Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
Browse
Search Results
Master Thesis Design and Experimental Evaluation of a Dynamically Balanced Over-Constrained Planar 6r Parallel Manipulator(Izmir Institute of Technology, 2019) Özkahya, Merve; Kiper, Gökhan; Dede, Mehmet İsmet CanWith the development of the industry, the number of robots used in the production line is increasing day by day. Particularly, it is known that parallel robots are better in terms of positioning accuracy compared to serial robots based on the stretching of robot arms. In parallel mechanisms, there are many factors such as calibration, stability and dynamic balancing of the mechanism affecting positioning accuracy. The aim of this thesis is to dynamically balancing parallel mechanisms to improve positioning accuracy. In high acceleration applications, the shaking force and moment are the factors that cause vibration in the base of the mechanism. These vibrations can be reduced by designing dynamically balanced mechanisms. In this thesis, over- and simply constrained 6R mechanisms are designed for dynamic balancing studies and prototypes are produced. The counter mass method was used to balance the mechanism dynamically. The design of the masses was made according to the mass information received from the model designed in the computer aided drawing program and the parts of the mechanisms were updated according to their actual mass values after they were produced. The design of the masses is designed according to the mass information from CAD model and the parts of the mechanisms are updated according to their actual mass values after they are produced. Dimensional measurements were taken by FARO Prime Arm device due to faults that may arise from the production in the parts of the mechanism after production. Then the mechanism was assembled. Before carrying out the balancing tests, calibration studies affecting the positioning accuracy of the over-constrained mechanism were carried out. Finally, the mechanism is activated balanced and unbalanced and the acceleration effect of the 6-axis accelerometer is obtained experimentally.Master Thesis On Improving the Performance of Repetitive Leaning Controllers(Izmir Institute of Technology, 2019) Çobanoğlu, Necati; Tatlıcıoğlu, EnverRobot manipulators are widely used to perform pre–defined tasks repetitively. Nearly all of the mass production factories use the robot manipulators to perform specific operations over and over again. In such a system, the control design may contain some difficulties, unavailabilities and/or there would be additive disturbances due to the periodic motion. Moreover, cost reduction may be vital, hence sensor usage has to be reduced. In the first part of this thesis, to address those restrictions, a model free full state feedback repetitive learning controller which is fused with a one–layer neural network is proposed for robot manipulator which performs a periodic motion. Stability of the system is ensured via Lyapunov based techniques. Numerical simulations and experimental results are introduced to demonstrate the performance of the proposed controller. In the second part of the thesis, under the additional constraint that velocity measurements being unavailable, output feedback repetitive learning controller fused with a neural network term is investigated. The dynamic model of the robot manipulator is again considered as uncertain to avoid its usage as part of the control design, and the reference position vector is still considered to be periodic. The stability of the closed loop system is investigated via Lyapunov based techniques. Numerical simulations are added to demonstrate the proposed controller performance.