A speed feedback control strategy for car-following model

2014 ◽  
Vol 413 ◽  
pp. 343-351 ◽  
Author(s):  
Wen-Xing Zhu ◽  
Li-Dong Zhang
Keyword(s):  
Feedback Control ◽  
Control Strategy ◽  
Car Following ◽  
Car Following Model ◽  
Feedback Control Strategy

scholarly journals The Feedback Control Strategy of the Takagi-Sugeno Fuzzy Car-Following Model with Two Delays

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Cong Zhai ◽  
Weiming Liu ◽  
Ling Huang
Keyword(s):  
Feedback Control ◽  
Linear Matrix Inequality ◽  
Control Strategy ◽  
Traffic Congestion ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Car Following ◽  
Car Following Model ◽  
Two Delays ◽  
Feedback Control Strategy

Considering the driver’s sensing the headway and velocity the different time-varying delays exist, respectively, and the sensitivity of drivers changes with headway and speed. Introducing the fuzzy control theory, a new fuzzy car-following model with two delays is presented, and the feedback control strategy of the new fuzzy car-following model is studied. Based on the Lyapunov function theory and linear matrix inequality (LMI) approach, the sufficient condition that the existence of the fuzzy controller is given making the closed-loop system is asymptotic, stable; namely, traffic congestion phenomenon can effectively be suppressed, and the controller gain matrix can be obtained via solving linear matrix inequality. Finally, the simulation examples verify that the method which suppresses traffic congestion and reduces fuel consumption and exhaust emissions is effective.

scholarly journals An Optimal Feedback Control Strategy for Nonlinear, Distributed-Parameter Processes

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 758 ◽  
Author(s):  
Debaprasad Dutta ◽  
Simant Ranjan Upreti
Keyword(s):  
Feedback Control ◽  
Oil Recovery ◽  
Control Strategy ◽  
Moving Boundary ◽  
State Feedback Control ◽  
Optimal Feedback Control ◽  
Distributed Parameter ◽  
Optimal State ◽  
Non Linear ◽  
Feedback Control Strategy

In this work, an optimal state feedback control strategy is proposed for non-linear, distributed-parameter processes. For different values of a given parameter susceptible to upsets, the strategy involves off-line computation of a repository of optimal open-loop states and gains needed for the feedback adjustment of control. A gain is determined by minimizing the perturbation of the objective functional about the new optimal state and control corresponding to a process upset. When an upset is encountered in a running process, the repository is utilized to obtain the control adjustment required to steer the process to the new optimal state. The strategy is successfully applied to a highly non-linear, gas-based heavy oil recovery process controlled by the gas temperature with the state depending non-linearly on time and two spatial directions inside a moving boundary, and subject to pressure upsets. The results demonstrate that when the process has a pressure upset, the proposed strategy is able to determine control adjustments with negligible time delays and to navigate the process to the new optimal state.

Sign in / Sign up

Export Citation Format

Share Document