A5019353698- Stability and Control of Uncertain Systems
- Adaptive Control of Nonlinear Systems
- Advanced Control Systems Optimization
- Control Systems and Identification
- Stability and Controllability of Differential Equations
- Fault Detection and Control Systems
- Numerical methods for differential equations
- Stochastic processes and financial applications
- Optimization and Variational Analysis
- Advanced Banach Space Theory
- Control and Stability of Dynamical Systems
- Control and Dynamics of Mobile Robots
- Advanced Topology and Set Theory
- Matrix Theory and Algorithms
- Gas Dynamics and Kinetic Theory
- Advanced Optimization Algorithms Research
- advanced mathematical theories
- Advanced Topics in Algebra
- Constraint Satisfaction and Optimization
- Abdominal Surgery and Complications
- Differential Equations and Numerical Methods
- Climate Change Policy and Economics
- Insurance, Mortality, Demography, Risk Management
- Petri Nets in System Modeling
- Fuzzy and Soft Set Theory
Guangzhou University of Chinese Medicine
2024
First Affiliated Hospital of Guangzhou University of Chinese Medicine
2024
Virginia Mason Medical Center
2018-2023
University of Cincinnati
2001-2009
Chinese Academy of Sciences
2005
Shanghai Jiao Tong University
2001-2003
University of Illinois Urbana-Champaign
1992-2002
SUNY Polytechnic Institute
2000-2002
Urbana University
2002
University of California, Santa Barbara
1996-2000
This paperdevelops a methodology for recursive construction of optimal and near-optimal controllers strict-feedback stochastic nonlinear systems under risk-sensitive cost function criterion. The design procedure follows the integrator backstepping methodology, obtained guarantee any desired achievable level long-term average given risk-sensitivity parameter $\theta$. Furthermore, they lead to closed-loop system trajectories that are bounded in probability, some cases asymptotically stable...
The authors develop a systematic procedure for obtaining robust adaptive controllers that achieve asymptotic tracking and disturbance attenuation class of nonlinear systems which are described in the parametric strict-feedback form subject to additional exogenous inputs. Their approach control is performance-based, where objective controller design not only find an controller, but also construct appropriate cost functional, compatible with desired specifications, respect "worst case...
In this note, we study the problem of output-feedback control design for a class strict feedback stochastic nonlinear systems. Under an infinite-horizon risk-sensitive cost criterion, controller designed can guarantee arbitrary small long-term average risk-sensitivity parameter and achieve boundedness in probability closed-loop system, using integrator backstepping methodology. Furthermore, preserves equilibrium at origin system.
For a class of nonlinear systems, robust backstepping design achieves both local optimality and global inverse optimality. The is in the sense that it prescribed level disturbance attenuation with stability margins. An analytic example illustrates performance locally optimal control design.
For pt.I, see ibid., vol. 29, no. 2, p 401-423 (1993). In this paper we study the H/sup /spl infin//-optimal control of singularly perturbed linear systems under general imperfect measurements, for both finite- and infinite-horizon formulations. Using a differential game theoretic approach, first show that as singular perturbation parameter (say, epsiv/>0) approaches zero, optimal disturbance attenuation level full-order system quadratic performance index converges to value is bounded above...
In nonlinear H/sup /spl infin//-optimal control design for strict-feedback systems, our objective is to construct globally stabilizing laws match the optimal law up any desired order, and be inverse with respect some computable cost functional. Our recursive construction of a functional corresponding solution Hamilton-Jacobi-Isaacs equation employs new concept Cholesky factorization. When value function system has factorization, we show that backstepping procedure can tuned yield law.
We study the optimal control of a general class stochastic singularly perturbed linear systems with perfect and noisy state measurements under positively negatively exponentiated quadratic cost. The (expected) cost function to be minimized is actually taken as long-term time average logarithm expected value an loss. identify appropriate "slow" "fast" subproblems, obtain their optimum solutions (compatible corresponding measurement structure), subsequently performances they achieve on...
The study focuses on the long-term prognosis of myocardial infarction (MI) influenced by neutrophil extracellular traps (NETs). It also aims to analyze and validate relative hub genes in this process, order further explore new therapeutic targets that can improve MI. We established a MI model mice ligating left anterior descending branch (LAD) conducted an 8-week continuous observation dynamic changes structure function heart these mice. Meanwhile, we administered Apocynin, inhibitor NADPH...
This paper studies, under state feedback policies, the H infinity control design for large-scale jump linear systems where form process admits strong and weak interactions. Through an analysis that covers both finite infinite horizon cases using averaging aggregation techniques, aggregate system of considerably smaller order has been obtained, along with a corresponding (compatible) cost function. reduced-order (aggregate) problem is another piecewise-deterministic problem, and, on basis...
We investigate the necessary and sufficient conditions for existence of diffeomorphisms that transforms stochastic nonlinear systems to various canonical forms. A main tool in our analysis is so called invariance under transformation rule directly relates coordinate deterministic uncertain systems. This allows utilization existing associated
This paper addresses the worst-case parameter identification problem for uncertain single-input/single-output (SISO) and multi-input/multi-output (MIMO) linear systems under partial state measurements derives identifiers using cost-to-come function method. In SISO case, identifier obtained subsumes Kreisselmeier observer as part of its structure with parameters set at some optimal values. Its is different from common least-squares (LS) identifier, however, in sense that there additional...
Using integrator backstepping we present a robust optimal control design method for nonlinear strict-feedback systems with disturbances also in form. We globally stabilize such while obtaining local optimality and global inverse optimality. An analytic example is presented which used to compare the performance of that linear design.
We study time-scale separation and robust controller design for a class of singularly perturbed nonlinear systems under perfect state measurements. The system dynamics are taken to be jointly linear in the fast variables, control disturbance inputs, but slow variables. Since global timescale may not always possible systems, we restrict our attention here some closed subset space, on which holds sufficiently small values singular perturbation parameter. construct composite based solutions...
In this article, we present robust adaptive controller design for SISO linear systems with noisy output measurements and partly measured disturbances. Using the worst-case analysis approach, formulate control problem as a non-linear H ∞-optimal under imperfect state solve it using game theory. The paradigm is same (Pan, Z. Başar, T., 1998, Adaptive Controller Design Tracking Disturbance Attenuation Linear Systems Noisy Output Measurements, CSL report, Urbana, IL: University of Illinois at...
We address the worst-case adaptive controller design problem for uncertain single-input single-output linear systems with noisy output measurements, under assumption that (parametrically) unknown system is minimum phase a known relative degree and high-frequency gain of sign. first formulate this control as nonlinear H <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sup> imperfect state which then directly addresses transient performance...
Abstract In this paper, we present robust adaptive controller design for SISO linear systems with zero relative degree under noisy output measurements. We formulate the control problem as a nonlinear H ∞ ‐optimal imperfect state measurements, and then solve it using game theory. By priori knowledge of parameter vector, apply soft projection algorithm, which guarantees robustness property closed‐loop system without any persistency excitation assumption reference signal. Owing to our...