Nonlinear control systems: an introduction (2nd ed.)
Nonlinear control systems: an introduction (2nd ed.)
Feedback linearization using neural networks
Automatica (Journal of IFAC)
Survey of advanced suspension developments and related optimal control applications
Automatica (Journal of IFAC)
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Direct adaptive neural control for affine nonlinear systems
Applied Soft Computing
H∞robust control of active suspensions: a practical point of view
ACC'09 Proceedings of the 2009 conference on American Control Conference
Input Constraints Handling in an MPC/Feedback Linearization Scheme
International Journal of Applied Mathematics and Computer Science
International Journal of Applied Mathematics and Computer Science
IEEE Transactions on Intelligent Transportation Systems
Sliding mode neural network inference fuzzy logic control for active suspension systems
IEEE Transactions on Fuzzy Systems
A neural approach for control of nonlinear systems with feedback linearization
IEEE Transactions on Neural Networks
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This paper presents the design of a neural network based feedback linearization (NNFBL) controller for a two degree-of-freedom (DOF), quarter-car, servo-hydraulic vehicle suspension system. The main objective of the direct adaptive NNFBL controller is to improve the system's ride comfort and handling quality. A feedforward, multi-layer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is developed using input-output data sets obtained from mathematical model simulation. The NN model is trained using the Levenberg-Marquardt optimization algorithm. The proposed controller is compared with a constant-gain PID controller (based on the Ziegler-Nichols tuning method) during suspension travel setpoint tracking in the presence of deterministic road disturbance. Simulation results demonstrate the superior performance of the proposed direct adaptive NNFBL controller over the generic PID controller in rejecting the deterministic road disturbance. This superior performance is achieved at a much lower control cost within the stipulated constraints.