Savremene tehnike upravljanja sistemom protiv blokiranja točkova
Perić, Staniša LJ.
Факултет:Универзитет у Нишу, Електронски факултет
Датум одбране дисертације:12-03-2016
Đorđević, Goran S.
МетаподациПриказ свих података о дисертацији
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The main goal of research in this PhD dissertation is to investigate the possibilities of application of modern control methods in anti-lock braking system (ABS), in order to increase the safety of passengers in traffic during vehicle emergency braking. The complete historical overview of ABS development is also presented, as well as the basic components of the system. Bearing in mind that the testing of newly designed algorithms is impractical on the real system, the laboratory experimental setup of ABS is used. The modeling of system using different methods is performed first, resulting in several models, where each of them could be used during the design of a specific control method. Since it is demonstrated that the model describing the dynamics of ABS is quite nonlinear, a special emphasis is placed on the use of sliding mode control, both in the continuous- and discrete-time domains. This dissertation also analyzes the possibility of combining sliding mode control with
intelligent control methods, such as fuzzy control systems, genetic algorithms and neural networks, all with the aim of overcoming the shortcomings of the certain control methods and improving system performances. Fuzzy control theory and genetic algorithms are implemented in setting the parameters of control laws, eliminating the need to adjust the parameters by trial and error method. In the domain of neural networks, the significant modifications in the traditional adaptive neuro-fuzzy inference system (ANFIS) are introduced, whereby almost orthogonal functions are inserted in particular network layer. The further network adaptation is performed by introducing external stimulus in the form of hormone secretion from the glands of the endocrine system. It is also designed a new structure consisting of almost orthogonal endocrine neural networks and nonlinear autoregressive neural network with external input (NARX) that is used during the prediction of modeling error. In the end, it is important to emphasize that the justification for introducing and the effectiveness of the proposed control algorithms are verified by a series of laboratory experiments with a comparative analysis of the obtained results with the results of the application of well-known control methods.Више
Кључне речи:ABS, klizni režimi, ortogonalni filtri, minimalna varijansa, fazi regulator, genetički algoritam, neuronska mreža, ANFIS, NARX; ABS, sliding mode, orthogonal filters, minimum variance, fuzzy regulator, genetic algorithm, neural network, ANFIS, NARX