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The problem of finding the optimal open-loop control for discrete-time stochastic dynamical systems is considered. It is assumed that the initial conditions and external influences are random.
Andrei Panteleev, Vladislav Rakitianskii
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Passive Stabilization of Static Output Feedback of Disturbed Nonlinear Stochastic System
This paper investigates the Static Output (SO) control issue of the disturbed nonlinear stochastic system, which achieves passivity. Through the application of fuzzy sets and the stochastic differential equation, a Takagi–Sugeno (T-S) fuzzy model with ...
Ping-Tzan Huang +3 more
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In our paper, we mainly concentrate on the existence of Hilfer fractional neutral stochastic Volterra integro-differential inclusions with almost sectorial operators.
Sivajiganesan Sivasankar +1 more
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Pseudo and resistant hypertension: A chaotic perspective
Systemic blood pressure (BP) may oscillate for homeostatic needs (equilibrium by constancy) or just as shifts in other intrinsic and extrinsic variables known as allostatic changes. This transitory pressure often rises alerts physicians to out‐of‐control
Heitor Moreno
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Hybrid-Driven-Based H∞ Control for Offshore Steel Jacket Platforms in Network Environments
This paper investigates the hybrid-driven-based networked control for an offshore steel jacket platform subject to external wave forces. A hybrid driven strategy is introduced to deal with the problem of networked control for offshore platforms.
En-Zhi Cao +3 more
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The existence of Hilfer fractional stochastic Volterra–Fredholm integro-differential inclusions via almost sectorial operators is the topic of our paper.
Sivajiganesan Sivasankar +2 more
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Mean-Square Stability of Uncertain Delayed Stochastic Systems Driven by G-Brownian Motion
This paper investigates the mean-square stability of uncertain time-delay stochastic systems driven by G-Brownian motion, which are commonly referred to as G-SDDEs.
Zhengqi Ma +3 more
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This paper discusses the multi-player non-cooperative game of nonlinear stochastic time-varying systems described by Itô-type differential equations in a finite time interval.
Xiangyun Lin +4 more
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A Numerical Algorithm for Self-Learning Model Predictive Control in Servo Systems
Model predictive control (MPC) is one of the most effective methods of dealing with constrained control problems. Nevertheless, the uncertainty of the control system poses many problems in its performance optimization.
Hengzhan Yang +4 more
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Stochastic Port-Hamiltonian Systems
AbstractIn the present work we formally extend the theory of port-Hamiltonian systems to include random perturbations. In particular, suitably choosing the space of flow and effort variables we will show how several elements coming from possibly different physical domains can be interconnected in order to describe a dynamic system perturbed by general ...
Cordoni F. +3 more
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