mohammadjavad mahmoodabadi
-
International Journal of Advanced Design and Manufacturing Technology, Volume:17 Issue: 4, Dec 2024, PP 29 -33
In this research, the application of the homotopy perturbation method to solve nonlinear Equations arising in oscillatory systems is investigated. In this way, the performance of the Homotopy Perturbation Method (HPM) is compared with the numerical methods to find the solutions of nonlinear Equations in the vibration field. To this end, the Duffing–Holmes oscillatory model with nonlinear terms is regarded and solved by the HPM method. In order to validate the obtained solution by the HPM, the answers are compared with those of numerical methods. The results clearly depict that the homotopy perturbation method, without needing to small parameters, could present the answers near to the exact solutions and also to the numerical one.
Keywords: Duffing-Holmes Model, Homotopy Perturbation Method, Nonlinear Equations, Oscillatory Systems -
در این پژوهش، به شبیه سازی عددی مسیر عبور جریان های داغ در ناحیه پخت کوره گندله سازی مجتمع معدنی صنعتی گل گهر سیرجان پرداخته شده است. در این راستا، از نرم افزار اوپن فوم که از برنامه های شیء گرا و بر پایه یک زبان برنامه نویسی مناسب است بهره برده است. محدوده مورد بررسی شامل صفحه خروجی مشعل ها، لوله های داون کامر، محفظه احتراق، فضای درون کوره و ویندباکس بوده و بستر گندله به صورت متخلخل فرض شده است. جریان مورد نظر به صورت پایا، تراکم پذیر و مغشوش فرض شده است که از بستر گندله با درصد تخلخل یکنواخت عبور می کند. برای مدل سازی جریان مغشوش از یک مدل دو معادله ای مناسب بهره گرفته شده است. علاوه براین، دیواره های کوره عایق، گرادیان دما و فشار روی دیواره ها صفر و شرط عدم لغزش برای شرط مرزی سرعت فرض شده اند. نتایج حاصل از شبیه سازی حاکی از انحراف جریان های داغ گازی به سمت دیواره های جانبی بوده که می تواند به عنوان یک عامل مهم در خوردگی و کاهش عمر آن ها تلقی شود.
کلید واژگان: شبیه سازی عددی، نرم افزار اوپن فوم، محیط متخلخل، جریان پایا، جریان تراکم پذیر، جریان مغشوشIn this research, numerical simulation of the hot gas flow in the firing area of the pelletizing furnace in Golgohar mining-industrial complex is studied. In this regard, Open-Foam software as an objective-oriented program and based on a proper programming language is used. The considered area includes the outlet plane of the burners, the down comer pipes, the combustion chamber, the space of the furnace and the wind box, while the pellet bed is regarded as a porous media. The investigated flow is assumed as steady-state, compressible and turbulent that passes through the pellet bed having a uniform porosity percentage. In order to model the turbulent flow, an appropriate two-equations approach is employed. In addition, the walls of the furnace are assumed to be insulated, the gradients of the temperature and pressure on the walls are considered to be zero, and non-sliding condition is regarded for the boundary condition of the velocity. The simulation results illustrate that the hot gasses are diverted on the sidewalls, which could be considered as an important factor for corrosion and decreasing their life.
Keywords: Numerical Simulation, Open-Foam Software, Porous Media, Steady-State Flow, Compressible Flow, Turbulent Flow -
هدف این پژوهش، ارایه مدل های تحلیلی کارآمد برای محاسبه نیروهای آیرودینامیکی وارد بر بال ها و دم یک ربات پرنده بال زن می باشد. برای دستیابی به این هدف، ابتدا مدل آیرودینامیکی بال ها برپایه تیوری نوارهای موازی و در نظر گرفتن اثرات انعطاف پذیری بال ها ارایه می شود. سپس، مدل آیرودینامیکی دم با در نظر گرفتن اثرات اختلاف فشار روی سطوح دم، گردابه های لبه ای و اصطکاک هوا معرفی می شود. سپس، پارامتر بهینه انعطاف پذیری بال ها با استفاده از الگوریتم ژنتیک تعیین می گردد. سرانجام، به منظور صحت سنجی، نتایج حاصل از مدل های پیشنهادی با مدل های ارایه شده در مطالعات گذشته و داده های آزمایشگاهی مقایسه می گردد. نتایج شبیه سازی نشان می دهد نیروهای آیرودینامیکی محاسبه شده توسط راهکارهای پیشنهادی در قیاس با مدل های قبلی به داده های آزمایشگاهی نزدیک تر است.
