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Adaptive PID Controller
Yiming Zhao
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Contents
- Control system
- PID controller
- Adaptive PID
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Adaptive PID Controller Yiming Zhao 1 Contents Control system - - PowerPoint PPT Presentation
Adaptive PID Controller Yiming Zhao 1 Contents Control system - - PowerPoint PPT Presentation
Adaptive PID Controller Yiming Zhao 1 Contents Control system PID controller Adaptive PID 2 Control System Open-loop system OUT IN PLANT 3 Control System Closed-loop system/feedback control system input reference
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Control System
- Open-loop system
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PLANT IN OUT
SLIDE 4
Control System
- Closed-loop system/feedback control system
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PLANT CONTROLLER SENSOR
- error
input
- utput
reference
SLIDE 5
PID - Introduction
- Proportional-integral-derivative
5 https://en.wikipedia.org/wiki/PID_controller
SLIDE 6
PID – P,PI,PID
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PID – Basic Tuning
Four major characteristics of the closed loop step response
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Rise Time Overshoot Settling time Steady state error
- scillation
Kp Decrease Increase NT Decrease increase KI Decrease Increase Increase Eliminate increase KD NT Decrease Decrease NT de/increase
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PID – Basic Tuning
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Source: wikipedia https://en.wikipedia.org/wiki/PID_controller
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PID - Tuning Methods
- ZN (Ziegler Nicholes) reaction curve method
- ZN step response method
- ZN Frequency response method
- ZN self-oscillation method
- Matlab/simulink
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PID – Ziegler Nicholes reaction curve method
Controller Kp Ki Kd P T/L PI 0.9(T/L) 0.27 T/L^2 PID 1.2(T/L) 0.6 T/L^2 0.6T
10 Source: Verver Training Ltd, Three term controller tuning
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PID – use case in real world
- Drone wings with PID
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PLANT PID Gyroscope
- u
θ ACTUATOR Delay y v e ref θ ADC DAC
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PID - Implementation
12 Source: https://www.youtube.com/watch?v=7qw7vnTGNsA&list=PLl0qyij_5jgF_75V49owrHSDCCAvwAVhw&index=2
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Adaptive PID – Movtivation
- To fit into different circumstance
- To make the automation working
- Personal interest (IAS)
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Adaptive PID – Self tuning
- Gain-scheduling controller structure
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PLANT CONTROLLER SENSOR
- reference
Gain scheduler Scheduling Variable
source: P.A. Tapp A, A Comparion of three self-tuning control algorithms
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Adaptive PID – Self tuning
- Self-tuning controller structure
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PLANT CONTROLLER SENSOR
- reference
Parameter Adjustment d PLANT ID & Parameter Estimation +
source: P.A. Tapp A, A Comparion of three self-tuning control algorithms
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Adaptive PID – Self tuning
- Model-reference adaptive controller structure
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PLANT CONTROLLER SENSOR
- reference
Model Desired Value Parameter Adjustment
source: P.A. Tapp A, A Comparion of three self-tuning control algorithms
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Adaptive PID – auto tuning
- PID auto-tuning scheme using neural networks
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PLANT CONTROLLER SENSOR
- reference
Parameter converter e(t) y(t)
source: Frankcklin Rivas-echeverria. Nerual Network-based Auto-Tuning for PID Controllers
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Adaptive PID – PIDNN
- Suitable for non-linear system
- Computation critical
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PLANT SENSOR reference
source: F. Shahraki, M.a. Fanaei. Adaptive System Control with PID Neural networks
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Conclusion
Conventional PID Control Adaptive PID Control Analytical approach Learning based approach Good for linear systems Suitable for non-linear systems Sensitve to the change of plant system Doesn‘t need to know the detail of the plant system Fast calculation just in time Slow in learning phase
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References
- [1]F. Shahraki, M.A. Fanaer Neural Network-based Auto-Tuning for PID
Controllers
- [2] F. Shahraki, M.A. Adaptive System Control with PID Neural Networks
- [3] Astrom, K. J. and Haggland, T. 1988, Automatic Tunning of PID Controlles
- [4] Karl Johan Åström (2002) Control System Design (Chapter 6)
- [5] H.L. Shu, Y. Pi (2005), Decoupled Temperature Control System Based on PID
Neural Network
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