Name: Aaron Radke
Interactive, Web Based Control Tuning and Simulation
Demonstrate, test and tune control algorithms
on the web with interactive tuning adjustments.
Implementing the Active Disturbance Rejection Controller
on a Rockwell 1756 M02AE Analog Servo Controller
Focuses on designing and implementing a digital Active Disturbance Rejection
Controller (ADRC) algorithm for controlling an X Y positioning table system.
This system is typically used for high speed applications such as glass
cutting, welding and transportation of components in assembly plants. The
mathematical model for the plant was developed based on the available system
resources (hardware and software). Then, the simulink model for both PI and
ADRC were developed. Both were then implemented on Rockwell Automation’s 1756
M02AE Analog Servo Controller connected to the X Y table setup. The
simulation and real time performance of the PID and ADRC based control systems
are then compared. An auto-tuning algorithm was developed for the ADRC
controller ( yet to be implemented). Some of the further research in diverse
areas are summarized as belows:
- Implementation of the
simulated or a new auto tuning algorithm for the ADRC controller would be an
ideal add on for this project to complete the ADRC control design package for
the X Y table setup.
- Design a more sophisticated
data acquisition system to accurately measure control signal, command profile
etc. without or with noise during measurement.
- This project has shown how
Rockwell’s 1756M02AE controller module can be modified with our own control
algorithm. Other advanced control methods apart from ADRC could be
implemented and tested with this controller.
Motion Control Design Optimization Using
A genetic algorithm (GA) based tuning method is
proposed for a class of motion control problems. Several control algorithms,
such as the conventional proportional-integral-derivative control and
its two variations, the parameterized loop-shaping control as well as the
linear active disturbance rejection control, are applied to address a motion
Development of a Nonlinear Control Structure
for Advanced Aero-Propulsion Systems
The challenge is in the application of a model-independent control structure,
known as Active Disturbance Rejection Control (ADRC), to the general jet
engine control problem and in the further enhancement of the technology to
adaptively optimize the control for engine-to-engine variations and for slow
degradations due to aging. This approach uses an extended state observer to
actively estimate and cancel the true dynamics of the system in real time.
Where modern multivariable control schemes are limited, ADRC offers a high
degree of tunability, and will reduce the complexity of gain scheduling
without sacrificing performance over the full envelope operational capability
of the engine. The scope of this research requires close collaboration with
the NASA Glenn Research Center facilities and General Electric Aircraft
Name: Tong Ren
Fragility of Control Design Methods
theory” investigates the change in graphical form of various mathematical
objects under smooth parameter variation. When a small perturbation of the
parameters of a controller occurs, it may lead to a considerable change in the
qualitative properties of the closed loop system. Such a controller is said to
be “fragile.” Optimal controllers are particularly fragile. A fragile
controller is deemed a “structurally unstable” controller.
Name: WanKun Zhou
A Novel Approach for Tension and Velocities Regulation in Continuous
Web Processing Lines
The strip tension as well as the roller velocities in web processing lines
should be controlled accurately for the quality of products. In this research,
a unique Active Disturbance Rejection Control (ADRC) strategy, which can
actively compensate for dynamic changes in the system and unpredictable
external disturbances, is proposed using an Extended State Observer (ESO) as a
compensator for unknown factors. In addition, in order to directly control of
web tension, a backstepping method is applied to compensate for the open-loop
tension regulation. Simulation results show the effective and the remarkable
disturbance rejection capability in coping with large dynamic variations
commonly seen in web tension applications.
A Novel Design Approach And Software
Implementation For Servo Systems
A systematic design approach for a servo system is proposed and implemented in
CAD software. Based on the load characteristics and design objectives, the
selection of the motors is optimized. A motor database is established. Then an
automatic design of the servo controller is carried out based on the
performance criteria defined by the user. A software simulation module within
the package allows user to verify the design before the final implementation.
A Graphical User Interface (GUI) is developed. It takes user from defination
of load, motion profile, optimal selection of the motor and gearbox, to the
digital or analog servo controller design and simulation. Finally the
controller parameters obtained from simulation are converted to those for a
particular industrial servo drive.
Rockwell industry software to control
2-axis XY table
ControlLogix: control XY table for both
torque mode and velocity mode
FlexLogix: C coded control algorithm to
control XY table, we tested torque mode only.
Nice switch box simplifies the wiring.
Next step: Dspace and new control
Nonlinear Control Strategies for Motion
Analysis and design of
extended state observer-based nonlinear control algorithm for the active
magnetic bearing system and real-time embedded control design for Model 220
Controlling Low-Frequency Mechanical
Resonance In Industrial Servo Systems
Research focused on applying nonlinear control algorithms for disturbance
rejection and control of a motor. The apparatus is a Kollmorgen SERVOSTAR 600
digital servo drive, which used to drive a motor exhibiting resonance.
Nonlinear algorithms are implemented in Macro assembler flex firmware.
Comparative Study of Differentiators and Integrators
for Advanced Controller
Among the Pure Integrator, Nonlinear Integrator, Clegg Integrator and Modified
Nonlinear Integrator, the Nonlinear Integrator demonstrates much better
performance in simulation. The above conclusions are drawn from numerical
simulation of a practical control system where disturbance and noise are
incorporated to make it realistic.