Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 2 (September 2017) 175–178___________________________________________________________________________________________________________Fuzzy self-tuning PID control algorithm for belt conveyor driven by multi-motor
Caixia Gao

College of Electrical Engineering and Automation, Henan Polytechnic University, 2001 Century Avenue, Jiaozuo
454003, P.R.China
Fuzhong Wang

College of Electrical Engineering and Automation, Henan Polytechnic University, 2001 Century Avenue, Jiaozuo
454003, P.R.China
Ziyi Fu

College of Electrical Engineering and Automation, Henan Polytechnic University, 2001 Century Avenue, Jiaozuo
454003, P.R.China
E-mail: gcx81 @126.com, wangfzh@hpu.edu.cn, fuzy@hpu.edu.cn
www.hpu.edu.cn

Abstract
Aiming at the problems of low efficiency when long distance and high-inclination belt conveyor driven by multimotor is in light or idle run as well as electrical power unbalance. Control strategy for belt conveyor driven by fourmotor via fuzzy self-tuning PID control algorithm was proposed. The Speed setting algorithm of belt conveyor andfuzzy self-tuning PID algorithm for speed control and power balance control are introduced. The application showsthat, according to the coal flow changes of the belt conveyor in real-time, the speed can be automatically adjusted
through this algorithm, making the power of the four motors convergence both speed control error and the power
control error of which are lower than 2.6%.
Keywords: belt conveyor, power unbalance, fuzzy self-tuning PID

problem. For the above problems, scholars at home andabroad have also carried out researches, but mostly forthe smaller angle (35 °and below): Reference 1 uses
direct torque control strategy to achieve motor powerbalance control with fast response and good stability,
which is directly affected by the motor parameters. In
Reference2, what is proposed is a power balance control
strategy for mine belt conveyor motor based on torque

1. Introduction
In order to ensure the safe and stable operation of thetransport aircraft, the following problems need to besolved: (1) Mechanical damage of the equipment due tothe heavy load and the dynamic tension of the tapeduring start-up and stopping; (2) Running state power
consumption problem; (3) Multi-motor power balance

Copyright © 2017, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 2 (September 2017) 175–178___________________________________________________________________________________________________________tape speed with the given speed. When the belt speed
and the given speed is inconsistent, the controller firstadjust 1# CST servo proportional valve opening step bystep to change the output of 1# motor, then the otherthree motors automatically tracking the output power of
1#motor , so four CSTs work together to achieve theadjustment of the belt speed. The function of the speed
setting module is to determine the speed of the tapeduring starting, stopping and normal operationaccording to the coal flow rate in the belt.

compensation. The vector dual closed-loop controller isa conventional PI controller, and its adaptability is notstrong. Reference 3 uses the current control method toregulate the power balance of the belt conveyor, when
the current of each motor exceeds or falls below 5% of
the average current. Because of the characteristics oflarge inertia and severe hysteresis, the belt conveyor
with multi-motor drive is a time-varying and nonlinear
control object, It is difficult to adopt conventional fixedparameter PID control to achieve good control effect;when a single fuzzy controller is used, the response
speed is high, but its control accuracy is difficult tomeet the requirements. This paper proposes a fuzzycontrol algorithm based on fuzzy self-tuning PID
control algorithm for large-angle mining belt conveyor
driven by multi-motor, achieving flexible starting andstopping of belt conveyor, adjusting the speed according
to the size of the load automatically, and maintaining
multi-motor power balance.

coal flow

speed-given+-speed fuzzycontrol
module1#motor

KW
power balance
fuzzy control
module2#motor
KW

servo brakelinearclutch
1#CST

servo brake1#
rollerlinearclutch
2#CST

belt
power balance
fuzzy control
module3#motorKW

2. The general control model of high-inclination
belt conveyor

power balance
fuzzy control
module4#motorAiming at the problem of mechanical damage to theequipment caused by the falling or rolling of thematerial (coal) during the heavy load start and stop of
the belt conveyor and the dynamic tension, theexcessive wear and energy wastage of the mechanicaltransmission mechanism under light load or no loadhigh speed running condition and dynamic balance ofmotors, this paper proposes the overall control model ofthe belt conveyor shown in Fig.1. The control system ismainly composed of speed setting module, speed
control module, power balance control module and soon. It adopts double closed-loop structure. The innerloop is composed of the power balance controller. The
strategy is using the master-slave control mode, namely,
taking the current of the 1# motor as the given value ofthe current of 2# ~ 4# motor. When the current of 2# ~4# motor is not consistent with the No. 1 motor, thepower balance fuzzy controller can change the output of
the motor by automatically adjusting the opening of theservo proportional valve of the 2# ~ 4# controllable
driving device CST, so as to realize the four motor
power balance control. The outer ring is composed of aspeed control module, and its function is to realize thebelt speed control. The basic principle is comparing theKW

servo brakelinearclutch
3#CST
2#rollerspeed

servo brakelinearclutch
4#CSTFig.1 Belt speed and motor power balance control principle

