unit through periodic control is studied. The periodic control manipulates the feed pressure and flow rate of the RO unit. To ensure the periodic behavior of the inputs, the manipulated variables (MV) are transformed into the form of sinusoidal functions. In this case, the amplitude and period of the sinusoidal functions become the surrogate MV and are thus regulated via nonlinear model predictive control algorithm. The simulation results indicated that the control system can generate cyclic inputs necessary to enhance the closedloop performance in the sense of increasing the permeate production and lowering the salt concentration. The proposed control system can attain its objective with arbitrary set point for the controlled outputs. Successful results were also obtained in the presence of modeling errors.

Keywords: Reverse osmosis, water desalination, periodic control, model predictive control.

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5296 Tuning of Power System Stabilizers in a Multi- Machine Power System using C-Catfish PSO

Authors: M. H. Moradi, S. M. Moosavi, A. R. Reisi

Abstract:

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The proposed algorithm is evaluated on a two-area, 4- machines system. The robustness of the proposed algorithm is verified on this system under different operating conditions and applying a three-phase fault. The nonlinear time-domain simulation results and some performance indices show the effectiveness of the proposed controller in damping power system oscillations and this novel optimization algorithm is compared with particle swarm optimization (PSO).

Keywords: Power system stabilizer, C-Catfish PSO, ITAE objective function, Power system control, Multi-machine power system

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5295 Jitter Transfer in High Speed Data Links

Authors: Tsunwai Gary Yip

Abstract:

Phase locked loops for data links operating at 10 Gb/s or faster are low phase noise devices designed to operate with a low jitter reference clock. Characterization of their jitter transfer function is difficult because the intrinsic noise of the device is comparable to the random noise level in the reference clock signal. A linear model is proposed to account for the intrinsic noise of a PLL. The intrinsic noise data of a PLL for 10 Gb/s links is presented. The jitter transfer function of a PLL in a test chip for 12.8 Gb/s data links was determined in experiments using the 400 MHz reference clock as the source of simultaneous excitations over a wide range of frequency. The result shows that the PLL jitter transfer function can be approximated by a second order linear model.

Keywords: Intrinsic phase noise, jitter in data link, PLL jitter transfer function, high speed clocking in electronic circuit

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5294 Knowledge Discovery from Production Databases for Hierarchical Process Control

Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

Abstract:

The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: Hierarchical process control, knowledge discovery from databases, neural network.

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5293 Stabilization of Rotational Motion of Spacecrafts Using Quantized Two Torque Inputs Based on Random Dither

Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara

Abstract:

The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.

Keywords: Spacecraft control, quantized control, nonlinear control, random dither method.

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5292 Identification of Nonlinear Systems Using Radial Basis Function Neural Network

Authors: C. Pislaru, A. Shebani

Abstract:

This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the KMeans clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: System identification, Nonlinear system, Neural networks, RBF neural network.

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5291 In Silico Analysis of Pax6 Interacting Proteins Indicates Missing Molecular Links in Development of Brain and Associated Disease

Authors: Ratnakar Tripathi, Rajnikant Mishra

Abstract:

The PAX6, a transcription factor, is essential for the morphogenesis of the eyes, brain, pituitary and pancreatic islets. In rodents, the loss of Pax6 function leads to central nervous system defects, anophthalmia, and nasal hypoplasia. The haplo-insufficiency of Pax6 causes microphthalmia, aggression and other behavioral abnormalities. It is also required in brain patterning and neuronal plasticity. In human, heterozygous mutation of Pax6 causes loss of iris [aniridia], mental retardation and glucose intolerance. The 3- deletion in Pax6 leads to autism and aniridia. The phenotypes are variable in peneterance and expressivity. However, mechanism of function and interaction of PAX6 with other proteins during development and associated disease are not clear. It is intended to explore interactors of PAX6 to elucidated biology of PAX6 function in the tissues where it is expressed and also in the central regulatory pathway. This report describes In-silico approaches to explore interacting proteins of PAX6. The models show several possible proteins interacting with PAX6 like MITF, SIX3, SOX2, SOX3, IPO13, TRIM, and OGT. Since the Pax6 is a critical transcriptional regulator and master control gene of eye and brain development it might be interacting with other protein involved in morphogenesis [TGIF, TGF, Ras etc]. It is also presumed that matricelluar proteins [SPARC, thrombospondin-1 and osteonectin etc] are likely to interact during transport and processing of PAX6 and are somewhere its cascade. The proteins involved in cell survival and cell proliferation can also not be ignored.

