Observer-based Adaptive Optimal Control for Unknown Singularly Perturbed Nonlinear Systems With Input Constraints

This paper introduces an observer-based adaptive optimal control method for unknown singularly perturbed nonlinear systems with input constraints. First, a multi-Time scales dynamic neural network MTSDNN observer with a novel updating law derived from a properly designed Lyapunov function is proposed to estimate the system states. Then, an adaptive learning rule driven by the critic NN weight error is presented for the critic NN, which is used to approximate the optimal cost function. Finally, the optimal control action is calculated by online solving the Hamilton-Jacobi-Bellman HJB equation associated with the MTSDNN observer and critic NN. The stability of the overall closed-loop system consisting of the MTSDNN observer, the critic NN and the optimal control action is proved. The proposed observer-based optimal control approach has an essential advantage that the system dynamics are not needed for implementation, and only the measured input U+002F output data is needed. Moreover, the proposed optimal control design takes the input constraints into consideration and thus can overcome the restriction of actuator saturation. Simulation results are presented to confirm the validity of the investigated approach. © 2014 Chinese Association of Automation.

Dynamic Rollover Prediction of Heavy Vehicles Considering Critical Frequency

Rollover of commercial heavy vehicles can cause enormous economic losses and fatalities.It is easier for such vehicles to rollover if the driver’s steering frequency is close to the critical frequency of the vehicle’s roll motion;however,the critical roll frequency has rarely been investigated.In this study,the second-order transfer function between the steering input and roll angle was developed to calculate the critical frequency of the vehicle’s roll motion.The simulated spectrum and transfer function were then used to dynamically predict the peak lateral load transfer ratio.Laboratory experiments were conducted using a scaled vehicle to verify the critical roll frequency.The results suggest that the peak value of the lateral load transfer ratio during steering can be accurately determined from the driver’s input,and the critical roll frequency has a dominant effect on the dynamic rollover of heavy vehicles.