Outline
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Introduction
Literature Review
Objective
Methodology
Basic block diagram
Comparison of PID,ANN,MPC
Conclusion
References
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Introduction.
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In modern engineering BLDC has wide range of application.(Motion control,
positioning, in E-Vehical etc.)
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That is why controlling of motor necessary.
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Controllers such as PID, MPC(Modern predictive control) or ANN based
controllers can be useful.
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Every controlled has its own specifications, comparing the performance of each
can give clear idea about its performance.
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Objective.
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An approach for building a mathematical model for the system.
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Setting up of control system for given BLDCM and optimizing its
performance.
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Going with one control strategy at a time and analysing its
performance.
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Generating the results for speed and torque control.
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Analyse and Comparing the results of all techniques to conclude
the best suitable control scheme.
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Methodology
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Mathematical modelling of BLDCM
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PID implementation for speed and torque control of BLDCM
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Collection of data for implementing ANN controller.
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Training of neural network from given data, and further
controlling BLDCM
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Basics of MPC (Model Predictive Control)
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Implementing MPC on BLDCM
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Comparing the results of all controller for given control.
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Basic Block diagram
Data
Collection
for ANN
Tuning ANN
ANN Control
PID Tuning
and Control
Speed And
Torque Control
BLDCM
MPC Controller
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PID
• Proportional, integral , derivative
control.
• One of the basic controllers.
• 𝑢 𝑡 = 𝐾𝑝 𝑒 𝑡 + 𝐾𝑖 𝑒 𝑡 𝑑𝑡 + 𝐾𝑑 𝑑𝑒
𝑑𝑡
• P- output proportional to error e(t). It
provides stable operation but error
present.
• I- Adds pole to the system and reduces
error.
• D- Output depends on rate of change
of error. Improves the stability also.
Increasing Kd improves speed of
response also.
ANN
MPC
• Stands for Artificial Neural network. • Stands for Model Predictive Control.
Interconnected group of nodes.
• MPC models predict the change in
• Inspired by biological neural
the dependent variables of the
network, i.e. Brain.
modelled system that will be caused
by changes in the independent
variables.
• Input layer, hidden layer, output
layer.
• Data based control.
• Training and tuning of controller.
• NN learn(or trained) by processing
example.
• Based on trained data, NN gives
output for given inputs.
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Conclusion
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So given study will analyse and compare the results of different
controllers.
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Initial part is the study of different controllers. Their working and
Specifications.
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Then actual work will be the speed and torque control of
BLDCM.
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With the help of mathematical model and control blocks in
MATLAB Simulink, controller action can will be studied.
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