The Speed Control Design Based on Fuzzy Logic

2014 ◽  
Vol 716-717 ◽  
pp. 1540-1544
Author(s):  
Ting Gong ◽  
Hui Yan
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Design ◽  
Operating Conditions ◽  
Time Varying ◽  
Cruise Control ◽  
Cruise Control System ◽  
Highly Nonlinear ◽  
Fuzzy Pd

The cruise control system has the highly nonlinear and time-varying uncertainty, and it will also influenced by the outside disturbance and complex operating conditions, and it is difficult to obtain a satisfied effect by using traditional PID control. In this paper, the auto cruise control system is designed based on fuzzy PI and fuzzy PD control algorithm, and the simulated effect is also provided.

scholarly journals LPV-based Control Design of an Adaptive Cruise Control System for Road Vehicles

2015 ◽  
Vol 48 (14) ◽  
pp. 62-67 ◽  
Author(s):  
Balázs Németh ◽  
Péter Gáspár ◽  
Rodolfo Orjuela ◽  
Michel Basset
Keyword(s):  
Control System ◽  
Adaptive Cruise Control ◽  
Control Design ◽  
Cruise Control ◽  
Road Vehicles ◽  
Adaptive Cruise Control System ◽  
Cruise Control System

scholarly journals Design and Implementation of Fuzzy Approximation PI Controller for Automatic Cruise Control System

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Pallab Maji ◽  
Sarat Kumar Patra ◽  
Kamalakanta Mahapatra
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Large Change ◽  
Nonlinear Process ◽  
Cruise Control ◽  
Fuzzy Logic Systems ◽  
Heuristic Knowledge ◽  
Cruise Control System ◽  
Highly Nonlinear

Fuzzy logic systems have been widely used for controlling nonlinear and complex dynamic systems by programming heuristic knowledge. But these systems are computationally complex and resource intensive. This paper presents a technique of development and porting of a fuzzy logic approximation PID controller (FLAC) in an automatic cruise control (ACC) system. ACC is a highly nonlinear process and its control is trivial due to the large change in parameters. Therefore, a suitable controller based on heuristic knowledge will be easy to develop and provide an effective solution. But the major problem with employing fuzzy logic controller (FLC) is its complexity. Moreover, the designing of Rulebase requires efficient heuristic knowledge about the system which is rarely found. Therefore, in this paper, a novel rule extraction process is used to derive a FLAC. This controller is then ported on a C6748 DSP hardware with timing and memory optimization. Later, it is seamlessly connected to a network to support remote reconfigurability. A performance analysis is drawn based on processor-in loop test with Simulink model of a cruise control system for vehicle.

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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