Altı eklemli robot kolunun genetik algoritma ve elman ağ uyarlamalı genelleştirilmiş öngörülü kontrolü

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Bu tez çalışmasında, Model Tabanlı Öngörülü Kontrol (Model Based Predictive Control-MBPC) sınıfına ait olan Genelleştirilmiş Öngörülü Kontrol (Generalized Predictive Control - GPC), Basit Genetik Algoritma uyarlamalı Genelleştirilmiş Öngörülü Kontrol (SGA-GPC), Newton-Raphson uyarlamalı Yapay Sinir Ağlı Genelleştirilmiş Öngörülü Kontrol (Neural Generalized Predictive Control - NGPC) ve Yinelenen Elman Yapay Sinir Ağ uyarlamalı Genelleştirilmiş Öngörülü Kontrol (Recurrent Elman Network implemented Neural Generalized Predictive Control - ENGPC) algoritmaları altı eklemli endüstriyel bir robotik manipülatöre eklem esaslı yörünge kontrolü için uygulanmıştır. Robotik manipülatörün dinamik modellenmesinde Lagrange-Euler yöntemi kullanılmıştır. Dinamik modellemeye sürtünme etkileri, yük taşıma ve taşınan yükün taşıma esnasında düşmesi durumları da ilave edilmiştir. Ayrıca, kontrolü güçleştirmek için ile arasında rasgele bozucular ilave edilmiştir. Dinamik model, 4. mertebeden Runge-Kutta bütünleştirme yöntemi kullanılarak robot kolu simülatörüne dönüştürülmüştür. Tasarlanan kontrol algoritmalarının performansı eklemlere ait tork, açısal yörünge, açısal hız, açısal hız hataları grafikleri ile eklemlere ait açısal konum hataları, açısal hız hatalarının kareleri ve uç nokta konum hataları üzerinden hem grafiksel hem de nümerik sonuçlarla karşılaştırılmıştır.In this thesis study, Generalized Predictive Control (GPC), Neural Generalized Predictive Control (NGPC), Simple Genetic Algorithm implemented GPC (SGA-GPC) and Recurrent Elman Neural Network implemented NGPC (ENGPC) algorithms belong to the class of Model Based Predictive Control (MBPC) were investigated and each of them was applied to a 6-DOF (Degrees-Of-Freedom) robotic manipulator as SISO (Single Input Single Output) and MIMO (Multiple Inputs Multiple Outputs) for the trajectory control based joint. Dynamics modeling of the robotic manipulator was made by using the Lagrange-Euler equations. The frictional effects, the state of carrying and falling load were also added to dynamics model. In addition, the random distortions between and were added to the torques applied to the joints in every control step, and the effect to the performance of the distortions was investigated. Dynamics model was transformed into robotic arm simulator by using the fourth-order Runge-Kutta integration method. The trajectory planning for the joints of the robotic arm was designated according to the sinusoidal trajectories principles. The control algorithms were compared with themselves for different examples and cases