کلید واژگان: ربات پرنده بال زن، بال های انعطاف پذیر، نیروی برآ، نیروی رانش، بهینه سازی، الگوریتم ژنتیکThis research aims to provide efficient analytical models for computing the aerodynamic forces exerted on the wings and the tail of a flapping-wing robot. To achieve this purpose, at first, the aerodynamic model of the wings is presented based upon the parallel strips theory and by considering the effects of wing flexibility. Afterward, the aerodynamic model of the tail is introduced regarding the effects of pressure difference on the tail surfaces, leading edge vortices and air friction. Next, the optimal coefficient of wing flexibility is obtained utilizing the genetic algorithm. Ultimately, in order to validate, the results of the proposed models are compared with the models presented in the former studies and the measured experimental data. Simulation results demonstrate that the aerodynamic forces reckoned by the suggested strategies are closer to the experimental data in comparison with the previous models.
Keywords: Flapping-wing robot, Flexible wings, Lift force, Thrust force, Optimization, genetic algorithm -
International Journal of Advanced Design and Manufacturing Technology, Volume:16 Issue: 1, Mar 2023, PP 89 -97In this paper, the multi-objective optimum design of plate fin heat exchangers is investigated. To this end, the efficiency and cost as two important factors for the design of heat exchangers are regarded as the objective functions. Fin pitch, fin height, fin offset length, cold stream flow length, no-flow length and hot stream flow length are considered as six design parameters. The ε-NTU method is applied to estimate the heat exchanger pressure drop and its effectiveness. A case study related to a gas furnace in Barez tire group located in the northwest of Kerman, Iran is considered for the constant parameters. The Imperialist Competitive Algorithm (ICA) is used to find the optimal design parameters to achieve the maximum thermal efficiency and minimum consumption cost. The method of the weighting coefficients is applied to change the considered multi-objective optimization problem as a single objective one. Furthermore, the effects of variations of the design parameters on the objective functions are independently investigated, and the related graphs are presented.Keywords: Consumption cost, Imperialist Competitive Algorithm, Multi-Objective Optimization, Plate fin heat exchanger, Thermal efficiency
-
International Journal of Advanced Design and Manufacturing Technology, Volume:15 Issue: 2, Jun 2022, PP 69 -82In this research study, an attempt is made to present a new optimization scheme by combination of the firefly algorithm and artificial bee colony (FA-ABC) to solve mathematical test functions and real-world problems as best as possible. In this regard, the main operators of the two meta-heuristic algorithms are employed and combined to utilize both advantages. The results are compared with those of five prominent well-known approaches on sixteen benchmark functions. Moreover, thermodynamic, economic and environmental modeling of a thermal power plant known as the CGAM problem is represented. The proposed FA-ABC algorithm is used to reduce the total cost and increase the efficiency of the system as shown in the Pareto front diagrams.Keywords: Artificial bee colony algorithm, CGAM problem, Firefly Algorithm, Hybrid optimization algorithm
-
Journal of Theoretical and Applied Vibration and Acoustics, Volume:6 Issue: 2, Summer & Autumn 2020, PP 325 -336In this work, a multi-objective optimization process based on the genetic algorithm is employed to damp the vibrations of a piezo actuating composite beam. A new mathematical model for the control effort is proposed and optimized with two objective functions. Conflicting objectives are considered as the displacement of the beam and the second derivative of the control voltage. The coefficients of the proposed control voltage model are regarded as the design variables for this optimization process. The corresponding Pareto front represents non-dominated optimum solutions with different choices to designers. The time behaviors of displacement, velocity and acceleration as well as the related control effort at the midpoint of the beam for three optimum design points are illustrated. The simulation of the time responses of a selected optimum point exhibits the advantage of the planned optimum strategy with regard to those stated in some research such as the cases used in the maximum principle for the same structure.Keywords: Piezo actuator, Beam vibrations, Optimum control effort, Multi-objective optimization, genetic algorithm
