Evaluating performance of extended Kalman filter based adaptive cruise control using PID controller

2021 ◽  
Author(s):  
Fahmida Islam ◽  
M. M. Nabi ◽  
Md Mehedi Farhad ◽  
Preston L. Peranich ◽  
John E. Ball ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Pid Controller ◽  
Adaptive Cruise Control ◽  
Cruise Control

Using improved chaotic ant swarm to tune PID controller on cooperative adaptive cruise control

Optik ◽  
2016 ◽  
Vol 127 (6) ◽  
pp. 3445-3450 ◽  
Author(s):  
Xingchen Wu ◽  
Guihe Qin ◽  
He Yu ◽  
Song Gao ◽  
Liu Liu ◽  
...  
Keyword(s):  
Pid Controller ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control

scholarly journals Adaptive Single Neuron Anti-Windup PID Controller Based on the Extended Kalman Filter Algorithm

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 636
Author(s):  
Jesus Hernandez-Barragan ◽  
Jorge D. Rios ◽  
Alma Y. Alanis ◽  
Carlos Lopez-Franco ◽  
Javier Gomez-Avila ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Pid Controller ◽  
Single Neuron ◽  
Experimental Tests ◽  
Pid Controllers ◽  
Training Algorithm ◽  
Omnidirectional Mobile Robot ◽  
Back Calculation ◽  
Kalman Filter Algorithm

In this paper, an adaptive single neuron Proportional–Integral–Derivative (PID) controller based on the extended Kalman filter (EKF) training algorithm is proposed. The use of EKF training allows online training with faster learning and convergence speeds than backpropagation training method. Moreover, the propose adaptive PID approach includes a back-calculation anti-windup scheme to deal with windup effects, which is a common problem in PID controllers. The performance of the proposed approach is shown by presenting both simulation and experimental tests, giving results that are comparable to similar and more complex implementations. Tests are performed for a four wheeled omnidirectional mobile robot. Tests show the superiority of the proposed adaptive PID controller over the conventional PID and other adaptive neural PID approaches. Experimental tests are performed on a KUKA® Youbot® omnidirectional platform.

scholarly journals Adaptive car control system based on a predictive model

2021 ◽  
Vol 1208 (1) ◽  
pp. 012040
Author(s):  
Amel Toroman ◽  
Samir Vojić
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Predictive Model ◽  
Rise Time ◽  
Pid Controller ◽  
Control Algorithm ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Traffic Incidents ◽  
Cruise Control System

Abstract An adaptive control is a control, which by pre-setting the parameters of the controller, enables the control of processes whose parameters are time-varying or are initially uncertain. The possibilities and benefits of adaptive control are versatile and can be best demonstrated by applying the system while driving a car, or maintaining the optimal speed and distance between cars, which is shown in this paper. As the car’s weight decreases while driving due to fuel consumption, the control algorithm has to be adapted to the changed driving conditions. Accordingly, an adaptive control system using the Matlab software package, and an adaptive cruise control system (ACC) was created in this paper, which is based on a predictive model. After evaluating the developed model of adaptive car motion control, the output parameters such as speed, acceleration, and distance between the two vehicles were analyzed. In this paper a PID controller is used to reduce oscillations in the system. First, the P controller was used to reduce the rise time of the significant values, then the PI controller improved the rise time, and finally the PID controller achieved overshoot reduction performance without affecting the dynamic response system. The obtained results confirm the justified expectations for the possibility of adaptive car control utilization as one of the possible solutions to the increasing traffic incidents, as well as a measure to improve the reduction of these incidents.

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