Robot Axis Dynamics Control Using A Virtual Robotics Environment

Robots are complex electromechanical systems where several electric drives are employed to control the movement of articulated structures. In industrial environments they must perform tasks with rapidity and accuracy in order to produce goods and services with minimal production time. These procedures require the use of flexible robots which can act in a large workspace, thus subject to important parameters variations, with efficient control algorithms. The progress of technology and the close relationships among several sciences, such as micro-electronic, software engineering and communications, open space for a great development in the robotics area and automation process. Generalized Predictive Control (GPC) has shown to be an effective strategy in many fields of applications, with good time-domain and frequency properties (small overshoot, improved tracking accuracy and disturbance rejection ability, good stability and robustness margins), able to cope with important parameters variations. This paper presents an application of GPC to a robot trajectory control with a comparison between classical PID and GPC controllers within an original Virtual Environment. © 2005 IEEE.1 2 VOLS305311Boucher, P., Dumur, D., Predictive Motion Control (1995) Journal of Systems Engineering, Special Issue on Motion Control Systems, 5, pp. 148-162. , Springer-Verlag, LondonSpong, M.W., Vidyasagar, M., Robot Dynamics and Control (1989) John Wiley & Sons, , New YorkClarke, D.W., Mohtadi, C., Tuffs, P.S., Generalized Predictive Control", Part I "The Basic Algorithm", Part II "Extensions and Interpretation (1987) Automatica, 23 (2), pp. 137-160Craig, J.J., (1989) Introduction to Robotics: Mechanics and Control, , Second edition, Addison-Wesley Publishing CompanyDavid, S., Rosário, J.M., Modeling, Simulation and Control of Flexible Robots (1998) CONTROLO'98, pp. 532-539. , Coimbra, PortugalPimenta, K.B., Souza, J.P., Rosário, J.M., Dumur, D., Control of Robotic Joints with Generalized Predictive Control (GPC) (2001) RADD '2001, , Vienne, AustriaPimenta, K.B., Rosário, J.M., The Using Techniques of Generalized Predictive Control (GPC) Applied on Control of Robotic Joints (2001) Asiar, , Bangkok, ThailandRosário, J.M., Oliveira, C., Sa, C.E.A., Proposal Methodology for the Modeling and Control of Manipulators (2002) International Journal of the Brazilian Society of Mechanical Engineering, XXIV-N. , 3, Jul

An Integrated Environment For The Modeling And Simulation Of Mechatronics Devices

One of the most common sources of performance limitation in the control of mechatronic systems is associated to the coupling dynamics of the different degrees of freedom, induced by the elasticity in some components. Indeed, in industrial environments, they must perform tasks with rapidity and accuracy in order to produce goods and services with minimal production time. These procedures require the use of flexible robots which can act in a large workspace, thus subject to important parameters variations. The design of the control system should guarantee a damped behavior of the load position, both in the set point response and in the rejection of the disturbances arising from the joints operation. This paper presents an application of Generalized Predictive Control (GPC) to a robot trajectory control using an Integrated Virtual Environment for the modeling and simulation of mechatronics devices. © 2006 IEEE.20066671Boucher, P., Dumur, D., Predictive motion control (1995) Journal of Systems Engineering, Special Issue on Motion Control Systems, 5, pp. 148-162. , Springer-Verlag, LondonSpong, M.W., Vidyasagar, M., Robot dynamics and control (1989) John Wiley & Sons, New YorkClarke, D.W., Mohtadi, C., Tuffs, P.S., "Generalized predictive control", part I "The basic algorithm", part II "extensions and interpretation (1987) Automatica, 23 (2), pp. 137-160Cassemiro, E.R., Rosário, J.M., Dumur, D., Robot axis dynamics control using a virtual robotics environment (2005) IEEE Transactions on Systems, Man and Cybernetics - ETFA'05, pp. 305-311. , Preprints of, Catania, ItalyOllero, A., Boverie, S., Goodal, R., Mechatronics, robotics and components for automation and control (2005) Annual Reviews in Control IFAC Journal, (26), pp. 203-228David, S., Rosário, J.M., Modeling, simulation and control of flexible robots (1998) CONTROLO'98, pp. 532-539. , Coimbra, PortugalPimenta, K.B., Souza, J.P., Rosário, J.M., Dumur, D., Control of robotic joints with Generalized Predictive Control (GPC) (2001) RADD'2001, Vienne, AustriaRosário, J.M., Oliveira, C., Sa, C.E.A., Proposal methodology for the modeling and control of manipulators (2002) International Journal of the Brazilian Society of Mechanical Engineering, 24 (3). , Jul

