Data-driven performance assessment of multivariable control loops using a modified Hurst exponent–based index

2020 ◽  
pp. 095965182096652
Author(s):  
Maryam Khosroshahi ◽  
Javad Poshtan
Keyword(s):  
Performance Assessment ◽  
Prior Knowledge ◽  
System Performance ◽  
Hurst Exponent ◽  
Minimum Variance ◽  
Practical Applications ◽  
Control Loops ◽  
System Parameters ◽  
Multivariate Systems ◽  
Hurst Exponents

Control system performance assessment is significant, especially in practical applications. One of the most important indices for the performance assessment of control systems is minimum variance. Calculating the minimum variance index in multivariate systems requires prior knowledge of system parameters and models, and is therefore an obstacle in practical applications. In this article, an index is proposed for the performance assessment of multivariate control loops, evaluating the system performance with the minimum variance criterion and using only the system’s routine operation data. This index can quantify the performance using neither any prior knowledge of system parameters nor the system’s optimal operation data. The proposed index is based on the Hurst exponent, a parameter for measuring correlations in time series data. In this article, detrended fluctuation analysis and rescaled range analysis are used to estimate the Hurst exponents of system outputs. Using a combination of these Hurst exponents, an index is defined for the performance assessment of multivariate systems. The results of simulation examples illustrate that the proposed index can assess the performance efficiently.

scholarly journals Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 831
Author(s):  
Izzat Al-Darraji ◽  
Dimitrios Piromalis ◽  
Ayad A. Kakei ◽  
Fazal Qudus Khan ◽  
Milos Stojemnovic ◽  
...  
Keyword(s):  
Neural Network ◽  
Controller Design ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Robot Arm ◽  
Robust Controller ◽  
Practical Applications ◽  
Control Loops ◽  
Modeling Errors ◽  
Aerial Robot

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d'Alembert principle. Secondly, an adaptive robust controller, based on a sliding mode, is designed to manipulate the problem of uncertainties, including modeling errors. Last, a higher stability controller, based on the RBF neural network, is implemented with the adaptive robust controller to stabilize the ARAs, avoiding modeling errors and unknown payload issues. The novelty of the proposed design is that it takes into account high nonlinearities, coupling control loops, high modeling errors, and disturbances due to payloads and environmental conditions. The model was evaluated by the simulation of a case study that includes the two proposed controllers and ARA trajectory tracking. The simulation results show the validation and notability of the presented control algorithm.

scholarly journals Perancangan Decision Support System Penilaian Kinerja Dosen Berdasarkan Penilaian Prestasi Kerja Pegawai dan Beban Kinerja Dosen

MATICS ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 48
Author(s):  
Rizal Furqan Ramadhan ◽  
Herman Tolle ◽  
Muhammad Aziz Muslim
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Performance Assessment ◽  
Support System ◽  
System Performance ◽  
Normal Medium ◽  
Higher Education System ◽  
Final Output ◽  
University Lecturers ◽  
Education Concept

<span>The lecturer is one of the essential<br />components in the Higher Education system. Performance<br />assessment of lecturer needs to be conducted to measure<br />the lecturer capability based on the Tri Darma’s Higher<br />Education concept. Related to the nowadays technology<br />development, to conduct performance assessment of<br />lecturer can use the Decision Support System based on<br />several criteria as the assessment material. The provided<br />criteria in this paper seem to be the obtained criteria from<br />P2KP and BKD component. P2KP is performance<br />assessment of lecturer under the Badan Kepegawaian<br />Negara (BKN) supervision. Meanwhile BKD is<br />performance assessment of lecturer under the DIKTI<br />supervision. The lecturer criteria are taken from those two<br />components because the lecturers’ status cannot be<br />separated from the officer under BKN and educator under<br />the DIKTI support. It is expected that the criteria coming<br />from both components integration will be able to produce<br />performance assessment of lecturer objectively. The<br />method to proceed the assessment was Weighted Product<br />(WP). The examined data of the lecturers were the<br />Brawijaya University lecturers’ data. The final<br />examination data was conducted by taking the data<br />randomly from 20 Brawijaya University lecturers. The<br />final output from this Decision Support System is the<br />lecturers which are selected from three categories, which<br />are, less, normal, and good. It is expected that Decision<br />Support System is able to categorize the standard eligible<br />lecturer (Normal/medium category), and the lecturer<br />surpassing the standard (good category).<br /></span>

Long-term dependency between sovereign bonds and sectoral indices of India: evidence using Hurst exponent and wavelet analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santanu Das ◽  
Ashish Kumar
Keyword(s):  
Wavelet Analysis ◽  
Hurst Exponent ◽  
Minimum Variance ◽  
Portfolio Risk ◽  
Content Type ◽  
Sovereign Bonds ◽  
Portfolio Returns ◽  
Portfolio Managers ◽  
Practical Implications

PurposeThe purpose of this study is to provide a new way to optimize a portfolio and to show that combining the Hurst exponent and wavelet analysis may help to increase portfolio returns.Design/methodology/approachThe authors use the Hurst exponent and wavelet analysis to study the long-term dependencies between sovereign bonds and sectoral indices of India. The authors further construct and evaluate the performance of three portfolios constructed on the basis of Hurst standard deviation (SD) – global minimum variance (GMV), most diversified portfolio (MDP) and equal risk contribution (ERC).FindingsThe authors find that an ERC portfolio generates positive superior return as compared other two. Since our sample includes periods of two crisis – post-2007 financial crisis and the ongoing pandemic, this study reveals that combining government bond with equities and gold provides a higher returns when the portfolios are constructed using the risk exposures of each asset in the overall portfolio risk.Practical implicationsThe findings provide guidance to portfolio managers by helping them to select assets using the Hurst approach and wavelet analysis thereby increasing the portfolio returns.Originality/valueIn this study, the authors use a combination of Hurst exponent and wavelet analysis to understand the long-term dependencies among various assets and provide a new methodology to optimize a portfolio. As far as the authors’ knowledge, no study in the past has attempted to provide a joint framework for portfolio optimization and therefore this study is the first to apply this methodology.

Sign in / Sign up

Export Citation Format

Share Document