He Defeng

Adaptive cruise control of vehicles subject to Denial-of-Service

In this paper, we present an adaptive cruise controller with time-varying sampling period for the case that the local communication network of vehicles is subjected to denial of service (DoS) attacks. Combining the model of adaptive cruise control systems and the linear quadratic optimal control (LQR) method, the adaptive cruise controller of vehicles is designed. Then dependence of the sampling interval with closed-loop input-to-state stability of vehicle adaptive cruise systems subject to Dos attacks is analyzed by the concept of input-to-state stability. The admissible upper limit of the duty ratio for DoS attacks that the LQR cruise controller of the vehicle can endure is computed. Moreover, some appropriate sampling period is given to make the cruise controller satisfy the input-to-state stability robust index. Finally, the effectiveness of the obtained results is demonstrated by numerical simulation experiments.

The design of the operation monitoring and statistics analysis system for taxi based on the GPS information

In order to strengthen the management of taxi and implement effective regulation and control on the taxi operation, one design approach of the operation monitoring and statistics analysis system for taxi based on the GPS information was developed in this paper. Firstly the taxi operation monitoring and statistical analysis index system is drawn up in this paper, and then the key technology of the operation monitoring and statistics analysis system for taxi was analyzed. Finally the operation monitoring and statistics analysis system for taxi was effectively designed. This approach can effectively compensate the shortcomings of the operation monitoring and statistics analysis system for taxi in china, and achieve the goals for protecting environment, saving resources and improving countrys comprehensive competitiveness.

Pole placement-based NMPC of Hammerstein systems and its application to grade transition control of polypropylene

This paper presents a new nonlinear model predictive control (MPC) algorithm for Hammerstein systems subject to constraints on the state, input, and intermediate variable. Taking no account of constraints, a desired linear controller of the intermediate variable is obtained by applying pole placement to the linear subsystem. Then, actual control actions are determined in consideration of constraints by online solving a finite horizon optimal control problem, where only the first control is calculated and others are approximated to reduce the computational demand. Moreover, the asymptotic stability can be guaranteed in certain condition. Finally, the simulation example of the grade transition control of industrial polypropylene plants is used to demonstrate the effectiveness of the results proposed here.