Fuzzy based PID Controller using VHDL for Transportation Application (original) (raw)

Design and Synthesis of PID Controller Based on Fuzzy

2006

Abstract: - This paper describes the hardware implementation of a PID-type (Proportional-Integral - Derivative) Fuzzy Logic Controller (FLC) algorithm using VHDL to use in transportation cruising system. The cruising system has developed to avoid the collisions between vehicles on ...

Mamdani and Sugeno Fuzzy Logic Approach of PID Controller

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

The design of a PID-type (Proportional-Integral-Derivative) controller based on a Fuzzy algorithm for deployment in a transportation cruising system is described in this work. To avoid collisions, a cruising system based on the Fuzzy rules has been developed. On the road, there are crashes between vehicles. Fuzzy Logic is a new type of logic which serves as a point of reference for driving the vehicle. It either increases or reduces the speed depending upon the speed of front, rear and ego vehicle. The speed of control is determined by the preceding vehicle's distance when it becomes too close and alerts the driver when required. There are two theories on fuzzy logic the first given by Mamdani and the other was given by Sugeno.

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

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.

FPGA Implementation of Fuzzy PID Controller for Transportation on the Internet of Vehicles (IOV)

2018

Implementation of Fuzzy PID controller for transportation on the internet of vehicles (IOV) using field programmable gate array technology (FPGA) technology. The IOV based traffic management enables the vehicle to communicate with their internal and external environment, supporting the interaction of vehicle to human, vehicle to vehicle, the vehicle to third-party. In vehicle to human communication, the driver will receive the warning message about vehicular speed, fuel level, door lock condition etc when the driver is inside the vehicle or away from the vehicle. In the vehicle to vehicle communication, a fuzzy PID controller is developed for avoiding collisions. If the vehicle undergoing accident it will send a notification message to the third party like police patrol, ambulance. They can find the exact location of the vehicle through the GPS coordinates which are sent by the vehicle. The chip developed in this way is cheaper and can be introduced to national cars. These cars can ...

Comparison of PID, GA and Fuzzy Logic Controllers for Cruise Control System

International Journal of Computing and Digital Systems, 2018

Nowadays, automobile companies give good attention of cruise systems and cruise controllers which are considered as one of the most critical aspects that require precise controller that can accommodate the new development in technology. The movement of running automobiles is variable and complex. For this reason, cruise control system (CCS) has high non-linearity and if a traditional PID controller has been used, it will not give good results in all conditions. This paper presents comparative study of PID controller, PID optimized by GA and fuzzy logic controllers for an automobile cruise control system (ACCS) where it has been used on linearized model of the cruise system. The comparison was for the transient performance; i.e. settling time, rise time and maximum overshoot in addition to the steady state performance i.e. steady state error. MATLAB/SIMULINK and m-file have been used to show the efficiency of each method used and shows the comparison between them. The results indicate that the performance of fuzzy controller has better response regarding the overshoot and the settling time while the PID tuned by using GA gives the shortest rising time. A comparative analysis of each simulated result will be done based on the response characteristic.

Designing Fuzzy VSPID Controller for Vehicle Speed Control

The PID controller has been extensively used in control applications. This is mainly due to the fact that despite the simple structure and ease of design of this controller, it still has some degree of robustness. In PID control method, three parameters, namely proportional, integral, and derivative, are being determined in such a way that the response of the system is satisfactory. The proportional part of the PID controller has an important role in determining the overshoot and the rise time, while the integral part reduces the steady-state error, and the derivative portion of the controller is mainly responsible for the stability of the closed-loop system and the smoothness of the response. But the major limitation of PID controller is that its response is only acceptable if the system is working around the operating point, especially when the nonlinearity of the system is complicated. Hence, there is need for more sophisticated control method [1]. Several methods have been proposed in the literature to overcome the weaknesses of the PID controller. Among these methods, there are Zeigler-Nichols PID [10], fuzzy

A Model for Vehicle Dynamic Simulation with PID and Fuzzy Logic Drive Controllers

Ann Arbor, 2000

A computer code oriented to S.I. engine control and powertrain simulation is presented. The model predicts engine and driveline states, taking into account the dynamics of air and fuel flows into the intake manifold and the transient response of cranks'haft, clutch, transmission gearing and vehicle. The whole model is integrated in the code O.D.E.C.S., now in use at Magneti Marelli, and is based on a hierarchical structure composed of different classes of models, ranging from black-box Neural Network to grey-box mean value models. By adopting the proposed approach, a satisfactory, accuracy is achieved with limited computational demand, which makes the model suitable for the optimization of engine control strategies. Furthermore, in order to simulate the driver behavior during the assigned vehicle mission profile, two drive controllers have been implemented for throttle and brakes actuation, based on classical PID and fuzzy-logic theoD'. In the paper a detailed description of the whole driveline system is presented and the results achieved making use of both driver-behavior models are compared with respect to a set of arbitraD' transient maneuvers and vehicle speed profiles.

Developing Adaptive Cruise Control Based on Fuzzy Logic Using Hardware Simulation

International Journal of Electrical and Computer Engineering (IJECE), 2014

Ride comfort on the highway often interrupted because drivers need to adjust the vehicle speed. Safe distance between vehicles should be maintained is the main reason. The situation of monotonous and high speed will increase the risk of accidents on highway. A device is required by the driver to adjust the vehicle speed during the long distance (cruise) driving on highway without neglecting the safety aspects. The device is known as Adaptive Cruise Control (ACC). The ACC is a subsystem of Advanced Driver Assistance Systems (ADASs) that serves to assist the driver during cruise driving. The working principle of the ACC is the vehicle speed set automatically so that the distance to the vehicle in front remains safe. This paper presents the development of fuzzy logic controller for ACC. The fuzzy inference method used in this study is Mamdani. The result from hardware simulation that using remote control car shows that the fuzzy logic controller can work according to the design.

Vehicle Yaw Rate Control Based on Fuzzy PID Control Technology

In this paper, control of vehicle yaw stability system is studied by using a two vehicle models where the first one is a linear two degree of freedom vehicle model to design the controller and the other one is a planar motion model which represents a nonlinear vehicle model (actual vehicle). The strategy of vehicle yaw stability control based on the yaw rate control which adopts the fuzzy PID controller. Compared to traditional PID control, the fuzzy PID control can adjust and tune the proportional, integral and derivative parameters and make efficient the system responds. To make sure that Fuzzy PID controller works well, it will be tested at two cases of input steering angle of the vehicle front tires which are a step signal maneuver and a single-lane-change maneuver. Various of computer simulations and results show that the control system of vehicle yaw stability and using of fuzzy PID controller can improve the stability and handling of vehicle significantly.