-
International Journal of Advanced Design and Manufacturing Technology, Volume:14 Issue: 2, Jun 2021, PP 93 -110Accurate trajectory tracking and control of the Double Flexible Joint Manipulator lead to design a controller with complex features. In this paper, we study two significant strategies based on improving the structure of the hybrid controller and training the controller parameters for an online estimation of time-varying parametric uncertainities. For this purpose, combination of feedback linearization with an adaptive sliding mode control by considering update mechanism is utilized to stabilize the DFJM system. The update mechanism is obtained based on gradient descend method and chain rule of the derivation. Following, in order to eliminate the tedious trial-and-error process of determining the control coefficients, an evolutionary algorithm (NSGA-II) is used to extract the optimal parameters by minimizing the tracking error and control input. In the second step, an online estimation of the designed parameters were proposed based on three intelligent methods; weighting function, Adaptive Neural Network Function Fitting (ANNF), and adaptive Neuro-fuzzy inference system (ANFIS-PSO). The proposed controller reliability finally was examined in condition of the mass and the length of the robot arm was changed and sudden disturbances were imposed at the moment of equilibrium position, simultanously. The results of the tracking error and control input of the trained proposed controller demonstrated minimal energy consumption and shorter stability time in condition that the control parameters are constant and training are not considered.Keywords: Double Flexible Joint Manipulator, Gradient Descent Method, sliding mode controller, Uncertainy
-
در این مقاله، با استفاده از یک روش عددی جدید به حل معادله شرودینگر وابسته به زمان پرداخته شده است. روش ارایه شده، حاصل ترکیب یک الگوریتم فراابتکاری قوی با سرعت و دقت بالا و روش تفاضل محدود است. به این منظور، ابتدا فضای حل متغیرهای مساله ی مورد نظر با استفاده از روش تفاضل محدود شبکه بندی و سپس، معادله شرودینگر با شرایط مرزی مشخص به یک مسئله بدون قید تبدیل شده است. در ادامه، به کمک روش ضریب پنالتی، شرایط مرزی ارضاء و یک تابع هدف مناسب تعریف شده است. در پایان، با استفاده از یک مدل بهبود یافته از الگوریتم تجمعی ذرات به بهینه سازی تابع هدف مورد نظر پرداخته شده است. در چندین مثال مختلف مقدار خطای حاصل از مقایسه مقدار دقیق تابع و مقدار عددی محاسبه شده بیانگر موفقیت روش عددی پیشنهادی در حل مسئله شرودینگر وابسته به زمان است.
کلید واژگان: معادله شرودینگر وابسته به زمان، الگوریتم تجمعی ذرات، روش تفاضل محدود، روش ضریب پنالتیIn this paper, a new numerical method is introduced to solve the time-dependent nonlinear Schrödinger equation. The proposed method is a combination of a novel metaheuristic optimization algorithm with the finite difference method. First, the regarded Schrödinger equation with the ralated boundary and initial conditions are converted into an unconstrained problem. For this purpose, the boundary and initial conditions are satisfied using the penalty method and a proper objective function is defined through the discretized governing equation. Then, a successful version of the particle swarm optimization is implemented to minimize the identified error function and find the best nodal values. The simulation results for several cases are illustrated to depict the effectiveness and capability of the introduced sterategy for solving the time-dependent nonlinear Schrödinger equation.