Conception Of Stewart-gough Platform With Reconfigurable Control

This paper shows that a hierarchical architecture, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing, enables to take into account the easiness of future modifications, updates and improvements in robotic applications. An experimental example of a Stewart-Gough platform control, platform applied as a solution of countless practical problems, is presented using reconfigurable computing. The developed software and hardware are structured in independent blocks. This open architecture implementation allows an easy expansion of the system and a better adaptation of the platform to its related tasks. ©2006 IEEE.200610391044Ollero, A., Boverie, S., Goodal, R., Mechatronics, robotics and components for automation and control (2005) Control IFAC Journal, 26, pp. 203-228Lee, T., Improved dualistic elimination algorithm for the forward kinematics of the general Stewart-Gough platform (2003) Mechanism and Machine Theory, 38, pp. 563-577Spong, M.W., Vidyasagar, M., Robot dynamics and control (1989) John Wiley & Sons, , New YorkPimenta, K.B., Souza, J.P., Rosário, J.M., Dumur, D., Control of robotic joints with Generalized Predictive Control (GPC) (2001) RADD'2001, , Vienne, AustriaCassemiro, E.R., Rosário, J.M., Dumur, D., Robot axis dynamics control using a virtual robotics environment (2005) IEEE Conference on Systems, Man and Cybernetics, pp. 305-311. , Catania, ItalyErig Lima, C.R., Silva, N.C., Rosário, J.M., A proposal of flexible architecture for mobile robotics (2000) 7th Forum International Conference and Mechatronics Education Workshop, pp. 57-62. , AtlantaDumur, D., Boucher, P., New predictive techniques - Control axis solutions (1994) Proceedings of the 3rd IEEE Conference on Control Applications, 3, pp. 1663-1668Rosário, J.M., Erig Lima, C.R., Ferasolli, H., Perogaro, R., Reconfigurable architecture proposal to application on mobile embedded systems prototypes (2003) 7th IFAC Symp. Robot Control - SYROCO'03, 1, pp. 89-94David, S., Rosario, J.M., Modeling, simulation and control of flexible robots (1998) CONTROLO'98, pp. 532-539. , Coimbra, PortugalBonev, I.A., A closed-form solution to the direct kinematics of nearly general parallel manipulators with optimally located three linear extra sensors (2003) IEEE Trans. on Robotics and Automation, 17 (2), pp. 148-15

A 3 Dof Robotic Platform Dynamics Control Using Rapid Prototyping Tools

As the main aim for mechatronics engineers in the field of industrial robotic is basically to enhance velocity and accuracy of the treated structure, more and more powerful systems for the design and optimization process are developed. Indeed, in industrial environments, they must perform tasks with rapidity and accuracy in order to produce goods and services with minimal production time. The rapid control prototyping is executed with simulation programs (mechanical and electronics devices) embedded in the real time environment. The design of the control system should guarantee a damped behavior of the load position, both in the set point response and in the rejection of the disturbances arising from the joints operation. This paper presents an application of Predictive Control laws to a robot trajectory control using an Integrated Virtual Environment for the modeling and simulation of mechatronics devices. © 2006 IEEE.2006663668Boucher, P., Dumur, D., Predictive motion control (1995) Journal of Systems Engineering, Special Issue on Motion Control Systems, 5, pp. 148-162. , Springer-Verlag, LondonSpong, M.W., Vidyasagar, M., (1989) Robot Dynamics and Control, , John Wiley & Sons, New YorkClarke, D.W., Mohtadi, C., Tuffs, P.S., Generalized predictive control, Part I "The Basic Algorithm", Part II "Extensions and Interpretation (1987) Automatica, 23 (2), pp. 137-160Cassemiro, E.R., Rosário, J.M., Dumur, D., Robot Axis dynamics control using a virtual robotics environment (2005) IEEE Transactions on Systems, Man and Cybernetics -ETFA'05, pp. 305-311. , Catania, ItalyOllero, A., Boverie, S., Goodal, R., Mechatronics, Robotics and components for automation and control (2005) Annual Reviews in Control IFAC Journal, (26), pp. 203-228David, S., Rosário, J.M., Modeling, simulation and COntrol of flexible robots (1998) CONTROLO'98, pp. 532-539. , Coimbra, PortugalPimenta, K.B., Souza, J.P., Rosário, J.M., Dumur, D., Control of robotic joints with generalized predictive control (GPC) (2001) RADD'2001, , Vienne, AustriaRosário, J.M., Oliveira, C., Sa, C.E.A., Proposal methodology for the modeling and control of manipulators (2002) Int. Journal of the Brazilian Society of Mech. Eng., 24 (3). , Jul