Optimized Active Disturbance Rejection Control for DC-DC Buck Converters With Uncertainties Using a Reduced-Order GPI Observer

Haihang

et al. 2018

Energies

Large-scale wind power interfacing to the power grid has an impact on the stability of the power system. However, with an additional damping controller of the wind generator, new ways for improving system damping and suppressing the low frequency oscillation (LFO) of power systems can be put forward. In this paper, an active-reactive power additional damping controller based on active disturbance rejection control (ADRC) is proposed. In order to improve the precision of the controller, the theory of data driven control is adopted, using the numerical algorithms for subspace state space system identification (N4SID) to obtain the two order model of the ADRC controlled object. Based on the identification model, the ADRC additional damping controller is designed. Taking a 2-area 4-machine system containing the doubly fed induction generator (DFIG) wind farm as an example, it is verified that the active-reactive additional damping controller designed in this paper performs well in suppressing negative-damping LFO and forced power oscillation. When the operation state of the power system changes, it can still restrain the LFO effectively, showing stronger robustness and better effectiveness compared to the traditional proportional-integral-derivative (PID) additional damping controller.

Section: The Principle Of Adrcmentioning

confidence: 99%

Active-Reactive Additional Damping Control of a Doubly-Fed Induction Generator Based on Active Disturbance Rejection Control

Haihang

et al. 2018

Energies

“…Over the past few decades, due to its practical insights, the model predictive control (MPC) problem has attracted considerable research interest in systems with bounded disturbances, which gives rise to robust MPC (RMPC), see [4], [10], [17], [35] for discrete-time systems and [21], [26]- [28] for continuous-time systems. Up to date, RMPC strategy has been extensively applied into various engineering areas such as chemical process, power systems, DC motors and mobile robots [8], [10]- [14], [31], [36].…”

Section: Introductionmentioning

confidence: 99%

N-Step MPC for Systems With Persistent Bounded Disturbances Under SCP

Song

Wang

IEEE Trans. Syst. Man Cybern, Syst.

et al. 2020

This paper is concerned with the N -step model predictive control (MPC) problem for a class of constrained systems with persistent bounded disturbances under the stochastic communication protocol (SCP). The control signals are transmitted to the plant via a shared network subject to a prescribed SCP for the purpose of avoiding data collisions. The SCP scheduling, which is governed by a Markov chain, is applied to orchestrate the transmission order of the controller nodes. Under the SCP, only one control node is allowed to update the control signal sent to the plant at each communication instant. Our aim is to design a set of desired controllers in the framework of N -step MPC such that the mean-square input-to-state stability of the closedloop system is guaranteed. An optimization algorithm consisting of both off-line and online parts is developed to cope with the design problem of the N -step controller. Finally, a numerical example is utilized to illustrate the validity of the proposed Nstep MPC strategy.Index Terms-N -step model predictive control, stochastic communication protocol, mean-square input-to-state stability, persistent bounded disturbances.Yan Song received the B.Sc. degree in materials science and engineering

“…H OW to attenuate external disturbances and system uncertainties has always been an attractive subject in both control theory and practical engineering [1]. Targeted at this old but still open issue, disturbance observer based control (DOBC) method, initiatively put forward by Kouhei Ohnishi [2] and independently developed by others [3]- [5], provides an alternative practical solution and has also proved its effectiveness in plenty of industrial sites, e.g., robots [6]- [8], motion control systems [9]- [12] and power electronics [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Disturbance Rejection for Nonlinear Uncertain Systems With Output Measurement Errors: Application to a Helicopter Model

Yan

Zhang

et al. 2020

IEEE Trans. Ind. Inf.

Self Cite

As a virtual sensor, disturbance observer provides an alternative approach to reconstruct lumped disturbances (including external disturbances and system uncertainties) based upon system states/outputs measured by physical sensors. Not surprisingly, measurement errors bring adverse effects on the control performance and even the stability of the closed-loop system. Toward this end, this paper investigates the problem of disturbance observer based control for a class of disturbed uncertain nonlinear systems in the presence of unknown output measurement errors. Instead of inheriting from the estimation-error-driven structure of Luenberger type observer, the proposed disturbance observer only explicitly uses the control input. It has been proved that the proposed method endows the closed-loop system with strong robustness against output measurement errors and system uncertainties. With rigorous analysis under the semiglobal stability criterion, the guideline of gain choice based upon the proposed structure is provided. To better demonstrate feature and validity of the proposed method, numerical simulation and comparative experiments of a helicopter model are implemented.