Keywords: Time-Dependent Schrödinger Equation, Particle swarm optimization algorithm, Finite difference method, Penalty method -
در این پژوهش، سینماتیک و دینامیک یک ربات کابلی صفحه ای سه درجه آزادی، به همراه کنترل مسیر آن مورد مطالعه و بررسی قرار گرفته است. ابتدا، کششی بودن نیروی کابل ها با توجه به این نکته بررسی شده که ربات مورد نظر یک مکانیسم زنجیره ای سینماتیک بسته بوده و عملگر از طریق چند کابل محرک به پایه متصل می شود. سپس، کنترل کننده های تناسبی- انتگرالی - مشتقی و فازی تناسبی- انتگرالی - مشتقی برای کنترل ربات کابلی به ازای شرایط نهایی مطلوب متعدد و متفاوت بکار گرفته شده اند. توجه به این نکته ضروری است که یک قانون کنترلی مناسب برای ربات های کابلی نه تنها سبب تعقیب مسیر تعریف شده می شود، بلکه مثبت بودن نیروی کششی کابل ها را در تمامی حالت ها نیز باید تضمین نماید. برای تعیین ضرایب کنترل کننده ها، از الگوریتم دسته میگو، که یک الگوریتم بهینه سازی بر پایه جمعیت است، استفاده شده است. نتایج بدست آمده حاکی از موفقیت استراتژی پیشنهادی در هدایت ربات کابلی به اهداف مطلوب می باشد.
کلید واژگان: کابل کششی، ربات کابلی، کنترل کننده فازی تناسبی- انتگرالی - مشتقی، الگوریتم بهینه سازی دسته میگوIn this study, the kinematics and dynamics of a plane direct-guided cable robot with three degree-of-freedom and the control of its direction have been studied and investigated. First, the tensile of the cables has been investigated regarding that the robot is a closed kinematic chain mechanism and the end-effector is adjoined to the base through several actuating cables. Afterwards, the Proportional-Integral-Derivative (PID) controller and the fuzzy PID controller have been applied on the cable robot for different and various final desired conditions. It is noticeable that a proper control rule for the cable robot not only causes the tracking of the desired trajectory, but also guarantees the positivity of the cable tension forces for all states. In order to determine the parameters of the controllers, the krill herd algorithm as a population-based optimization procedure is implemented. The obtained results indicate the successfulness of the proposed strategy to guide the cable robot to the desired objectives.
Keywords: Cable robot, Fuzzy proportional-integral-derivative controller, Krill herd optimization algorithm -
Oil is one of the most precious source of energy for the world and has an important role in the global economy. Therefore, the long-term prediction of the crude oil price is an important issue in economy and industry especially in recent years. The purpose of this paper is introducing a new Particle Swarm Optimization (PSO) algorithm to forecast the oil prices. Indeed, the PSO is a population-based optimization method inspired by the flocking behavior of birds. Its original version suffers from tripping in local minima. Here, the PSO is enhanced utilizing a convergence operator, an adaptive inertia weight and linear acceleration coefficients. The numerical results of mathematical test functions, obtained by the proposed algorithm and other variants of the PSO elucidate that this new approach operates competently in terms of the convergence speed, global optimality and solution accuracy. Furthermore, the effective variables on the long-term crude oil price are regarded and utilized as input data to the algorithm. The objective function of the optimization process considered in this research study is the summation of the square of the difference between the actual and the predicted oil prices. Finally, the long-term crude oil prices are accurately forecasted by the proposed strategy which proves its reliability and competence.Keywords: Particle Swarm Optimization, Long-term prediction, crude oil price, Mathematical test functions
-
The main purpose of this work is the comparison of several objective functions for optimization of the vertical alignment. To this end, after formulation of optimum vertical alignment problem based on different constraints, the objective function was considered as four forms including: 1) the sum of the absolute value of variance between the vertical alignment and the existing ground; 2) the sum of the absolute value of variance between the vertical alignment and the existing ground based on the diverse weights for cuts and fills; 3) the sum of cut and fill volumes; and 4) the earthwork cost and then the value of objective function was compared for the first three cases with the last one, which was the most accurate ones. In order to optimize the raised problem, Genetic Algorithm (GA) and Group Search Optimization (GSO) were implemented and performance of these two optimization algorithms were also compared. This research proves that the minimization of sum of the absolute value of variance between the vertical alignment and the existing ground, which is commonly used for design of vertical alignment, can’t at all grantee the optimum vertical alignment in terms of earthwork cost.
