Guaranteed cost PID control for uncertain discrete‐time stochastic systems with additive gain perturbations

Mukaidani, Hiroaki

doi:10.1002/asjc.259

Cited by 6 publications

(3 citation statements)

References 30 publications

(93 reference statements)

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“…v ds = R s i ds + d ds dt (8) v qs = R s i qs + e ds (9) ds = L s i ds + L m i dr (10) Moreover, substituting (10) into (8) and (9), gives:…”

Section: Control Of Rotor Side Converterunclassified

“…The development of proportional‐integral‐derivative (PID) control has been around for 90 years and is still popular for industries and academies nowadays 9, 10. Although complicated control algorithms, such as adaptive control or optimal control, have been researched and proposed in recent years, PID control continues to be widely employed in various practical applications.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent control of doubly‐fed induction generator systems using PIDNNs

Lin

Hwang

Tan

et al. 2011

Asian Journal of Control

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An intelligent control for a stand-alone doubly-fed induction generator (DFIG) system using a proportional-integral-derivative neural network (PIDNN) is proposed in this study. This system can be applied as a standalone power supply system or as the emergency power system when the electricity grid fails for all sub-synchronous, synchronous, and super-synchronous conditions. The rotor side converter is controlled using field-oriented control to produce 3-phase stator voltages with constant magnitude and frequency at different rotor speeds. Moreover, the grid side converter, which is also controlled using field-oriented control, is primarily implemented to maintain the magnitude of the DC-link voltage. Furthermore, the intelligent PIDNN controller is proposed for both the rotor and grid side converters to improve the transient and steady-state responses of the DFIG system for different operating conditions. Both the network structure and online learning algorithm are introduced in detail. Finally, the feasibility of the proposed control scheme is verified through experimentation.

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“…v ds = R s i ds + d ds dt (8) v qs = R s i qs + e ds (9) ds = L s i ds + L m i dr (10) Moreover, substituting (10) into (8) and (9), gives:…”

Section: Control Of Rotor Side Converterunclassified

Section: Introductionmentioning

confidence: 99%

Intelligent control of doubly‐fed induction generator systems using PIDNNs

Lin

Hwang

Tan

et al. 2011

Asian Journal of Control

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show abstract

“… presented exponential stability and delayed‐state‐feedback stabilization criteria for a class of nonlinear uncertain stochastic time‐delay systems. investigated a design method for robust nonfragile PID control that is based on the guaranteed cost control problem for a class of uncertain discrete‐time stochastic systems with additive gain perturbations. All the aforementioned studies try to stabilize or control the states or the outputs of the system.…”

Section: Introductionmentioning

confidence: 99%

Model‐Reference Adaptive Moment Control of Uncertain Nonlinear Stochastic Systems

Beheshtipour

Khaloozadeh

Amjadifard

2018

Asian Journal of Control

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In this paper, a new model-reference adaptive moment control method is proposed to control the first and second moments of an uncertain nonlinear system with additive external stochastic excitation. This method has established a closed-loop control system that calculates an adaptive stochastic nonlinear input by introducing a Lyapunov function and adaptive update law. The proposed adaptive structure is innovative in trying to minimize two errors simultaneously: the moments tracking error and the error between the nonlinear system output and reference model. Furthermore, the proposed method can control the expected and covariance matrices of the states without needing to solve the complicated Fokker-Planck-Kolmogorov differential equation or using the approximate methods. Simulation has been performed on two practical examples, which show a good performance for the designed controller.

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Systematic linear matrix inequality conditions to design a robust decentralised observer-based optimal control for interconnected systems

Tlili

Braïek

2012

IET Control Theory &Amp; Applications

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Guaranteed cost PID control for uncertain discrete‐time stochastic systems with additive gain perturbations

Cited by 6 publications

References 30 publications

Intelligent control of doubly‐fed induction generator systems using PIDNNs

Intelligent control of doubly‐fed induction generator systems using PIDNNs

Model‐Reference Adaptive Moment Control of Uncertain Nonlinear Stochastic Systems

Systematic linear matrix inequality conditions to design a robust decentralised observer-based optimal control for interconnected systems

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