Decoupled Reference Governors for Multi-Input Multi-Output Systems

In this work, a computationally efficient solution for constraint management of square multi-input multi-output (MIMO) systems is presented. The solution, referred to as the Decoupled Reference Governor (DRG), maintains the highly-attractive computational features of scalar reference governors (SRG) compared to Vector Reference Governor (VRG) and Command Governor (CG). This work focuses on square MIMO systems that already achieve the desired tracking performance. The goal of DRG is to enforce output constraints and simultaneously ensure that the degradation to tracking performance is minimal. DRG is based on decoupling the input-output dynamics of the system so that every channel of the system can be viewed as an independent input-output relationship, followed by the deployment of a bank of scalar reference governors for each decoupled channel. We present a detailed set-theoretic analysis of DRG, which highlights its main characteristics. A quantitative comparison between DRG, SRG, and the VRG is also presented in order to illustrate the computational advantages of DRG. Finally, a distillation process is introduced as an example to illustrate the applicability of DRG

Reliability -aware optimal checkpoint /restart model in high performance computing

Computational power demand for large challenging problems has increasingly driven the physical size of High Performance Computing (HPC) systems. As the system gets larger, it requires more and more components (processor, memory, disk, switch, power supply and so on). Thus, challenges arise in handling reliability of such large-scale systems. In order to minimize the performance loss due to unexpected failures, fault tolerant mechanisms are vital to sustain computational power in such environment. Checkpoint/restart is a common fault tolerant technique which has been widely applied in the single computer system. However, checkpointing in a large-scale HPC environment is much more challenging due to complexity, coordination, and timing issues. In this dissertation, we present a reliability-aware method for an optimal checkpoint/restart strategy. Our scheme aims to address the fault tolerance challenge, especially in a large-scale HPC system, by providing optimal checkpoint placement techniques derived from the actual system reliability. Unlike existing checkpoint models, which can only handle Poisson failure and a constant checkpoint interval, our model can perform a varying checkpoint interval and deal with different failure distributions. In addition, the approach considers optimality for both checkpoint overhead and rollback time. Our validation results suggest a significant improvement over existing techniques

Accurate Multi-physics Numerical Analysis of Particle Preconcentration Based on Ion Concentration Polarization

This paper studies mechanism of preconcentration of charged particles in a straight micro-channel embedded with permselective membranes, by numerically solving coupled transport equations of ions, charged particles and solvent fluid without any simplifying assumptions. It is demonstrated that trapping and preconcentration of charged particles are determined by the interplay between drag force from the electroosmotic fluid flow and the electrophoretic force applied trough the electric field. Several insightful characteristics are revealed, including the diverse dynamics of co-ions and counter ions, replacement of co-ions by focused particles, lowered ion concentrations in particle enriched zone, and enhanced electroosmotic pumping effect etc. Conditions for particles that may be concentrated are identified in terms of charges, sizes and electrophoretic mobilities of particles and co-ions. Dependences of enrichment factor on cross-membrane voltage, initial particle concentration and buffer ion concentrations are analyzed and the underlying reasons are elaborated. Finally, post priori a condition for validity of decoupled simulation model is given based on charges carried by focused charge particles and that by buffer co-ions. These results provide important guidance in the design and optimization of nanofluidic preconcentration and other related devices.Comment: 18 pages, 11 firgure

Limit theorems for functionals of long memory linear processes with infinite variance

Let $X=\{X_n: n\in\mathbb{N}\}$ be a long memory linear process in which the coefficients are regularly varying and innovations are independent and identically distributed and belong to the domain of attraction of an $\alpha$-stable law with $\alpha\in (0, 2)$. Then, for any integrable and square integrable function $K$ on $\mathbb{R}$, under certain mild conditions, we establish the asymptotic distributions of the partial sum $$\sum\limits_{n=1}^{N}\big[K(X_n)-\mathbb{E} K(X_n)\big]$$ as $N$ tends to infinity

Validation of recommended definition in identifying elevated blood pressure in adolescents