Keywords: Earthwork Volumes, Group Search Optimization (GSO), Objective function, Optimization, Optimum Vertical Alignment -
This paper is concerned with fuzzy tracking control optimized via multi-objective particle swarm optimization for stable walking of biped robots. To present an optimal control approach, multi-objective particle swarm optimization is used to design the parameters of the control method in comparison to three effectual multi-objective optimization algorithms in the literature. In particle swarm optimization, a dynamic elimination technique is utilized as a novel approach to prune the archive effectively. Moreover, a turbulence operator is used to skip the local optima and the personal best position of each particle is determined by making use of the Sigma method. Normalized summation of angles errors and normalized summation of control efforts are two conflicting objective functions addressed by dint of multi-objective optimization algorithms in the present investigation. By contrasting the Pareto front of multi-objective particle swarm optimization with the Pareto fronts of other methods, it is illustrated that multi-objective particle swarm optimization performs with high accuracy, convergence and diversity of solutions in the design of fuzzy tracking control for nonlinear dynamics of biped robots. Finally, the proper performance of the proposed controller is demonstrated by the results presenting an appropriate tracking system and optimal control inputs. Indeed, the appropriate tracking system and optimal control inputs prove the efficiency of optimal fuzzy tracking control in dealing with the nonlinear dynamics of biped robots.
Keywords: Fuzzy Tracking Control, Multi-Objective Optimization, Particle Swarm Optimization, Genetic Algorithm Optimization, Biped Robots -
Many researchers have controlled and analyzed biped robots that walk in the sagittal plane. Nevertheless, walking robots require the capability to walk merely laterally, when they are faced with the obstacles such as a wall. In walking robot field, both nonlinearity of the dynamic equations and also having a tracking system cause an effective control has to be utilized to address these problems. Therefore, this paper presents a nonlinear fuzzy tracking control for the walking robots that step purely in the lateral plane on slope. When fuzzy control is utilized to track the desired trajectories of the joints, there has to be a trade-off between tracking errors and control efforts. Consequently, a particle swarm optimization algorithm is used to obtain the Pareto front of these non-commensurable objective functions to determinate the fuzzy control parameters. In this paper, normalized summation of angles errors and normalized summation of control efforts are considered as the objective functions. These objective functions have to be minimized simultaneously. A vector which contains the control parameters is considered as the vector of selective parameters with positive constant values. The obtained Pareto front by the proposed multi-objective algorithm is contrasted with three prominent algorithms, modified NSGAII, Sigma method and MATLAB Toolbox MOGA. The result dramatizes the superiority of innovative particle swarm optimization over the algorithms.Keywords: Walking Robot, Fuzzy Tracking Control, Particle Swarm Optimization, Multi-objective optimization
-
International Journal of Advanced Design and Manufacturing Technology, Volume:11 Issue: 3, Sep 2018, PP 75 -82In this paper, the multi-objective optimum design of shell and tube heat exchangers is investigated. A thermal modelling of an industrial shell and tube heat exchanger is performed using an -NTU method for estimating the shell side heat transfer coefficient and pressure drop. The efficiency and total cost (includes the capital investment for the equipment and operating cost) are two important parameters in the design of heat exchangers. The fixed parameters and the ranges of the design variables are obtained from a shell and tube recovery heat exchanger in Barez tire production factory located in Kerman city, Iran. The Imperialist Competitive Algorithm (ICA) is used to find the optimal design parameters to achieve the maximum thermal efficiency and minimum consumption cost as the objective functions. The tube inside and outside diameters, tube length and the number of tubes are considered as four design variables. Furthermore, the effects of changing the values of the design variable on the objective functions are independently investigated. At the end, the obtained Pareto front and the related design variables and their corresponding objective functions are presented.Keywords: Imperialist Competitive Algorithm, Multi-Objective Optimization, Shell, Tube Heat Exchangers
-
Improving and enhancing methodologies for efficiently and effectively design of the energy systems is one of the most important challenges that energy engineers face. In this work, a multi-objective particle swarm optimization algorithm is applied for a highly constrained cogeneration problem named CGAM problem as a standard cycle to verify all optimization methods. The regarded objective functions are the exergetic efficiency that should be maximized and the total cost rate that should be minimized, simultaneously. In order to determine the polar effects of the pressure ratio and the turbine inlet temperature on the specified objective functions, a sensitivity analysis is performed. The related Pareto fronts with different values of equivalence ratios, unit costs of fuel and NOx emissions are represented and their effects on the system are studied. Furthermore, the comparison of the obtained results with those of other evolutionary algorithms demonstrates the superiority and efficiency of the considered multi-objective particle swarm optimization algorithm.
