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Integrating H∞ control and optimal control strategies, the fuzzy controller and observer are formulated by solving a minimization problem, which is to minimize a given quadratic performance function.
This scheme is able to minimize a given Utility Function over a certain time horizon.
This task has been carried out by taking into account the program parameters and the material model, in order to minimize a given error function.
Given an m-dimensional surface Φ in Rn, we characterize parametric curves in Φ, which interpolate or approximate a sequence of given points pi∈Φ and minimize a given energy functional.
Inspired by the work of Borrvall and Petersson [1], we propose a novel algorithm for optimal shape design problem of two-dimensional Stokes flow in order to minimize a given objective functional.
NMF algorithm starts with an initial estimate for and, and performs an iterative optimization to minimize a given cost function.
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The state variables of the rail/vehicle systems are estimated by using a Kalman filter, and the active control is determined by minimizing a given performance index.
In the outer program of the bilevel optimization program, an input minimizing a given norm and satisfying input constraints is determined.
The optimal decoupling controller minimizing a given quadratic cost function is derived for the generalized plant model with two-degree-of-freedom controller configuration.
For a class of denial-of-service (DoS) attack models, the goal is to find an (optimal) causal feedback controller that minimizes a given objective function subject to safety and power constraints.
Initially, we design a bounded output feedback controller for which the region of constrained closed-loop stability is explicitly characterized and an MPC controller that minimizes a given performance objective subject to constraints.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com