Recently, the American Academy of Pediatrics (AAP) recommended 120/80 mm Hg as thresholds for identifying elevated blood pressure (BP) in adolescents aged 13‐17 years. The authors aimed to compare the performance of the new definition in identifying elevated BP with traditional percentile‐based definition. Data were obtained from the National Health and Nutrition Examination Survey 1999‐2014, which included 7485 adolescents aged 13‐17 years. Elevated BP was defined using the recommended (≥120/80 mm Hg) and traditional definition (≥90th percentile for sex, age, and height or 120/80 mm Hg) presented in AAP guideline. The prevalence of elevated BP was 15.7% and 17.2% using the recommended and traditional definition, respectively (P < .001). The recommended definition had high sensitivity (90.9%), perfect specificity (100.0%), perfect positive predictive value (100.0%), and very high negative predictive value (98.1%) compared with the traditional definition. The Kappa correlation coefficient between two definitions was 0.94 (P < .001). Similar results can be observed in subgroups across sex, age, and sex‐ and age‐specific height percentile except for both sexes with young age and low height percentile. Generally, our results supported the use of the recommended definition for identifying elevated BP in adolescents.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151868/1/jch13640.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151868/2/jch13640_am.pd

Reference Governors for MIMO Systems and Preview Control: Theory, Algorithms, and Practical Applications

The Reference Governor (RG) is a methodology based on predictive control for constraint management of pre-stablized closed-loop systems. This problem is motivated by the fact that control systems are usually subject to physical restrictions, hardware protection, and safety and efficiency considerations. The goal of RG is to optimize the tracking performance while ensuring that the constraints are satisfied. Due to structural limitations of RG, however, these requirements are difficult to meet for Multi-Input Multi-Output (MIMO) systems or systems with preview information. Hence, in this dissertation, three extensions of RG for constraint management of these classes of systems are developed. The first approach aims to solve constraint management problem for linear MIMO systems based on decoupling the input-output dynamics, followed by the deployment of a bank of RGs for each decoupled channel, namely Decoupled Reference Governor (DRG). This idea was originally developed in my previous work based on transfer function decoupling, namely DRG-tf. This dissertation improves the design of DRG-tf, analyzes the transient performance of DRG-tf, and extends the DRG formula to state space representations. The second scheme, which is called Preview Reference Governor, extends the applicability of RG to systems incorporated with the preview information of the reference and disturbance signals. The third subject focuses on enforcing constraints on nonlinear MIMO systems. To achieve this goal, three different methods are established. In the first approach, which is referred to as the Nonlinear Decoupled Reference Governor (NL-DRG), instead of employing the Maximal Admissible set and using the decoupling methods as the DRG does, numerical simulations are used to compute the constraint-admissible setpoints. Given the extensive numerical simulations required to implement NL-DRG, the second approach, namely Modified RG (M-RG), is proposed to reduce the computational burden of NL-DRG. This solution consists of the sequential application of different RGs based on linear prediction models, each robustified to account for the worst-case linearization error as well as coupling behavior. Due to this robustification, however, M-RG may lead to a conservative response. To lower the computation time of NL-DRG while improving the performance of M-RG, the third approach, which is referred to as Neural Network DRG (NN-DRG), is proposed. The main idea behinds NN-DRG is to approximate the input-output mapping of NL-DRG with a well-trained NN model. Afterwards, a Quadratic Program is solved to augment the results of NN such that the constraints are satisfied at the next timestep. Additionally, motivated by the broad utilization of quadcopter drones and the necessity to impose constraints on the angles and angle rates of drones, the simulation and experimental results of the proposed nonlinear RG-based methods on a real quadcopter are demonstrated

Intrapancreatic Ganglia and Neural Regulation of Pancreatic Endocrine Secretion

Extrapancreatic nerves project to pancreatic islets directly or converge onto intrapancreatic ganglia. Intrapancreatic ganglia constitute a complex information-processing center that contains various neurotransmitters and forms an endogenous neural network. Both intrapancreatic ganglia and extrapancreatic nerves have an important influence on pancreatic endocrine function. This review introduces the histomorphology, innervation, neurochemistry, and electrophysiological properties of intrapancreatic ganglia/neurons, and summarizes the modulatory effects of intrapancreatic ganglia and extrapancreatic nerves on endocrine function