Synteza układu sterowania semiaktywnego zawieszenia samochodu z elementami magnetoreologicznymi
Wariant tytułu
Synthesis of semi-active suspension control system with magneto-rheological elements
Autor
Nabagło, Tomasz
Promotor
prof. zw. dr hab. inż. Bogdan Fijałkowski
Data wydania
2006
Wydawca
[s.n.]
Język
polski
Abstrakt
Tematem niniejszej rozprawy jest synteza układu sterowania semiaktywnego zawieszenia samochodu z tłumikami magneto-reologicznymi. Rozprawa obejmuje zarówno modelowanie układu sterowania semiaktywnego zawieszenia samochodu jak i jego optymalizację. Modelowanie to oparto na różnego rodzaju modelach fizycznych zawieszenia samochodu począwszy od najprostszego ćwiartkowego modelu fizycznego zawieszenia samochodu a skończywszy na pełnym modelu fizycznym samochodu o ponad 90 stopniach swobody. W pracy poruszono również problem modelowania neuronowego w zastosowaniu do tworzenia nieliniowego modelu fizycznego tłumika magneto-reologicznego. Praca zawiera także zarys teorii samochodu dotyczącej istniejących rozwiązań zawieszeń samochodowych i ich sterowania. Praca rozpatruje układ sterowania oparty o logikę rozmytą, a w procesie jego optymalizacji wykorzystuje optymalizacyjne algorytmy genetyczne. Efektywność sterowania i optymalizacji została potwierdzona przez liczne testy symulacyjne modeli fizycznych semiaktywnego zawieszenia samochodu w oparciu o jeden z najpopularniejszych w tej dziedzinie programów komputerowych do celów modelowania i symulacji, a mianowicie program MSC.ADAMS. W procesie symulacji pełnego modelu samochodu zastosowano tzw. proces ko-symulacji między modelem samochodu w programie ADAMS/Car a modelem sterownika logiki rozmytej w programie MATLAB-Simulink.
In this PhD thesis, the author presents synthesis of a semi-active suspension control system with the magneto-rheological dampers. The main objective of this control system is a drive comfort improvement. The thesis encloses a modeling process as well as semi-active suspension control process and its optimization. Modeling process is based on various kinds of physical models with an effect of the simplest quarter-car model with the Volkswagen Golf parameters as well as a quarter-car model with the Ferrari Testarossa parameters. The final model is a full-car physical model with 90 degrees of freedom and parameters of the full-car Ferrari Testarossa. In the thesis, the author describes a neural-network model of the magneto-rheological damper, which parameters were applied in the simulations on the quarter-car models with the Ferrari Testarossa parameters as well as on the full-car model of this car. The thesis connected with simulations was divided between two parts. In the first part the author works on control optimization and its results verification for Volkswagen Golf linear model. In the second part the optimization process as also its verification were conducted for nonlinear models of the quarter-car and full-car with parameters of Ferrari Testarossa. The author describes also an outline of theory of car suspensions existing solutions as well as its control systems. This control system proposed in this work is based on the fuzzy logic, which is optimized with genetic algorithms. In the optimization process, a simple quarter-car model is applied. This model is based on parameters of the Ferrari Testarossa full car physical model. In the thesis, the author examines a control system based on the fuzzy logic, which is optimized by genetic algorithms. Through optimization process the parameters of the optimal fuzzy logic controller obtained. Optimization of the fuzzy logic controller with reduced number of optimized parameters is a new element proposed by the author. This task has been chosen for maximal effectiveness keeping and in the same time for the optimization time reduction. The main novelty of the work is usage of improved version of so called "grid and seed" method, which is used for fuzzy rules optimization. The effectiveness of the control and optimization was confirmed in numerous simulations of physical models of the car semi-active suspensions in one of the most popular program MSC.ADAMS. This program is the most popular in this discipline. Next significant element is usage of semi-active car suspension with a nonlinear neural model of the magneto-rheological damper for Ferrari Testarossa car model. This model is a result of co-simulation between ADAMS/Car with mechanical part of the model and MATLAB-Simulink with the optimal fuzzy logic controller. In this thesis, the author also presents time waveforms and step-function response of the sprung and unsprung mass vertical accelerations, as well as indicators of ride comfort and safety improvement.
Klasyfikacja PKT
372321 Samochody
372300 Przemysł środków transportu
370000 Budowa maszyn. Przemysł maszynowy i metalowy
