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MATLAB AND CARDIOVASCULAR ENGINEERING
SOLVING PROBLEMS, SAVING TIME
Dr Michael Stevens
INNOVATIVE CARDIOVASCULAR ENGINEERING AND TECHNOLOGY LABORATORY
Using MATLAB in the ICET LAB
• Numerical Model (Computer Simulation)
• Mock Circulation Loop (Mechanical Simulation)
• Design and Tuning of Feedback Control Loops
1. Terracciano, C.M., L.W. Miller, and M.H. Yacoub, Contemporary use of ventricular assist devices. Annu. Rev. Med., 2010. 61: p. 255-70.2. Heidenreich, P.A., et al., Forecasting the Future of Cardiovascular Disease in the United States: A Policy Statement From the American Heart Association. Circulation, 2011. 123(8): p. 933-944.3. Thunberg, C.A., et al., Ventricular assist devices today and tomorrow. Journal of Cardiothoracic and Vascular Anesthesia, 2010. In Press.
• Prevalence: About 3% of population1,2
• Hospital admissions: Over 1M in US alone per year3
• Costs: $35B USD per year in US2
• Projections: $95B USD per year in US by 2030.2
• Less than 4000 heart transplants performed worldwide per year.
HEART FAILURE
Combating cardiovascular disease by serving as a bridge between the engineering department and clinic.
ICET LAB - OUR AIM
Using MATLAB in the ICET LAB
• Numerical Model (Computer Simulation)
• Mock Circulation Loop (Mechanical Simulation)
• Design and Tuning of Feedback Control Loops
Using MATLAB in the ICET LAB
• Numerical Model (Computer Simulation)
• Mock Circulation Loop (Mechanical Simulation)
• Design and Tuning of Feedback Control Loops
Instrumentation and Actuation
P
V
Q
PV
S&R
P
PP P
P
P
P
P
P
V
Q
Q
Q
PV
S&RS&R
16+ Analog inputs5+ Digital outputs7+ Analog OutputsControl @ 2000HzSample @ 100 Hz
S&R
S&R
Using MATLAB in the ICET LAB
• Numerical Model (Computer Simulation)
• Mock Circulation Loop (Mechanical Simulation)
• Design and Tuning of Feedback Control Loops
Physiological Control:‘Smart’ Cruise Control for Rotary VADs
Automatically adjust speed to respond to physiological changes• Prevent collapse of ventricle
• Increase flow during exercise
Control System Tuning
• Very complex plant model
• High-order
• Non-linear
• Time and patient variance
• Tuning was performed using gradient descent optimisation.
• Initially developed own optimisation script
• Now use MATLAB Optimisation Toolbox
Optimisation Objective Function
Define Ideal Control + Plant
Behaviour
𝜔𝑛2
𝑠2 + 2ζ𝜔𝑛𝑠 + 𝜔𝑛2
+
- 0
𝑇Value to minimise
𝑥2
C(s) G(s)+-
Controller Plant
Target
Rise TimeSettling TimeOvershoot
Control Tuning using Optimisation: Some Considerations.
• Local vs. Global minima.
• Initial Guess of Gains.
• Requires careful selection of objective function and optimisation parameters.
• MATLAB documentation for Optimisation Toolbox very helpful.
Using MATLAB in the ICET LAB
• Numerical Model (Computer Simulation)
• Mock Circulation Loop (Mechanical Simulation)
• Design and Tuning of Feedback Control Loops
Solving Problems, saving time
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