Keywords: Interacting Proteins, Pax6, PIP, STRING

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5290 Application of Adaptive Genetic Algorithm in Function Optimization

Authors: Panpan Xu, Shulin Sui

Abstract:

The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.

Keywords: Genetic algorithm, Adaptive genetic algorithm, Function optimization.

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5289 Comparison of Proportional Control and Fuzzy Logic Control to Develop an Ideal Thermoelectric Renal Hypothermia System

Authors: Hakan Işık, Esra Saraçoğlu

Abstract:

In this study, a comparison of two control methods, Proportional Control (PC) and Fuzzy Logic Control (FLC), which have been used to develop an ideal thermoelectric renal hypothermia system in order to use in renal surgery, has been carried out. Since the most important issues in long-lasting parenchymatous renal surgery are to provide an operation medium free of blood and to prevent renal dysfunction in the postoperative period, control of the temperature has become very important in renal surgery. The final product is seriously affected from the changes in temperature, therefore, it is necessary to reach some desired temperature points quickly and avoid large overshoot. PIC16F877 microcontroller has been used as controller for both of these two methods. Each control method can simply ensure extra renal hypothermia in the targeted way. But investigation of advantages and disadvantages of every control method to each other is aimed and carried out by the experimental implementations. Shortly, investigation of the most appropriate method to use for development of system and that can be applied to people safely in the future, has been performed. In this sense, experimental results show that fuzzy logic control gives out more reliable responses and efficient performance.

Keywords: renal hypothermia, renal cooling, temperature control, proportional control fuzzy logic control

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5288 Phase Jitter Transfer in High Speed Data Links

Authors: Tsunwai Gary Yip

Abstract:

Phase locked loops in 10 Gb/s and faster data links are low phase noise devices. Characterization of their phase jitter transfer functions is difficult because the intrinsic noise of the PLLs is comparable to the phase noise of the reference clock signal. The problem is solved by using a linear model to account for the intrinsic noise. This study also introduces a novel technique for measuring the transfer function. It involves the use of the reference clock as a source of wideband excitation, in contrast to the commonly used sinusoidal excitations at discrete frequencies. The data reported here include the intrinsic noise of a PLL for 10 Gb/s links and the jitter transfer function of a PLL for 12.8 Gb/s links. The measured transfer function suggests that the PLL responded like a second order linear system to a low noise reference clock.

Keywords: Intrinsic phase noise, jitter in data link, PLL jitter transfer function, high speed clocking in electronic circuit

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5287 Use of Vegetation and Geo-Jute in Erosion Control of Slopes in a Sub-Tropical Climate

Authors: Mohammad Shariful Islam, Shamima Nasrin, Md. Shahidul Islam, Farzana Rahman Moury

Abstract:

Protection of slope and embankment from erosion has become an important issue in Bangladesh. The constructions of strong structures require large capital, integrated designing, high maintenance cost. Strong structure methods have negative impact on the environment and sometimes not function for the design period. Plantation of vetiver system along the slopes is an alternative solution. Vetiver not only serves the purpose of slope protection but also adds green environment reducing pollution. Vetiver is available in almost all the districts of Bangladesh. This paper presents the application of vetiver system with geo-jute, for slope protection and erosion control of embankments and slopes. In-situ shear tests have been conducted on vetiver rooted soil system to find the shear strength. The shear strength and effective soil cohesion of vetiver rooted soil matrix are respectively 2.0 times and 2.1 times higher than that of the bared soil. Similar trends have been found in direct shear tests conducted on laboratory reconstituted samples. Field trials have been conducted in road embankment and slope protection with vetiver at different sites. During the time of vetiver root growth the soil protection has been accomplished by geo-jute. As the geo-jute degrades with time, vetiver roots grow and take over the function of geo-jutes. Slope stability analyses showed that vegetation increase the factor of safety significantly.

