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In this paper, we discuss the stability of continuous-time stochastic systems with probabilistic mode switchings and state jumps. Occurrences of mode transitions and state jumps are modeled with independent Poisson processes. We use multiple Lyapunov functions to derive sufficient conditions for stability in probability and moment exponential stability both for linear and nonlinear stochastic switching...
A neuro adaptive control framework for stochastic nonnegative and compartmental dynamical systems is developed. In the face of stochastic variations of system coefficients, we present analysis and adaptive control methodology that guarantees global ultimate boundedness of the second moment of the nonlinear stochastic nonnegative systems.
A direct adaptive control framework for nonlinear uncertain systems with input quantizers is developed. The proposed framework is Lyapunov-based and guarantees ultimate boundedness (practical stability) of the closed-loop system. Specifically, the input quantizers are logarithmic and characterized by sector-bound conditions with the conic sector adjusted at each time instant by the adaptive controller...
In this paper, we develop a direct adaptive control framework for uncertain linear nonnegative dynamical systems with unknown time delay. The specific focus of the paper is on compartmental pharmacokinetic models and their applications to drug delivery systems. In particular, we develop a Lyapunov-Krasovskii-based direct adaptive control framework for guaranteeing set-point regulation of the closed-loop...
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