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Active control of a suspension system is intended to provide isolated behavior of the spring mass of that system (e.g., increased comfort, performance, etc.). In this research work, I want to explain the importance of developing an intelligent active control approach for truck suspensions based on artificial neural network (ANN). Hence the main objective of this thesis is to obtain a mathematical model for active suspension systems and then build a hydraulic model for active suspension control for trucks using artificial neural network (ANN). In this context, a corresponding non-linear ANN active suspension controller was designed and optimized for approximate road profiles using simulation according to ISO 2631-5 and ISO 8608. The model developed with MATLAB Toolbox, estimated and validated from data collected from tests performed with a truck according to other research works. The simulation results show that this new methodology offers excellent performance.