Keywords: Erosion, geo-jute, green technology, vegetation.

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5286 Generalized Predictive Control of Batch Polymerization Reactor

Authors: R. Khaniki, M.B. Menhaj, H. Eliasi

Abstract:

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.

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5285 Generalized Predictive Control of Batch Polymerization Reactor

Authors: R. Khaniki, M.B. Menhaj, H. Eliasi

Abstract:

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.

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5284 Training Radial Basis Function Networks with Differential Evolution

Authors: Bing Yu , Xingshi He

Abstract:

In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.

Keywords: differential evolution, neural network, Rbf function

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5283 Aerobic Bioprocess Control Using Artificial Intelligence Techniques

Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: Bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques.

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5282 Computer Simulations of an Augmented Automatic Choosing Control Using Automatic Choosing Functions of Gradient Optimization Type

Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) using the automatic choosing functions of gradient optimization type for nonlinear systems. Constant terms which arise from sectionwise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics. Parameters included in the control are suboptimally selected by minimizing the Hamiltonian 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.

Keywords: augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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5281 The Decentralized Nonlinear Controller of Robot Manipulator with External Load Compensation

Authors: Sun Lim, Il-Kyun Jung

Abstract:

This paper describes a newly designed decentralized nonlinear control strategy to control a robot manipulator. Based on the concept of the nonlinear state feedback theory and decentralized concept is developed to improve the drawbacks in previous works concerned with complicate intelligent control and low cost effective sensor. The control methodology is derived in the sense of Lyapunov theorem so that the stability of the control system is guaranteed. The decentralized algorithm does not require other joint angle and velocity information. Individual Joint controller is implemented using a digital processor with nearly actuator to make it possible to achieve good dynamics and modular. Computer simulation result has been conducted to validate the effectiveness of the proposed control scheme under the occurrence of possible uncertainties and different reference trajectories. The merit of the proposed control system is indicated in comparison with a classical control system.

Keywords: Robot manipulator control, nonlinear controller, Lyapunov based stability, Interconnection compensation.

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5280 Digital Automatic Gain Control Integrated on WLAN Platform

Authors: Emilija Miletic, Milos Krstic, Maxim Piz, Michael Methfessel

Abstract:

In this work we present a solution for DAGC (Digital Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4 GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used enables gain control over Low Noise Amplifier (LNA) and a Variable Gain Amplifier (VGA). The control over those signals is performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the average power of the baseband signal close to the desired set point. DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and actual gain setting, adjusting a gain factor of the accumulation, and applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.

Keywords: WLAN, AGC, RSSI, baseband processor

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5279 Riemann-Liouville Fractional Calculus and Multiindex Dzrbashjan-Gelfond-Leontiev Differentiation and Integration with Multiindex Mittag-Leffler Function

Authors: U.K. Saha, L.K. Arora

Abstract:

The multiindex Mittag-Leffler (M-L) function and the multiindex Dzrbashjan-Gelfond-Leontiev (D-G-L) differentiation and integration play a very pivotal role in the theory and applications of generalized fractional calculus. The object of this paper is to investigate the relations that exist between the Riemann-Liouville fractional calculus and multiindex Dzrbashjan-Gelfond-Leontiev differentiation and integration with multiindex Mittag-Leffler function.

Keywords: Multiindex Mittag-Leffler function, Multiindex Dzrbashjan-Gelfond-Leontiev differentiation and integration, Riemann-Liouville fractional integrals and derivatives.

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