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This paper studies the controller design for automatic steering of vehicles tracking a desired path. A nonlinear model with coupled inputs is considered and a suitable transformation is applied to deal with the nonlinearities. Nonlinear sliding surfaces are designed using Lyapunov approach to deal with the nonlinear effects. Simulation results are given to show that the designed controller is effective.

This paper deals with the controller design problem for automatic steering of vehicles. The nonlinear and uncertain lateral motion model of the vehicle is considered. The sliding mode controllers, with LQ optimal sliding surface and with guaranteed cost sliding surface, are proposed such that the lateral velocity and the yaw rate are stabilized. The robustness of the controllers is verified by comparing the simulation results.

This work deals with Diesel engine exhaust emissions modelling. Although, the combustion process in internal combustion engine is very complex, the formation of products can then be predicted in order to control automotive polluting emissions. Firstly, we have defined a neural network structure based on the determination of time delays, input and output orders, and finally number of hidden layer neurons. Secondly, the proposed model has been applied on Diesel engine process. An Artificial neural networks (ANN) describing the prediction of exhaust emissions through its parameters is given