Antlion optimizer tuned PID controller based on Bode ideal transfer function for automobile cruise control system

2018 ◽  
Vol 9 ◽  
pp. 45-52 ◽  
Author(s):  
Rosy Pradhan ◽  
Santosh Kumar Majhi ◽  
Jatin Ku Pradhan ◽  
Bibhuti Bhusan Pati
2017 ◽  
Vol 21 (5) ◽  
pp. 347-361 ◽  
Author(s):  
Rosy Pradhan ◽  
Santosh Kumar Majhi ◽  
Jatin Kumar Pradhan ◽  
Bibhuti Bhusan Pati

2021 ◽  
Vol 1208 (1) ◽  
pp. 012040
Author(s):  
Amel Toroman ◽  
Samir Vojić

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.


2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
M. N. Ab Malek ◽  
M. S. Mohamed Ali

For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques. Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system. This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly. Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model. The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero. The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.


2021 ◽  
Vol 2115 (1) ◽  
pp. 012023
Author(s):  
M Manju Prasad ◽  
M A Inayathullah

Abstract The Proportional Integral Derivative (PID) controller is an effective and common feedback control design used in closed loop control systems. One such best consideration of closed loop control system would be cruise control system. This is a system that automatically controls the speed of an electric vehicle despite external disturbances. In this paper, the goal is to design a PID controller using root locus technique for a closed loop cruise control system. By root locus approach, the controller constants and controller design is finalized. Simulation results through MATLAB environment validate the effectiveness of controller design.


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