FPGA Implementation of Fuzzy based PID Controller using VHDL for Transport Application on the Internet of Vehicles

FPGA Implementation of Fuzzy based PID
Controller using VHDL for Transport Application
on the Internet of Vehicles(IOV)
Ashmi T. Issac
, Anish M.Jose y
Department of Electronics and Communication Engineering Viswajyothi College of Engineering and Technology
Ernakulam, India
Email: [email protected]
yEmail: [email protected]
Abstract —This paper presents the implementation of an ef-
fective Fuzzy based PID controller using VHDL for transport
applications on the internet of the vehicle using Field Pro-
grammable gate array (FPGA)technology.Communications in
this IOV based trafc management are communications between
the vehicle and the vehicle user, communication between the
vehicles, communication between the vehicle and the third party.
In communication between the vehicle and the user, few attributes
of the vehicle like the vehicular speed, fuel level etc. are directly
reported to the user when the user is inside the vehicle or
away from the vehicle.In Communication between two vehicles,
a fuzzy-based PID controller is developed in order to avoid
collisions when the vehicle is on the road or even when the
vehicle is parked.If the vehicle undergoing accident it will send
a notication to the third party like police patrol, ambulance.
They can nd the exact location of the vehicle through GPS
coordinates which are sent by the vehicle. The main aim of this
paper is that the chip developed in this way is cheaper and can
be applied to national cars. This can reduce the road accidents
and ensure the safety of the road user in future.
Keywords:-IOV based trafc management, fuzzy,
VHDL,PID algorithm,Synthesis
I. IN T RO D U C T I O N
The recent study of WHO, approximately 1.2 million people
lost their lives in road accident per year, and about 50 million
got injured in the trafc accident. Today vehicles play a major
role in our day to day life. Nowadays the Number of vehicles is
increasing faster than the number of roads, leading to frequent
trafc accidents.Before a couple of decades, the internet has
been all around the world. And is used to connect computers
together, sharing data, sharing information and also to interact
people around the world. All the surrounding smart devices
(things) that are connecting to the internet are simply called
internet of things.
Smart devices are any mechanical or electronic devices that
can make intelligent decisions on its own.it would be the
smartphone,smart TV, smart washing machine etc. when these
smart things connected to the internet are limited to vehicles
are called internet of vehicles1. Regarding the development
of next-generation intelligent transportation system, internet
of vehicles is intended to play an essential role. For IOV to see its full potential there are many challenges that need to
be addressed, including collecting real-time vehicle informa-
tion, enhancing on-time delivery rate, optimizing dispatch and
eet management to improve the operating performance and
reducing the manpower and fuel costs. The ultimate goal is to
achieve a more efcient, safe and green world transportation.
There are a lot of systems that support the drivers to avoid
accidents such as adaptive cruise control, trafc sign recogni-
tion etc.
In this paper focus on the internet of vehicles based trafc
management system17include 3 communications:
1.Communication between the vehicle and the vehicle user.
2.Communication between the vehicles.
3.Communication between the vehicle and a third party like
police patrol,ambulance.
An integrated hardware and software design method is devel-
oped to implement on FPGA chip over the past few years,
there has been phenomenal progress in FPGA technology.
Going from simple glue logic to impressive programmable
systems on a chip. Today FPGA’s are some of the most pow-
erful and exible devices ever built.FPGAs are the integrated
circuits can recongure or reprogrammable5.They are widely
popular due to rapid advancement and also it can modify the
device functions. Simulation is done in VHDL language2.Is
very deterministic and strongly typed and harder to make typo
type mistakes and more verbose than Verilog. The automotive
industry going through a massive transformation driven by
grateful digital technology as the growth of technology from
the consumer electronics and information technology cross
over to automotive industry. Now the modern vehicle is
equipped with powerful sensors and networking and com-
munication drivers8. In connected vehicle technology each
vehicle can talk to the driver when the driver is away from
the vehicle or inside the vehicle through the internet and also
can communicate with infrastructure.

