Designing Adaptive Intensive Interventions Using Methods from Engineering
Published in IEEE Transactions on Control Systems Technology, 2017
Recommended citation: Bekiroglu, K., Lagoa, C., Murphy, S. A., & Lanza, S. T. (2016). Control engineering methods for the design of robust behavioral treatments. IEEE Transactions on Control Systems Technology, 25(3), 979-990. https://ieeexplore.ieee.org/ielaam/87/7876877/7501575-aam.pdf
A robust control approach is used to address the problem of adaptive behavioral treatment design. Human behavior (e.g., smoking, exercise) and reactions to treatment are complex and depend on many unmeasurable external stimuli, some of which are unknown. Thus, it is crucial to model human behavior over many subject responses. We propose a simple (low order) uncertain affine model subject to uncertainties whose response covers the most probable behavioral responses. The proposed model contains two different types of uncertainties: uncertainty of the dynamics and external perturbations that patients face in their daily life. Once the uncertain model is def ined, we demonstrate how least absolute shrinkage and selection operator (lasso) can be used as an identification tool. The lasso algorithm provides a way to directly estimate a model subject to sparse perturbations. With this estimated model, a robust control algorithm is developed, where one relies on the special structure of the uncertainty to develop efficient optimization algorithms.