This paper demonstrates the effectiveness of a genetic algorithm in identification of the unknown parameters of a nonlinear 2DOF laboratory helicopter model. The mathematical model of physical structure of the helicop...
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This paper demonstrates the effectiveness of a genetic algorithm in identification of the unknown parameters of a nonlinear 2DOF laboratory helicopter model. The mathematical model of physical structure of the helicopter has fourteen unknown parameters which are necessary to be identified. For identification of this model a genetic algorithm is chosen because it enables finding referent results using less number of the experiments in comparison with other identification techniques. After the identification process has been carried out, the unknown parameters are determined and validated through comparisons of the simulation model response and response of the real helicopter system.
This paper presents an implementation of soft computing methodologies, like genetic algorithm and fuzzy logic, in identification and control of 2DOF nonlinear helicopter model (Humusoft CE 150). The genetic algorithm ...
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This paper presents an implementation of soft computing methodologies, like genetic algorithm and fuzzy logic, in identification and control of 2DOF nonlinear helicopter model (Humusoft CE 150). The genetic algorithm is proposed for identification of the physical structure of helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to elevation and azimuth fuzzy logic Mamdani type controllers design in a simulation mode. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments.
This paper is about the Matlab teaching at the faculty of electricalengineering and Information Technology in Bratislava. In this course we are focusing on the individual work of students. Students work on assignment...
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ISBN:
(纸本)9789604742028
This paper is about the Matlab teaching at the faculty of electricalengineering and Information Technology in Bratislava. In this course we are focusing on the individual work of students. Students work on assignments every week and they are evaluated for finishing tasks on the exercises. We studied their results and impact of evaluating the tasks on the exercises. We also compared this type of evaluating and others used before.
作者：
Ríos, HéctorDávila, JorgeFridman, LeonidDepartment of Control
Division of Electrical Engineering Engineering Faculty C.P. 04510 Mexico DF Mexico
CINVESTAV-IPN Automatic Control Department Av. IPN 2508 Col. San Pedro Zacatenco Gustavo A. Madero Mexico DF Mexico
This article presents the problem of finite time state observation for a class of non-linear systems with multiple outputs affected by modeling uncertainties and unknown inputs. The proposed adaptable method is based ...
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An adequate collaboration between the partners within a multinational project is essential for a successful project deployment. The activities developed by the project partnership involve usually decisions that collab...
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An adequate collaboration between the partners within a multinational project is essential for a successful project deployment. The activities developed by the project partnership involve usually decisions that collaboratively must be taken. Although the e-mail is the most used technology for distance collaboration, the team work within a multinational project involves collaborative activities and the decisions associated to it that only the e-mail cannot support. This paper presents several collaborative work examples and decision scenarios which are specific to many European funded multinational educational projects. The analysis of these scenarios shapes a list of features that a decision support system must provide in order to facilitate the collaborative activities developed in the frame of multinational projects.
We present a novel approach to interactive and concurrent volume visualization of functional Magnetic Resonance Imaging (fMRI). While the patient is in the scanner, data is extracted in real-time using state-of-the-ar...
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The paper presents a design of 3D simulator for 2DOF laboratory helicopter model (Humusoft CE 150) and its practical implementation in various control system structures. The developed simulator provides testing perfor...
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The paper presents a design of 3D simulator for 2DOF laboratory helicopter model (Humusoft CE 150) and its practical implementation in various control system structures. The developed simulator provides testing performance of different control algorithms and visualization of results obtained. The 3D simulator has been designed and developed using the VRML programming language under the Virtual Reality toolbox in Matlab/Simulink. The effectiveness of this simulator are demonstrated during simulation and experiments on the 2DOF helicopter model using different control techniques, such as PID, adaptive gain scheduling and fuzzy controllers. Some of them have been designed in this paper.
Hybrid ohosis combined Functional electrical Stimulation (FES) with a lower limb ohotic brace. The first hybrid ohosis system is introduce in 1972 and since many researchers began to produced hybrid orthosis from comp...
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Neural networks have been applied very successfully in the identification and control of nonlinear dynamic systems. The paper presents a design of neural network based control system for 2DOF nonlinear laboratory heli...
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Neural networks have been applied very successfully in the identification and control of nonlinear dynamic systems. The paper presents a design of neural network based control system for 2DOF nonlinear laboratory helicopter model (Humusoft CE 150). The main objective of this paper is to develop artificial neural networks to control helicopter's motors, or consequently elevation and azimuth angles. Neural networks are obtained by cloning various type of controllers designed in our previous papers. Those procedures included a cloning linear PID controller, gain scheduling controller and fuzzy controller.
This paper presents the design of a robust Iterative Learning control (ILC) algorithm for linear systems in the presence of parametric uncertainties and repetitive disturbances. The robust ILC design is formulated as ...
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ISBN:
(纸本)9781424456062
This paper presents the design of a robust Iterative Learning control (ILC) algorithm for linear systems in the presence of parametric uncertainties and repetitive disturbances. The robust ILC design is formulated as a min-max problem with a quadratic performance index subjected to constraints of the control input. Employing Lagrange duality, we can reformulate the robust ILC design as a convex optimization problem over linear matrix inequalities (LMIs). An LMI algorithm for the robust ILC design is then given. Finally, the effectiveness of the proposed robust ILC algorithm is demonstrated through a numerical example.
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