Chronic obstructive pulmonary disease (COPD) is a progressive
lung
disease characterized by airflow limitation. This study develops a
systems engineering framework for representing important mechanistic
details of COPD in a model of the cardiorespiratory system. In this
model, we present the cardiorespiratory system as an integrated biological
control system responsible for regulating breathing. Four engineering
control system components are considered: sensor, controller, actuator,
and the process itself. Knowledge of human anatomy and physiology
is used to develop appropriate mechanistic mathematical models for
each component. Following a systematic analysis of the computational
model, we identify three physiological parameters associated with
reproducing clinical manifestations of COPD: changes in the forced
expiratory volume, lung volumes, and pulmonary hypertension. We quantify
the changes in these parameters (airway resistance, lung elastance,
and pulmonary resistance) as the ones that result in a systemic response
that is diagnostic of COPD. A multivariate analysis of the simulation
results reveals that the changes in airway resistance have a broad
impact on the human cardiorespiratory system and that the pulmonary
circuit is stressed beyond normal under hypoxic environments in most
COPD patients.
The issues regarding the design and implementation of on-line optimal control strategies of crystal properties in noniso- thermal antisolvent crystallization processes to control particles’ mean size and standard deviation are dealt. The one- dimensional Fokker–Planck equation is used to represent the dynamic characteristics of the crystal growth and generate iso-mean and iso-standard deviation curves. Using controllability tools it is demonstrated that the system is ill condi- tioned in the whole operational range, posing limitations on the achievable control performance. To circumvent the problem, a control strategy is formulated by pairing crystals’ mean size with antisolvent feed rate and manipulating temperature to control the standard deviation. A novel digital image-texturing analysis approach is discussed and imple- mented to track crystals’ size distribution along the experiment and providing the on-line information for further feed- back control action. Subsequently, alternative control strategies are implemented and tested to achieve a desired crystal size distribution
This paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous on-line monitoring of polymerization system (ACOMP), with a modern simulation, estimation and optimization software environment towards an integrated scheme for the optimal operation of polymeric processes. An initial validation of the framework was performed for modelling and optimization using literature data, illustrating the flexibility of the method to apply under different systems and conditions. Subsequently, off-line capabilities of the system were fully tested experimentally for model validations, parameter estimation and process optimization using ACOMP data. Experimental results are provided for free radical solution polymerization of methyl methacrylate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.