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his article presents a novel systematic methodology for the detection of interest points in 3D point clouds and its corresponding descriptors by using the information of an RGB camera and a structured-light sensor. This is achieved by fusing Speeded-Up Robust Features (SURF) in the image space, and histograms that statistically represent the relationship of three dimensional geometric data around...
This paper will compare properties of Sliding Mode Controllers and classical Proportional Integral controller for permanent magnet synchronous machines. PI controller is simple but sensitive to parameter variations and external disturbance. Due to this reasons, Sliding Mode Control technique is proposed in this paper. This control technique works against parameters variations and external disturbances,...
In order to obtain a robust optimal control for a DC drive system a different solution from the existing technical literature is proposed in this paper. By using the linear quadratic control the optimal speed of the DC dive is obtained. This serves as a reference to the adaptive DC drive system. The model reference adaptive control (MRAC) ensures the robustness to parameters and load variations, to...
This paper propose a model predictive control (MPC) of a three phase Permanent Magnet Synchronous Motor (PMSM). The ARX model, used to compute the predictive control signal, is obtained using an online identification procedure. The MPC is then compared with a conventional approach, i.e. Proportional Integral (PI) speed controller. The effectiveness of the approach is shown in the simulation results...
This paper presents a sliding mode control structure designed for a dynamic system, helicopter type. The approach is robust to model uncertainties and disturbances. The proposed control algorithm is validated on a laboratory stand which uses carrying force to stabilize a helicopter.
This paper presents a research of temporal variability for water parameters on the most important river system from Romania and Europe - the Danube River.
An alternative approach for the identification of the LuGre dynamical friction model is proposed in this paper. The identification procedure is made using modular neural networks (MNN). The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several (nonlinear) subsystems. Each local nonlinear model is identified by a neural network (NN)...
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