Search results for: fast prediction model

Authors: M. Rychlik, R. Roszak, M. Morzynski, M. Nowak, H. Hausa, K. Kotecki

Abstract:

Article presents the geometry and structure reconstruction procedure of the aircraft model for flatter research (based on the I22-IRYDA aircraft). For reconstruction the Reverse Engineering techniques and advanced surface modeling CAD tools are used. Authors discuss all stages of data acquisition process, computation and analysis of measured data. For acquisition the three dimensional structured light scanner was used. In the further sections, details of reconstruction process are present. Geometry reconstruction procedure transform measured input data (points cloud) into the three dimensional parametric computer model (NURBS solid model) which is compatible with CAD systems. Parallel to the geometry of the aircraft, the internal structure (structural model) are extracted and modeled. In last chapter the evaluation of obtained models are discussed.

Keywords: computer modeling, numerical simulation, Reverse Engineering, structural model

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Authors: Yung-Yuan Hsu

Abstract:

The primary objective of this paper was to construct a “kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools.

Keywords: Three-axis machine tool, Geometric error, HTM, Error measuring

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: M. A. Serag-Eldin

Abstract:

The paper presents the results of simple measurements conducted on a model of a wind-driven venturi-type room ventilator. The ventilator design is new and was developed employing mathematical modeling. However, the computational model was not validated experimentally for the particular application considered. The paper presents the performance of the ventilator model under laboratory conditions, for five different wind tunnel speeds. The results are used to both demonstrate the effectiveness of the new design and to validate the computational model employed to develop it.

Keywords: Venturi-flow, ventilation, Wind-energy, Wind flow.

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Authors: Ali Taee Zade, Siamak Rasulzadeh, Reza Torkashvan

Abstract:

Although Model Driven Architecture has taken successful steps toward model-based software development, this approach still faces complex situations and ambiguous questions while applying to real world software systems. One of these questions - which has taken the most interest and focus - is how model transforms between different abstraction levels, MDA proposes. In this paper, we propose an approach based on Story Driven Modeling and Aspect Oriented Programming to ease these transformations. Service Oriented Architecture is taken as the target model to test the proposed mechanism in a functional system. Service Oriented Architecture and Model Driven Architecture [1] are both considered as the frontiers of their own domain in the software world. Following components - which was the greatest step after object oriented - SOA is introduced, focusing on more integrated and automated software solutions. On the other hand - and from the designers' point of view - MDA is just initiating another evolution. MDA is considered as the next big step after UML in designing domain.

Keywords: SOA, MDA, SDM, Model Transformation, Middleware Transparency, Aspects and Jini.

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Authors: Azlina Abu Bakar, Abdul Fatah Wan Sidek

Abstract:

Well-being has been given special emphasis in quality of life. It involves living a meaningful, life satisfaction, stability and happiness in life. Well-being also concerns the satisfaction of physical, psychological, social needs and demands of an individual. The purpose of this study was to validate three-factor measurement model of well-being using structural equation modeling (SEM). The conceptions of well-being measured such dimensions as physical, psychological and social well-being. This study was done based on a total sample of 650 adolescents from east-coast of peninsular Malaysia. The Well-Being Scales which was adapted from [1] was used in this study. The items were hypothesized a priori to have nonzero loadings on all dimensions in the model. The findings of the SEM demonstrated that it is a good fitting model which the proposed model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998; TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR) was .93 and average variance extracted (AVE) was 58%. The model in this study fits with the sample of data and well-being is important to bring sustainable development to the mainstream.

Keywords: Adolescence, Structural Equation Modeling, Sustainable Development, Well-Being.

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Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

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The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate.

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Authors: Lenka Krulikovská, Jaroslav Polec

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In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.

Keywords: Abrupt cut, shot cut detection, adaptive threshold.

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Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca

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This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.

Keywords: Transshipment model, mixed integer programming, saving algorithm, dry freight transportation.