Speed control module and power balance control
module both use fuzzy self-tuning PID control
algorithm, and its structure is shown in Fig.2. It is
composed of a fuzzy controller and PID controller. ThePID controller mainly realizes the speed and power
balance control of the double drum four-drive belt
conveyor. The fuzzy controller is mainly used tomonitor the control effect and adjust the parameters of
the PID controller. By monitoring the tape machine
speed and motor power (current) deviation e and thedeviation change rate ec continuously, the control effectcan be analyzed. Improving the control effect of doubledrum four-drive belt conveyor control system isachieved by adjusting the proportion coefficient,integral coefficient and differential coefficient of PID
controller using fuzzy reasoning. Speed control fuzzy
self-tuning PID input is speed deviation e and speed
deviation rate of change ec; three power balance control
fuzzy self-tuning PID input are current deviation e and176

Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 2 (September 2017) 175–178___________________________________________________________________________________________________________

3. Speed setting of tape conveyor

current deviation Rate of change ec of 2# ~ 4# motorand 1# motor. Fuzzy self-tuning PID output are therespective controllable drive CST servo proportional
valve opening.

In order to reduce the loss of mechanical transmission
mechanism and improve the efficiency of the motor, thebelt conveyor should operate at the speed in accordance
fuzzywith the speed of its coal flow. At the same time, incontroller
ΔK
order to prevent damage caused by impact on the tape
ΔKp
ΔKgiven value
from frequent changes of tape speed, control system sete
outputcontrol
PID
objectcontroller+
six speed diagrams. When the belt is overhauled (no- de/dt ecload), the speed is 0.25m/s; when the coal flow rate isless than or equal to 120t, the speed is 0.65m/s; the coalflow rate is more than 120t and less than or equal toFig.2 The fuzzy self-tuning PID principle diagram
240t, the speed is 1.35m/s; the coal flow rate is morethan 240t and less than or equal to 360t , the speed is
PID controller uses incremental operation, position
2.00m/s; the coal flow is greater than 360t less than oroutput, and the formula is shown in (1), (2), (3).
equal to 480t, the speed is 2.55m/s; the coal flow is
In the formulas (1) to (3): U (k) is the output of thegreaterthan 480t less than or equal to 600t , the speed iscontroller (also called the regulator)3.15m/ s.
∆u ( k )= u ( k ) − u ( k − 1)= K p ec( k ) + K i e( k ) +In order to reduce the impact on the grid caused bystarting current of four drive motors, reduce theK d [ec( k ) − ec( k − 1)] （1）mechanical damage to the equipment caused byu( k=) u ( k − 1) + ∆u ( k ) （2）dynamic tension because of starting and stopping of
high-angle tape conveyor, and avoid the materialec( k ) = e( k ) − e( k − 1) （3）decline or rolling when start, the speed curve of belt
First, apply the simulation tools and experimental
starting and stopping should use "S" type speed
methods offline. According to the principle of fuzzy
diagram, as shown in Fig.3.0~t3 is the starting
control, establish on-line adjust table of PID controller’s
acceleration phase of the belt conveyor; t3~t4 is constant
proportional(fuzzy decision table), including coefficient
speed running section; t4~t7 is the deceleration stage;increment △Kp, integral coefficient △Ki differential
t4~t5 is the early deceleration stage; t5~t6 is the constantcoefficient, and store them in the PLC controller
deceleration stage; t6~t7 is the final deceleration stage ofd△K
memory for fuzzy on-line reasoning query controller. In
the belt conveyor: the acceleration of the tape machine
the control process, the fuzzy controller applies fuzzy
can be set at 0.1 m/s2 to 0.3 m/ s2 at the time of starting
reasoning to find out the corresponding adjustment table
and stopping, and the starting time is controlled in(fuzzy decision table) from,and60s~200s, and both can be set according to site
p△Ki△Kd△K
according to the deviation e and deviation change raterequirements.
ec (de/dt) (4), and get the PID three parameters Kp, Ki
1V1 (t ) = k1t 2 （5）and Kd setting value. Finally, adjust the Kp, Ki and Kd to2
the PID controller.
i

