Untitled e ISSN 2582 5208 International Research Journal of Modernization in Engineering Technology and Science Volume 03/Issue 05/May 2021 Impact Factor 5 354 www irjmets com www irjmets com @Interna[.]
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STUDY ON HYBRID CONTROLLER ERROR ALGORITHM TO MAXIMIZE
SPEED CONTROL PARAMETERS OF DC MOTORS
ABSTRACT
In the closed control system to drive the electricity between the generator and the motor, there are three control loops using a PID controller However, the innermost inrush current control loop requires a fast and precise actuation In this paper, the research to improve the control quality of the Ikt control circuit is decisive to the quality as well as the response of the other two loop circuits By using an Ikt tuning circuit using a hybrid controller between FC and PID tuning The research results show that the Hybrid hybrid control system is more efficient and accurate than the traditional PID control method
Keyword: Control Panel; Engine; PID, Hybrid Controller
I INTRODUCTION
PID controller: The PID controller has been widely used in industry many decades ago because of its simplicity
In the control field, the PID is seen as a versatile solution for analog and digital control application [1-4]
The principle diagram, control structure of the classic PID is described in Figure 1
Figure 1: Schematic diagram of the classic PID set
The mathematical model of PID is described:
( ) ( ) ∫ ( ) ( )
Or the form of transfer function:
( )( ) Implement the PID controller based on the difference between the set value and the actual value so that suitable values for three parameters are found Kp, Ki, KD
The general rule for defining these parameters is usually according to Zeigler - Nichols, and these parameters are calculated to work in a fixed mode With the electric excavator drive systems in the mining industry, the study subject worked in an environment with a very specific specificity [3-6] The temperature, humidity constantly changing, the noise is high, the parameters are uncertain and strong nonlinearity is strong Therefore, the necessary PID parameters need to be regularly calibrated for adaptation The research and application of the self-correcting fuzzy algorithm will solve this shortcoming, make the system more stable and also contribute to improving and improving the quality of the electric drive systems in today's excavators [6-7] Fuzzy – Controller (FC): One advantage of using fuzzy controllers for systems is that they don't need the exact mathematical model of the object Here, it only needs to use a set of constituent law propositions in the form of composite law matrix tables The schematic diagram of an FC set is shown in Figure 2 and Figure 3
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Figure 2: Schematic diagram of an FC controller
Figure 3: Schematic of principles, structure of FC application
Figures 2 and 3 show the principle diagram, structure diagram of the functional blocks of a fuzzy controller In which the input variables through a fuzzy interface and converted into linguistic variables Then the database and fuzzy law will make a decision to infer the fuzzy result Finally, the fuzzy solution with the function of converting the fuzzy output to a value will be sent to the control of the object
The hybrid controller (Hybrid) combines FC and PID: The PID controller is often sensitive to the change in process output variables and system parameters The PID also has good control and minimizes deviation between set value and actual value
For fuzzy controller (FC), there is no need for accurate information and need not define explicit mathematical model for the object Therefore, the proposed research and application of a hybrid control system is described
in Figure 4 In order to better exploit the advantages of both PID and FC controllers, the system can bring about outstanding advantages
Figure 4 Diagram of FC and PID hybrid control
In Figure 4, a switch K is used between the PID controller and FC In which, the position of the switch K depends
on the deviation between the real and set values If the deviation calculated in the absolute value is greater than the threshold e0, the Hybrid system adopts FC fuzzy controller (to ensure the need for rapid rise time and small over-adjustment) When the deviation is less than the threshold e0 or close to the setpoint neighbor, the Hybrid system will automatically switch to PID Then it helps to make the static deviation better for the real value
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target to stick with the set value The proposed algorithm promises to better improve the quality of the existing electric drive control system
Figure 5: Diagram of the principle of MF-DC electric power generation using hybrid fuzzy algorithm
+ Block A: The control signal generator is received from the driver α
+ Block B: Engine speed measuring ring: use PID
+ Block C: Loop Iu: use FC + PID
+ Block D: Ikt current measuring ring: using FC + PID tuning
Figure 6: Diagram of the principle of proposing hybrid fuzzy control systems for MF - DC power transformers
II METHODOLOGY
Design of I u series control loop using FC and PID controller:
Principle diagram of controlling the circuit block of a current Iu motor using a hybrid controller combining FC + PID In this content we focus on algorithm proposal for fuzzy controller The essence of the system is to keep
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the old PID, only add the FC controller that is connected in parallel with the PID in combination with the switch
K for the purpose of improving and further improving the quality of the control technique control current Design of FC controller: The FC set has 2 input variables e and ∆e, which are defined by linguistic variables In which error e uses 7 linguistic variables described in English terms:
+ ETu = {Negativ Big, Negativ Medium, Negativ Small, Zero, Positiv Small, Positiv Medium, Positiv Big}
+ ETu = {NB, NM, NS, Z, PS, PM, PB}
+ Based on the transient characteristics surveyed and modeled, the ETu value is determined in the range (-1000
÷ 1000)
Design a I kt series control loop using an FC + PID controller
Compare the hybrid fuzzy control and the PID control
+ The join function of the form Δ is described in Figure 3
Figure 7: Hybrid control diagram
III RESULT AND DISCUSSION
The simulation result that shown in Figure 8 to Figure 16, the comparison results between the two methods showed that the FC algorithm has higher performance than the traditional algorithm The data summary table
in Table 1 shows the parameters when comparing PID controller and Hybrid controller with different load cases as follows The acceleration time of the Hybrid is faster than the PID shown in Figure 9, Figure 10 and Figure 11 The setting time of the Hybrid is faster than the PID that shown in Figures 9 to Figures 16 The Hybrid overshoot is lower than the PID Figure 12, figure 13, figure 14 The highest angle speed value for Hybrid controller is faster than PID controller
Figure 8: Engine speed under load
Figure 9: Engine speed at rated load
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Figure 10: Engine speed when overloaded
Figure 11: Armature current under load
Figure 12: Armature current at rated load
Figure 13: Armature current under overload
Figure 14: Generator electrodynamic level under load
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Figure 15: Generator dynamic level under rated load
Figure 16: Generator's electromotive force when overloaded Table 1: Comparison of times and values when controlling the Hybrid and Pid
time (Sec)
Establishment time (Sec)
Overshoot
% armature current
Highest angle speed value (RPM)
HYBRID
Rated current PID
HYBRID
HYBRID
The effect of the model's performance is based on the different load changes and response speed The effect of different loads changing the output parameters on the system represented by acceleration time, setting time, overshoot and maximum speed value are shown in Table 1 that in case of load, when comparing PID controller with Hybrid controller, PID controller has high overshoot, so it takes longer time to stabilize to motor speed value desire Also can be observed in Figure 16, Fig 17, Fig 18, when the load is different, the speed of the motor is also slightly affected The Hybrid controller quickly adapts more quickly to load changes compared to
a PID unit
In Figure 9,10, at the initial time of start up there is a speed fluctuation during the first 1 second of a specific PID controller According to Table 1, when there is an overload current, the average value increases 2,925 times compared to the norm, the overshoot of the PID is higher than that of the Hybrid survey Figure 14, cut protection speed Fast Hybrid is faster than PID
IV CONCLUSIONS
Analysis of the PID control process of controller and hybrid controller in the controller structure Comparisons drawn from the PID and Hybrid controls require high stability, minimizing the interference caused on the system that will cause errors and improve quick response
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From the above results, it can be seen that in controlling the speed of a DC motor, the Hybrid controller operates more efficiently than the PID controller due to no unwanted overshoot, and the processing time faster management in different load cases
On the basis of this research, keeping up with the times of artificial intelligence if Hybrid controllers can be easily deployed in our mining industries to improve accuracy and improve performance improvements in operations involving DC motors in electric excavator devices The most desirable performance requires the controller to have the smallest value it can handle
V REFERENCES
[1] Bui Quoc Khanh - Nguyen Van Lien - Nguyen Thi Hien Electric Drive, Science and Technology
Publishing House, Hanoi 2004
[2] Thai Duy Thuc, Khong Cao Phong (2006), Power Electronics in the oil and gas industry, Transport
Publishing House, Hanoi
[3] ABB documents, 2009 in “Revamp of an Electric shovel - A cost saving alternative between frequent
repairs and the purchase of new machine”
[4] Lich N T, 2010in “Design a control module for shovel excavator EKG 10”, Master thesis, Ha Noi, 2010 [5] Li-Xin Wang, A Course in Fuzzy Systems and Control, Prentice Hall 1997
[6] Pearson Education Inc, Pearson Prentice Hall, 2004
[7] Pierre Guillemin (1996).” Fuzzy Logic Applied to Motor Control” IEEE Transactions On Industry
Applications