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision making, management and planning of healthcare and related activities. However, user resistances, unique position of medical data content and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. Success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose a HA process model with features from rational unified process (RUP) model and agile methodology.

Keywords: Agile methodology, health analytics, unified process model, UML.

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Authors: A. Amar, O. Hemeda

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A study of the structure of the nucleus with the analogy by solid-state physics has been developed. We have used binding energy to calculate R (a parameter that is proportional to the radius of the nucleus) for deuteron, alpha, and ⁸Be. The calculated parameter r calculated from solid state physics produces a probe for calculation the nuclear radii. ⁸Be has special attention as it is radioactive nucleus and the latest nucleus to be calculated from crystalline model approach. The distribution of nucleons inside the nucleus is taken to be tetrahedral for ¹⁶O. The model has failed to expect the radius of ⁹Be which is an impression about the modification should be done on the model at near future. A comparison between our calculations and those from literature has been made, and a good agreement has been obtained.

Keywords: The structure of the nucleus, binding energy, crystalline model approach, nuclear radii, tetrahedral for 16O.

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Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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Authors: M. Palanivel, R. Uthayakumar

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In this paper, Economic Order Quantity (EOQ) based model for non-instantaneous Weibull distribution deteriorating items with power demand pattern is presented. In this model, the holding cost per unit of the item per unit time is assumed to be an increasing linear function of time spent in storage. Here the retailer is allowed a trade-credit offer by the supplier to buy more items. Also in this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This model aids in minimizing the total inventory cost by finding the optimal time interval and finding the optimal order quantity. The optimal solution of the model is illustrated with the help of numerical examples. Finally sensitivity analysis and graphical representations are given to demonstrate the model.

Keywords: Power demand pattern, Partial backlogging, Time dependent holding cost, Trade credit, Weibull deterioration.

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Authors: Heung Sun Yoon, Jong Tae Kim

Abstract:

In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption. We can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: Activity diagram, automotive, braking system, double-loop, Self-adaptive, UML, vehicle.

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Authors: Mehdi Kheradmand, Mehdi Azhdary Moghaddam, Abdolreza Zahiri, Khalil Ghorbani

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This research compares results of major methods of determining the flow discharge using experimental relationships with results from the M5 decision tree model in meandering compound sections in several laboratory channels. It was found that the M5 decision tree model enjoyed greater accuracy of statistical parameters compared to methods to the said methods. This suggested that the M5 decision tree model has highly improved the calculated accuracy of the flow discharge in meandering compound channels.

Keywords: Stage-discharge relationship, M5 decision tree model, compound section, meandering compound channel.

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Authors: Rishabh Garg

Abstract:

Blockchain technology can allow remote, untrusted parties in the banking and financial sector to reach consensus on the state of databases without the involvement of gatekeepers. Like a bookkeeper, it can manage all financial transactions including payments, settlements, fundraising, securities management, loans, credits and trade finance. It can outperform existing systems in terms of identity verification, asset transfers, peer-to-peer transfers, hedge funds, security and auditability. Blockchain-based decentralized finance (DeFi) is a new financial protocol. Being open and programmable, it enables various DeFi use-cases, including asset management, tokenization, tokenized derivatives, decentralized autonomous organizations, data analysis and valuation, payments, lending and borrowing, insurance, margin trading, prediction market, gambling and yield-farming, etc. In addition, it can ease financial transactions, cash-flow, use of programmable currency, no-loss lotteries, etc. This paper aims to assess the potential of decentralized finance by leveraging the blockchain-enabled Ethereum platform as an alternative to traditional finance. The study also aims to find out the impact of decentralized finance on prediction markets, quadratic funding and crowd-funding, together with the potential challenges and solutions associated with its implementation.

Keywords: Advance trading, crowd funding, exchange tokens, fund aggregation, margin trading, quadratic funding, smart contracts, streaming money, token derivatives.