Keywords: Multi-objective Particle swarm optimization, Highly constrained thermal system, Exergetic efficiency, Total cost, Pareto design -
در این مقاله، روش درون یابی حداقل مربعات متحرک برای تقریب پارامترهای کنترل کننده فازی تطبیقی در یک سیستم تعلیق دو درجه آزادی با پارامتر متغیر جرم بدنه پیشنهاد شده است. در طراحی روش کنترلی پیشنهادی، دو سیستم فازی که هر کدام دو ورودی و یک خروجی به همراه بیست و پنج قانون اگر-آنگاه فازی می باشد، در نظر گرفته شده است. با استفاده از پنج تابع عضویت گاووسی برای هر ورودی، فازی ساز منفرد، موتور استنتاج حاصلضرب و غیر فازی ساز میانگین مراکز، سیستم های فازی طراحی شده اند. سیستم های فازی ساخته شده با قوانین انطباق ترکیب می شوند. برای این منظور، تئوری لیاپانوف برای پایداری قوانین انطباق اعمال شده است. برای بدست آوردن پارامترهای بهینه ی کنترل کننده، الگوریتم بهینه سازی جستجوی گرانشی بکار برده شده است. در این الگوریتم مجموع وزن دار دو هدف جابجایی نسبی بین جرم فنر بندی شده و تایر و همچنین شتاب بدنه به عنوان تابع هدف مورد استفاده قرار گرفته است. از آنجا که انتخاب ضرایب مناسب کنترل کننده حائز اهمیت است و همچنین هنگامی که پارامتر سیستم تغییر پیدا کند، ضرایب بهینه کنترل کننده نیز تغییر میابند. برای حل این مشکل، مدل پیشگوی حداقل مربعات متحرک پیشنهاد شده است که نوعی روش درون یابی بر اساس شعاع همسایگی، تابع پایه و تابع وزن برای نقاط مورد نظر مساله است. در نهایت مدل برخط حاصل، بر سیستم تعلیق دو درجه آزادی اعمال شده و نتایج با سیستم های بهینه بدون تقریبگر مقایسه شده است.کلید واژگان: مدل پیشگو، حداقل مربعات متحرک، کنترل کننده فازی تطبیقی بهینه، الگوریتم جستجوی گرانشی، سیستم تعلیق دو درجه آزادیThe Moving Least Square (MLS) interpolation method is proposed for approximation of adaptive fuzzy controller parameters for two degrees of freedom suspension system and each one has two inputs, one output with twenty-five linguistic fuzzy IF-THEN rules. Fuzzy systems are designed by using five Gaussian membership functions for each input, product inference engine, singleton fuzzifier and center average defuzzifier. The constructed fuzzy systems is composed with adaptation rules. For this purpose, Lyapunove approach is implemented for stability of the adaptation rules. The Gravity Search Algorithm (GSA) is implemented for achieve the optimum controller parameters. The relative displacement between sprung mass and tire and the body acceleration are two objective functions used in the optimization algorithm. Since, choose the suitable controller coefficients are important and when the parameter of the system change, Optimum coefficients of the controller will also change. In order to solve this obstacle, the MLS predictive model is purposed that is interpolation method based on a radius of the neighborhood, a basis function and a weight function for points of interest. Finally online model is implemented on the two degrees of freedom suspension system and results compared with the offline optimal systems.
