[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Li et al., 2022 - Google Patents

Decentralized stabilization of large-scale stochastic nonlinear systems with time-varying powers

Li et al., 2022

Document ID
5245922879428542808
Author
Li H
Li W
Gu J
Publication year
Publication venue
Applied Mathematics and Computation

External Links

Snippet

In this paper, we study the decentralized stabilization problem for large-scale high-order stochastic nonlinear systems with time-varying powers. By using the backstepping design technique, a new decentralized state-feedback controller is constructed to ensure the closed …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models

Similar Documents

Publication Publication Date Title
Haddad et al. Adaptive perimeter control for multi-region accumulation-based models with state delays
Schweidtmann et al. Deterministic global optimization with artificial neural networks embedded
Mohanty et al. Design and analysis of fuzzy PID controller with derivative filter for AGC in multi‐area interconnected power system
Gao et al. A new approach to quantized feedback control systems
Camacho et al. Some long time delay sliding mode control approaches
Assawinchaichote et al. H∞ output feedback control design for uncertain fuzzy singularly perturbed systems: an LMI approach
Zhu et al. Stability analysis for stochastic neural networks of neutral type with both Markovian jump parameters and mixed time delays
Fraile-Ardanuy et al. Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms
CN102870309A (en) Method and system for facilitating design of a high voltage (HVDC) control system, an HVDC system and a method for optimising an HVDC system
Barton et al. Design of process operations using hybrid dynamic optimization
Li et al. Decentralized stabilization of large-scale stochastic nonlinear systems with time-varying powers
Wen et al. Homogeneous constrained finite-time controller for double integrator systems: Analysis and experiment
CN110797857A (en) Switching fuzzy model prediction control method for uncertain direct-current micro-grid
Pradhan et al. Analysis of hybrid fuzzy logic control based PID through the filter for frequency regulation of electrical power system with real-time simulation
Udhayakumar et al. Novel finite and fixed-time stability theorems for fractional-order impulsive discontinuous systems and their application to multi-agent systems
Mohagheghi et al. Hardware implementation of a mamdani fuzzy logic controller for a static compensator in a multimachine power system
Haris et al. A nonlinear adaptive controller for the synchronization of unknown identical chaotic systems
Vatankhah Ghadim et al. Fermat-curve based fuzzy inference system for the fuzzy logic controller performance optimization in load frequency control application
Zanovello et al. Model predictive control with soft constraints with application to lime kiln control
Duan et al. Robust model predictive control based on recurrent multi‐dimensional Taylor network for discrete‐time non‐linear time‐delay systems
Harris et al. On the computation of a nonlinearity measure using functional expansions
Scarratt et al. Dynamical adaptive first and second-order sliding backstepping control of nonlinear nontriangular uncertain systems
Wang et al. Sliding mode dynamic surface control for multi-machine power systems with time delays and dead-zones
Perkins et al. Optimization as a tool for design/control integration
Ning et al. Robust adaptive decentralized control for a class of noaffine stochastic nonlinear interconnected systems