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Authors: Erik Delarue, David Bekaert, Ronnie Belmans, William D'haeseleer

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This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.

Keywords: Electricity generation modeling, Unit Commitment(UC), Mixed Integer Linear Programming (MILP), DC load flow.

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Authors: János Levendovszky, András Oláh

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In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.

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Authors: T.C.Manjunath, C. Ardil

Abstract:

This paper deals with the development of a Jacobean model for a 4-axes indigenously developed scara robot arm in the laboratory. This model is used to study the relation between the velocities and the forces in the robot while it is doing the pick and place operation.

Keywords: SCARA, Jacobean, Tool Configuration Vector, Computer Control , Visual Basic , Interfacing , Drivers,

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Authors: Liu Shu, Dong Shangjia

Abstract:

Our goal is to effectively increase the number of boats in the river during a six month period. The main factors of determining the number of boats are duration and “select the priority trip". In the microcosmic simulation model, the best result is 4 to 24 nights with DSCF, and the number of boats is 812 with an increasing ratio of 9.0% related to the second best result. However, the number of boats is related to 31.6% less than the best one in 6 to 18 nights with FCFS. In the discrete duration model, we get from 6 to 18 nights, the numbers of boats have increased to 848 with an increase ratio of 29.7% than the best result in model I for the same time range. Moreover, from 4 to 24 nights, the numbers of boats have increase to 1194 with an increase ratio of 47.0% than the best result in model I for the same time range.

Keywords: Discrete duration model, “select the priority trip”, microcosmic simulation model.

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Authors: Muh. Hisjam, Nancy Oktyajati, Wakhid A. Jauhari, Wahyudi Sutopo

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This research is intended to develop a raw material allocation model in timber processing industry in Perum Perhutani Unit I, Central Java, Indonesia. The model can be used to determine the quantity of allocation of timber between chain in the supply chain to select supplier considering factors that are log price and the distance. In determining the quantity of allocation of timber between chains in the supply chain, the model considers the optimal inventory in each chain. Whilst the optimal inventory is determined based on demand forecast, the capacity and safety stock. Problem solving allocation is conducted by developing linear programming model that aims to minimize the total cost of the purchase, transportation cost and storage costs at each chain. The results of numerical examples show that the proposed model can generate savings of the purchase cost of 20.84% and select suppliers with mileage closer.

Keywords: Allocation model, linear programming, purchase costs, storage costs, suppliers, transportation costs.

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Authors: Kai Wang, Yanling Zu

Abstract:

By utilizing the comparison theorem and Lyapunov second method, some sufficient conditions for the permanence and global attractivity of positive periodic solution for a predator-prey model with mutual interference m ∈ (0, 1) and delays τi are obtained. It is the first time that such a model is considered with delays. The significant is that the results presented are related to the delays and the mutual interference constant m. Several examples are illustrated to verify the feasibility of the results by simulation in the last part.

Keywords: Predator-prey model, Mutual interference, Delays, Permanence, Global attractivity

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Authors: H. Pahlavanzadeh, A.R.Jahangiri, I. Noshadi

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In this paper, the solubility of CO2 in AMP solution have been measured at temperature range of ( 293, 303 ,313,323) K.The amine concentration ranges studied are (2.0, 2.8, and 3.4) M. A solubility apparatus was used to measure the solubility of CO2 in AMP solution on samples of flue gases from Thermal and Central Power Plants of Esfahan Steel Company. The modified Kent Eisenberg model was used to correlate and predict the vapor-liquid equilibria of the (CO2 + AMP + H2O) system. The model predicted results are in good agreement with the experimental vapor-liquid equilibrium measurements.