-
International Journal of Advanced Design and Manufacturing Technology, Volume:9 Issue: 4, Dec 2016, P 59It would be difficult to deny the importance of optimization in the areas of science and technology. This is in fact, one of the most critical steps in any design process. Even small changes in optimization can improve dramatically upon any process or element within a process. However, determining whether an optimization approach will improve on an original design is usually a question that its response in this study has led to an optimal design out of an existing car model. First of all, the optimization of a passive car-quarter model has been accomplished by means of a genetic algorithm. This initial optimization gives a figure of points named ''Pareto optimum points''. Secondly, through selecting a point amongst them, the design of active model has been completed and optimized based on genetic algorithm. Continuing with this thought, a similar process has been also accomplished with a car-half vehicle model with five degrees of freedom. Though the last optimized active model may prove a more reliable efficient design due to the more comprehensive feature related to the degrees of freedom, the results of each optimization should be considered and may supply equally attractive and diverse choices as well. Anyway, let's focus on the final purpose which is to reduce the vibrations as much as possible. This is what is observed through all the optimization jobs in this study. Comparison of these results with those reported in the literature affirms the excellence of the proposed optimal designs.Keywords: Active suspension system, Genetic algorithm, Multi, objective optimization, Passive suspension system, PID controller, Vehicle vibration model
-
International Journal of Advanced Design and Manufacturing Technology, Volume:4 Issue: 4, 2011, PP 47 -56Numerical solutions obtained by the Meshless local Petrov–Galerkin (MLPG) method are presented for two-dimensional steady-state heat conduction problems. The MLPG method is a truly meshless approach, and neither the nodal connectivity nor the background mesh is required for solving the initial-boundary-value problem. The penalty method is adopted to efficiently enforce the essential boundary conditions, the moving least squares approximation is used for interpolation schemes and the Heaviside step function is chosen for test function. The results show that the present method is very promising in solving engineering two-dimensional steady-state heat conduction problems.
-
This paper deals with a globally convergent adaptive and sliding mode control of a cart-pole inverted pendulum for trajectory tracking in the presence of a bounded measurement noise and parameter uncertainty. Two kinds of controllers have been used for evaluation of tracking error in presence of a bounded noise; as a result, we want to compare that at what time we can see the convergence of tracking error and which controller can perform better? Simulation results on a cart-pole inverted pendulum are shown for trajectory tracking in presence of impulse disturbance.
-
International Journal of Advanced Design and Manufacturing Technology, Volume:3 Issue: 2, 2010, P 37A truly meshless local Petrov-Galerkin (MLPG) method is developed forsolving 3D elasto-static problems. Using the general MLPG concept, this method isderived through the local weak forms of the equilibrium equations, by using test functions,namely, the Heaviside function. The moving least squares (MLS) are chosen to constructthe shape functions, for the MLPG method. The penalty approximation is used to imposeessential boundary condition. Several numerical examples are included to demonstrate thatthe present method is very promising for solving the elastic problems.
- در این صفحه نام مورد نظر در اسامی نویسندگان مقالات جستجو میشود. ممکن است نتایج شامل مطالب نویسندگان هم نام و حتی در رشتههای مختلف باشد.
- همه مقالات ترجمه فارسی یا انگلیسی ندارند پس ممکن است مقالاتی باشند که نام نویسنده مورد نظر شما به صورت معادل فارسی یا انگلیسی آن درج شده باشد. در صفحه جستجوی پیشرفته میتوانید همزمان نام فارسی و انگلیسی نویسنده را درج نمایید.
- در صورتی که میخواهید جستجو را با شرایط متفاوت تکرار کنید به صفحه جستجوی پیشرفته مطالب نشریات مراجعه کنید.