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

Sokolov, 2016 - Google Patents

Adaptive stabilization of parameter-affine minimum-phase plants under Lipschitz uncertainty

Sokolov, 2016

Document ID
8680638451505792908
Author
Sokolov V
Publication year
Publication venue
Automatica

External Links

Snippet

The maximum capability of feedback control for discrete-time systems under a nonparametric Lipschitz uncertainty was first established in Xie and Guo (2000) for the simplest dynamical control system. It was shown that the necessary and sufficient condition …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive 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
    • G05B13/042Adaptive 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • G06F7/38Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
    • G06F7/48Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
    • G06F7/4806Computations with complex numbers
    • G06F7/4818Computations with complex numbers using coordinate rotation digital computer [CORDIC]
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/021Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a variable is automatically adjusted to optimise the performance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Mayne et al. Robust output feedback model predictive control of constrained linear systems
Sokolov Adaptive stabilization of parameter-affine minimum-phase plants under Lipschitz uncertainty
Cagienard et al. Move blocking strategies in receding horizon control
Edwards A practical method for the design of sliding mode controllers using linear matrix inequalities
Hu et al. Output feedback robust MPC for linear systems with norm-bounded model uncertainty and disturbance
Zhu et al. Adaptive output feedback control for uncertain linear time-delay systems
Müller et al. On the performance of economic model predictive control with self-tuning terminal cost
Liu et al. Full‐complexity polytopic robust control invariant sets for uncertain linear discrete‐time systems
Hetel et al. Variable structure control with generalized relays: A simple convex optimization approach
Reble et al. Model predictive control of constrained non-linear time-delay systems
Kang et al. A survey of observers for nonlinear dynamical systems
Chakrabarty et al. Approximate dynamic programming for linear systems with state and input constraints
Primbs et al. A framework for robustness analysis of constrained finite receding horizon control
Ping et al. An observer‐based output feedback robust MPC approach for constrained LPV systems with bounded disturbance and noise
Danik et al. The construction of stabilizing regulators sets for nonlinear control systems with the help of Padé approximations
Kim Delay-dependent robust H∞ control for discrete-time uncertain singular systems with interval time-varying delays in state and control input
Sokolov Adaptive l1 robust control for SISO systems
Ge et al. Optimal control for unknown mean-field discrete-time system based on Q-Learning
Batmani On the design of event‐triggered suboptimal controllers for nonlinear systems
Costanza et al. Equations for the missing boundary values in the hamiltonian formulation of optimal control problems
He et al. Optimized‐based stabilization of constrained nonlinear systems: a receding horizon approach
Tran et al. Fixed‐Time Complex Modified Function Projective Lag Synchronization of Chaotic (Hyperchaotic) Complex Systems
Gürsoy-Demir et al. A nonlinear disturbance observer-based adaptive integral sliding mode control for missile guidance system
Mozelli et al. SOFC for TS fuzzy systems: Less conservative and local stabilization conditions
Sokolov Adaptive stabilization of minimum-phase plant under Lipschitz uncertainty via Yakubovich's method of recurrent objective inequalities