Keywords: AMP, Carbon dioxide; loading, Flue gases, Modified Kent Eisenberg model

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Authors: A. Zanj, F. He

Abstract:

In the current paper, a domain independent conduction model compatible for multi-physical system dynamic investigations is suggested. By means of a port-based approach, a classical nonlinear conduction model containing physical states is first represented. A compatible discrete configuration of the thermal domain in line with the elastic domain is then generated through the enhancement of the configuration of the conventional thermal element. The presented simulation results of a sample structure indicate that the suggested conductive model can cover a wide range of dynamic behavior of the thermal domain.

Keywords: Multi-physical domain, conduction model, port-based modeling, dynamic interaction, physical modeling.

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Authors: Kyoungwoo Park, Byeong Sam Kim, Juhee Lee, Kwang Soo Kim

Abstract:

The Prediction of aerodynamic characteristics and shape optimization of airfoil under the ground effect have been carried out by integration of computational fluid dynamics and the multiobjective Pareto-based genetic algorithm. The main flow characteristics around an airfoil of WIG craft are lift force, lift-to-drag ratio and static height stability (H.S). However, they show a strong trade-off phenomenon so that it is not easy to satisfy the design requirements simultaneously. This difficulty can be resolved by the optimal design. The above mentioned three characteristics are chosen as the objective functions and NACA0015 airfoil is considered as a baseline model in the present study. The profile of airfoil is constructed by Bezier curves with fourteen control points and these control points are adopted as the design variables. For multi-objective optimization problems, the optimal solutions are not unique but a set of non-dominated optima and they are called Pareto frontiers or Pareto sets. As the results of optimization, forty numbers of non- dominated Pareto optima can be obtained at thirty evolutions.

Keywords: Aerodynamics, Shape optimization, Airfoil on WIGcraft, Genetic algorithm, Computational fluid dynamics (CFD).

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Yenni Anggrayni

Abstract:

The lack of awareness of the significant prevalence of school absenteeism in Indonesia, which ultimately results in high rates of school dropouts, is an unresolved issue. Therefore, this study aims to investigate the root causes of chronic absenteeism qualitatively and quantitatively using the bioecological systems paradigm in secondary schools for any reason. This study used an open-ended questionnaire to collect data from 1,148 students in six West Java Province districts/cities. Univariate and stepwise multiple logistic regression analyses produced a prediction model for the components. Analysis results show that poor teacher-student relationships, bullying by peers or teachers, negative perception of education, and lack of parental involvement in learning activities are the leading causes of chronic absenteeism. Another finding is to promote home-school partnerships to improve school climate and parental involvement in learning to address chronic absenteeism.

Keywords: Bullying, chronic absenteeism, dropout of school, home-school partnerships, parental involvement.

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Authors: Sepideh Fazeli, Fariba Bahrami

Abstract:

Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.

Keywords: Brain modeling, computer models, language acquisition, reinforcement learning.

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Authors: Spiros Mazarakis, George Matzavinos, Peter P. Groumpos

Abstract:

Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed

Keywords: Macroeconomic Models, Mamdani Rule Based- FCMs(MBFCMs), Qualitative and Dynamics System, Simulation.

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Authors: Sufian Ashraf Mazhari, Surendra Kumar

Abstract:

Robot manipulators are highly coupled nonlinear systems, therefore real system and mathematical model of dynamics used for control system design are not same. Hence, fine-tuning of controller is always needed. For better tuning fast simulation speed is desired. Since, Matlab incorporates LAPACK to increase the speed and complexity of matrix computation, dynamics, forward and inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in such a way that all operations are matrix based which give very less simulation time. This paper compares PID parameter tuning using Genetic Algorithm, Simulated Annealing, Generalized Pattern Search (GPS) and Hybrid Search techniques. Controller performances for all these methods are compared in terms of joint space ITSE and cartesian space ISE for tracking circular and butterfly trajectories. Disturbance signal is added to check robustness of controller. GAGPS hybrid search technique is showing best results for tuning PID controller parameters in terms of ITSE and robustness.

Keywords: Controller Tuning, Genetic Algorithm, Pattern Search, Robotic Controller, Simulated Annealing.

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