Robust closed loop reference MRAC with PI compensator

Youssef

Int Trans Electr Energ Syst

et al. 2019

Summary To eliminate problems of traditional perturb and observe (TPO) maximum power point tracking (MPPT) relying on large scale variable speed wind energy conversion system (VS‐WECS), this paper suggests a variable step size perturb and observe (VS‐PO) MPPT algorithm. The VS‐PO technique is performed to split the power‐speed (P‐ω) curve with four segments every with a particular step size. A large step size is chosen for the two segments distant from the MPP. Otherwise, a smaller step size can be implemented. The proposed algorithm can achieve the maximum power without large oscillations and reduce the settling time under different wind speed conditions, which means high tracking efficiency. Moreover, the model reference adaptive control (MRC) is applied instead of a PI controller to regulate the rotor speed, which maximizes the extracted power. Also, the MRC successful for reducing the large oscillation and settling time compared with the PI controller. The suggested control technique is tested over a 1.5 MW DFIG WECS by MATLAB/Simulink software.

Section: Model Reference Adaptive Control (Mrc)mentioning

confidence: 99%

“…By using an adaptive technique with the traditional PI control, the nonlinearities of the system can be compensated. In addition, MRC can guarantee asymptotic tracking performance 47 …”

Section: Speed Controller Schemesmentioning

confidence: 99%

Variable step size PO MPPT algorithm using model reference adaptive control for optimal power extraction

Youssef

Int Trans Electr Energ Syst

et al. 2019

Advances in Mechanical Engineering

“…For example, in previous works, [6][7][8] the classical theory of MRAC is applied to different control systems. In previous works, [9][10][11][12][13][14][15][16] MRAC is further employed to ameliorate the tracking performance of a control system.…”

Section: Introductionmentioning

confidence: 99%

A method to construct a reference model for model reference adaptive control

Zhu

Wang

et al. 2019

Model reference adaptive control takes the output of a reference model as the target and ensures that the actual output is consistent with the target. In this scenario, the reference model determines the performance of the control system. Constructing a reference model with specific performance is challenging, and most researchers construct the reference model by experience. As alternative frameworks, we propose two novel reference model construction methods, namely, zero-pole method and frequency response method. The zero-pole method establishes a nonlinear optimization model to ensure that the added zeros and poles are as far away from the imaginary axis as possible. In the case where this cannot be done, the frequency response method matches the system frequency response of the reference model and the given model to the extent possible using a nonlinear optimization model. Experimental results are presented to confirm that both methods can construct a reference model based on a given transfer function. Deviations in response between the reference models constructed using the two methods and the given model are compared, and the reasons for higher accuracy of the frequency response method are discussed.

Transactions of the Institute of Measurement and Control

“…Therefore, a great deal of effort has been devoted by researchers focusing on potential ways of improving the transient performance (Cao and Hovakimyan, 2008; Datta and Ioannou, 1994; Dey et al, 2016; Gibson et al, 2012, 2013; Ioannou and Kokotovic, 1984; Krstić et al, 1993; Lee and Huh, 1997; Narendra and Annaswamy, 1987; Nguyen, 2012; Parks, 1966; Stepanyan and Krishnakumar, 2010, 2012; Sun, 1993; Sun et al, 2016; Xin et al, 2012; Yucelen and Haddad, 2013). Some of these efforts include: modified standard adaptive law (Datta and Ioannou, 1994), multiple models with switching control schemes (Narendra and Balakrishnan, 1997), L 1 adaptive control (Cao and Hovakimyan, 2008; Hovakimyan and Cao, 2010) and closed-loop reference MRAC (Gibson et al, 2012, 2013; Lee and Huh, 1997; Stepanyan and Krishnakumar, 2010, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…In the first category, Datta and Ioannou (1994) introduced L 2 and L ∞ tracking error bound criteria to study the transient performance of MRAC schemes. In this work, a small tracking error is ensured with a high adaptation gain, which may lead to adverse effects, as discussed (Dey et al, 2016; Ioannou and Kokotovic, 1984; Yucelen and Haddad, 2013). Furthermore, a very high adaptation gain makes the differential equation of adaptive law stiff and may cause numerical instabilities (Ioannou et al, 2014), and may also excite unmodelled dynamics of the plant, leading to instability of the system (Ioannou and Sun, 2012).…”

Section: Introductionmentioning

confidence: 99%

Robust flexible adaptation gain based CRM for guaranteed transient performance

Dey

Jain

Padhy

2018

Self Cite

High adaptation gain in model reference adaptive control (MRAC) with closed-loop reference models (CRMs) is a necessary requirement to ensure guaranteed transient performance with better tracking and fast convergence. The high adaptation gain, however, may excite unmodelled dynamics, leading to instability, making the differential equations of the adaptive law stiff and causing numerical instability. Therefore, it becomes apparent that a compromise is required on either convergence speed and transient performance or system stability. This paper attempts to address these issues with a novel CRM-MRAC architecture with flexible adaptation gain, which varies as a function of the derived parameter estimation error. The proposed adaptive scheme mathematically ensures a designable upper bound of the L ∞ norm; it also ensures the absence of high-frequency oscillations in the control input, thereby making the system more robust and stable. The effectiveness of the proposed work has been validated with simulation studies on a standard numerical example and the performance has been compared with recent similar works.