II. COMMUNICATION BETWEEN THE VEHICLE
AND THE VEHICLE USER
Few attributes of the vehicle like vehicular speed, fuel level,
tire pressure, the vehicular lock condition are directly reported
to the user through onboard Screen and also active updates
about the vehicle are getting from mobile. When the user is
away from the vehicle.
III. COMMUNICATION BETWEEN THE VEHICLES A fuzzy-based PID controller is developed in order to avoid
collisions. When the vehicle is on the road or even when
the vehicle is parked. The system sense distance between two
adjacent vehicles and decreases the speed in accordance with
the distance between them in a decreasing nature. If the two
vehicles getting close to each other then the system will apply
sudden break2. PID controller is widely used in industrial
process control systems. The popularity of PID controller
is because of their robust performance9 in wide range of
operating conditions and functional simplicity. PID algorithm
consists of three basic coefcients. Proportional, integral and
derivative. Which are varied to get optimal response. The PID
control algorithm has sufcient exibility to yield the excellent
result. And is linear in nature. Conventional PID controller is
not suitable for the non-linear system1011. So introduce a
fuzzy-based approach to it. Fuzzy logic has been successful to
control non-linearity and uncertainty of a system. Fuzzy based
PID controller has better stability and fast response compared
with conventional PID controller. The fuzzy logic controller
can work with less precise input and it doesnt need a fast
processor, this is the reason for choosing fuzzy logic controller.
The fuzzy controller is the optimal discrete time version of the
conventional PID controller. The control signal generated by a
PID controller in the continuous time domain34is described
by,
U t=K
Pet
+k
IZ
t
0 e
( )d ( ) + k
D de
(t) dt
(1)
Where e(t) is the error signal K
P; K
I; K
Dare the propor-
tional, integral, derivative constants respectively. The equation
can be represented in frequency domain3
VS =
E(S )K
P K
I S
+
K
DS
(2)
Equation can be transformed into discrete version by apply-
ing the bilinear transformation.
S= 2 T

1
Z
1 1 +
Z1
(3)
Where T ;0in the sampling Period. Then it becomes.
U P I D (
Z ) = K
P K
IT 2

2
K
D T
+
K
IT 1 +
Z1 + K
D T
1 1 +
Z1
(4)
K P =
K
P K
IT 2

2
K
D T
; K
I= K
IT ;
K
D = K
D T

(5)
PID Controllers can be described by the equations
KP =
K
Pe
(K ) + K
Ie
(K ) + K
Dde
(K ) (6)U
(K ) = Outputcontrolsignal;
e (K ) = error;
e (K ) = accumulativeerror (rateof changeinerror );
de (K ) = derivativeerror (changeinerror )
Non-linearity in PID controlling algorithm can be achieved
by using fuzzy logic into it. Fuzzication, control rule base
establishment, defuzzication are the procedure for designing
fuzzy based PID controller in a PID controller there is 3
input as proportional, integral, derivative because of more
parameters are needed to be considered in building the fuzzy
control rule base6.So 3 input of the controller is dened as
the error (e), change in error (e) and rate of change of error
( 2
e ) 2.The component of FLC is an interface engine and
a set of linguistic if-then rules. That encode the speed of the
vehicle with the distance from the other vehicle or obstacle
the main difculty is designing a fuzzy logic controller is the
efcient formulation of fuzzy if-then rules. Rule base increase
with increase in member ship function 212. Where e, de, e
are the input variables and K
P; K
I; andK
Dare the constants
same as in the conventional PID controller equation. Fig. 1: Flow chart of PID type fuzzy controller algorithm
Fuzzy implementation can be performed by taking the
product. Total no of the if-else rule can be obtained by taking
the product of total no of inputs and the total no membership
function3. Fig. 2: input output member ship functions

Fig. 3: RTL view of PID type fuzzy controller system
IV. COMMUNICATION BETWEEN VEHICLE AND THE THIRD PARTY
The data regarding the vehicular collisions or accident are
sent to the server from the chip that is integrated into the
vehicle through a communication device. From this server, the
data is forwarded to a third party like police patrol, ambulance.
These third parties take the vehicle into consideration and
provide necessary assistance. Server decides when this third
party need to be triggered and the information regarding how
to classify the incoming data with primary importance. These
are predened on the servers decision-making algorithm. In
the server the data that stores in the database and analyses the
data for the crack 1.
V. RESULTS
Synthesis is the process by which representation of the
desired circuit behaviour. And this process is done using synthesis tools. In synthesising the compiled code of VHDL is
turned into a design implementation in terms of logic gates2.
The RTL view of fuzzy based PID controller on the internet
of vehicles is shown in below. Fig. 4: The RTL view of fuzzy based PID controller on internet
of vehicles
VI. CONCLUSION
This paper has presented a novel way to implement a fuzzy
based PID controller for Transport applications of the internet
of vehicles using FPGA. The application of FPGA structure
is very suitable for the high-speed process. The main aim of
this project is that the chip developed in this way is cheaper
and can be applied to national cars. This can reduce the road
accidents and ensure safety the of the road user in future
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