K P′ +
 K=P

Ki′ +
 K=i
 K= K ′ + ddd

1 2k1t + amq (t − t1 ) （6）21 2
12V3 (t=k1t + amq (t2 − t1 ) + k2 (t − t2 )（)7）
2
2K P′ + ∆K P
{E , EC }； K=P{E , EC }； K=i Ki′ + ∆Ki ( 4 )K d′ + ∆K d{E , EC }； K=dV2 (t ) =In the formulas (5) to (7):k1 (m/s3) is the change rate of
the acceleration in the stage 0~t1; k2(m/s3) is the change
rate of the acceleration in the stage t2~t3. amq (m/s2) isthe maximum acceleration in acceleration section;

In the formula (4), K'p, K'i and K'd are the initial presetting values of Kp, Ki and Kd obtained through thetraditional PID parameter setting method.

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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 2 (September 2017) 175–178___________________________________________________________________________________________________________5. Conclusion

V=Vm
1 (t )

t4 < t ≤ t5 （8）1V (t ) = Vm − k3 (t − t4 ) 2 t4 < t ≤ t5 （9）2
1S (t ) = Vm (t − t4 ) − k3 (t − t4 )3 （10）6(1) "S" speed profile is applied as speed profile in thebelt conveyor's starting and stopping, thus preventing
the material (coal) from dropping or rolling during thestart and stop of the heavy-duty conveyor, and themechanical damage to equipment caused by thedynamic tension of the tape during start and stop, so as
to improve the safety performance of equipment andoperators.
(2) According to the size of the coal flow, the speed of
the belt conveyor is divided into 6 steps. The fuzzy selftuning PID algorithm is used to control the speed of thebelt conveyor, so the speed control error is less than2.6%.
(3) Use the master-slave control mode and take thecurrent of the 1# motor as a given value. The fuzzy selftuning PID control algorithm makes the current of the2#~4# motor follow the current of the 1# motor, so thecontrol error is less than 2.6%. This realizes highcontrol precision so that the powers of four drive motors
are almost balanced or the difference is controlled
within an allowable range. By doing so, we prevent theoccurrence of motor burnout, improve the safety andreliability of the system, and extend the life of the belt
conveyor.

12 2
65

V=(t ) (2amz S + V ) t < t ≤ t6 （11）1V (t ) = V6 − k z 4 (t − t6 ) 2 t 6 < t ≤ t7 （12）22

In the formulas (8) to (12): amz (m/s ) is the maximum
acceleration in the starting acceleration stage; S(t)is thetravel in the constant deceleration stage(m);kz4（m/s3）
is the change rate of acceleration in stage t6~t7.
4. Experimental analysis
Based on the designed speed and power, the belt
conveyor control system of balance adaptive fuzzy PID
control algorithm has actually operated, with the actual
control curve speed and power of the belt conveyor
shown in Figure 3. In the figure, the belt start-up time is180s, the belt speed is fixed at 3.15m/s. Once the beltruns stably, the running speed will change from 3.20m/s
to 3.10m/s, and the control error will be less than 2.6%.
The operating current fluctuates within the range of
20.5A~21.5A, and the control error is less than 2.6%,
which realizes the reliable, safe and energy-saving
operation of the main shaft belt transport system.

References
1. Wang Zhong-hua, Chen Xun, Yang Guang-hui. Researchof Multi-motor Power Balance Control of Belt System in
Coal Mining, Coal Mine Machinery, Vol.34 No.8(2013),
pp:61-63.
2. Xu Lu-hui, Li Fu-dong, Zhang Chao, Zhang Xiao-yong,Zong Cheng-guo. Research of Power Balance of BeltConveyor Driven by Multi-motor and Its Analysis,Industry and Mine Automation, No.5(2011), pp: 63-65.
3. Chen Yu. Study on Control of Belt Conveyor Based onIntelligent Algorithm Fuzzy Neutral PID Controller, Coal
Mine Machinery, Vol.35 No.42(2014), pp:39-41.

Fig.3 System speed and power curve of actual control

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