Adaptive Finite-Time NN Control for 3-DOF Active Suspension Systems With Displacement Constraints

In this paper, the displacement constraints and finite-time control problems are handled for 3 degrees of freedom (DOF) active suspension systems (ASSs). In order to ensure that seat and active suspension’s displacements do not violate their limits, the Barrier Lyapunov functions (BLFs) are employed to handle displacement constraints problem, and the ride comfort and safety are improved at the same time. The unknown functions in the ASSs are approximated by using the neural networks (NNs). The traditional finite-time controller often contains the sign functions or absolute value functions, and they cause the problem about buffeting of the controller. By using NNs, finite-time theory, and BLFs, an adaptive finite-time control approach is constructed to avoid this problem. Then, the boundedness of all signals of 3-DOF ASSs is testified by the semi-global practical finite-time stability analysis and a zero dynamics analysis. In addition, the results of two numerical examples demonstrate the effectiveness of the established adaptive finite-time NN control scheme.