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SUMMARY Treatment of a pathogenic disease process is interpreted as the optimal control of a dynamic system. Evolution of the disease is characterized by a non-linear, fourth-order ordinary differential equation that describes concentrations of pathogens, plasma cells, and antibodies, as well as a numerical indication of patient health. Without control, the(More)
MOTIVATION Therapeutic enhancement of innate immune response to microbial attack is addressed as the optimal control of a dynamic system. Interactions between an invading pathogen and the innate immune system are characterized by four non-linear, ordinary differential equations that describe rates of change of pathogen, plasma cell, and antibody(More)
—This paper considers probabilistic robust control of nonlinear uncertain systems. A combination of stochastic robust-ness and dynamic inversion is proposed for general systems that have a feedback-linearizable nominal system. In this paper, the stochastic robust nonlinear control approach is applied to a highly nonlinear complex aircraft model, the(More)
We examine the dynamics of infection by the human immunodeficiency virus (HIV), as well as therapies that minimize viral load, restore adaptive immunity, and use minimal dosage of anti-HIV drugs. Virtual therapies for wild-type infections are demonstrated; however, the HIV infection is never cured, requiring continued treatment to keep the condition in(More)
Several studies have verified the existence of multiple chromosomal abnormalities in colon cancer. However, the relationships between DNA copy number and gene expression have not been adequately explored nor globally monitored during the progression of the disease. In this work, three types of array-generated data (expression, single nucleotide(More)
An algebraic approach for representing multidimensional nonlinear functions by feedforward neural networks is presented. In this paper, the approach is implemented for the approximation of smooth batch data containing the function's input, output, and possibly, gradient information. The training set is associated to the network adjustable parameters by(More)
Abstruct-Real-time, rule-based guidance systems for autonomous vehicles on limited-access highways are investigated. The goal of these systems is to plan trajectories that are safe, while satisfying the driver's requests based on stochastic information about the vehicle state and the surrounding traffic. A rule-based system is used for high-level planning.(More)