parameter perturbations
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Author(s):  
Jia Song ◽  
Jiangcheng Su ◽  
Yunlong Hu ◽  
Mingfei Zhao ◽  
Ke Gao

This paper investigates the stability and performance of the linear active disturbance rejection control (LADRC)–based system with uncertainties and external disturbance via transfer functions and a frequency-domain view. The performance of LADRC is compared with the state-observer-based state feedback control (SOSFC) and state feedback control (SFC). First, the transfer functions and the error transfer functions for LADRC, SOSFC, and SFC are studied using the state-space method. It is proven that the LADRC-, SOSFC-, and SFC-based closed-loop systems have the same transfer function from the reference input to the output and achieve the same control effects for the nominal system. Then, it is proven for the first time that the LADRC has a better anti-interference ability than the SOSFC and SFC. Besides, the asymptotic stability condition of LADRC-based closed-loop system considering large parameter perturbations is given first. Moreover, the sensitivity analysis of the closed-loop system is carried out. The results show that the LADRC has stronger robustness under parameter perturbations. According to the results, we conclude that the LADRC is of great disturbance rejection ability and strong robustness.


Author(s):  
Mingming Mei ◽  
Shuo Cheng ◽  
Liang Li ◽  
Bingjie Yan

Abstract Based on the guaranteed cost theory, this paper proposes a robust controller for the automotive electro-hydraulic coupling system. However, parameter perturbation caused by the model linearization is a critical challenge for the nonlinear electro-hydraulic coupling system. Generally, the electrical brake booster system (E-Booster) can be separated into three parts, a permanent magnet synchronous motor (PMSM), a hydraulic model of the master cylinder, and the transmission mechanism. In this paper, the robust guaranteed cost controller (RGCC) could adjust accurately the pushrod position of the E-Booster and has strong robustness against internal uncertainties, and the linear extended state observer (LESO) was utilized to optimize E-Booster's dynamic performance. Thus, the tracking differentiator (TD) and LESO are used to improve the dynamic precision and reduce the hysteresis effect. The overshoot is suppressed by TD, and the disturbance caused by nonlinear uncertainty is restrained by LESO. Experiment results show that RGCC sacrifices 6% phase lag in the low-frequency domain for a 10% and 40% reduction in first and second-order respectively compared with the proportion integration differentiation (PID). Results demonstrate that RGCC has higher precision and stronger robustness in dynamic behaviour.


2021 ◽  
Vol 8 ◽  
Author(s):  
Prima Anugerahanti ◽  
Onur Kerimoglu ◽  
S. Lan Smith

Chlorophyll (Chl) is widely taken as a proxy for phytoplankton biomass, despite well-known variations in Chl:C:biomass ratios as an acclimative response to changing environmental conditions. For the sake of simplicity and computational efficiency, many large scale biogeochemical models ignore this flexibility, compromising their ability to capture phytoplankton dynamics. Here we evaluate modelling approaches of differing complexity for phytoplankton growth response: fixed stoichiometry, fixed stoichiometry with photoacclimation, classical variable-composition with photoacclimation, and Instantaneous Acclimation with optimal resource allocation. Model performance is evaluated against biogeochemical observations from time-series sites BATS and ALOHA, where phytoplankton composition varies substantially. We analyse the sensitivity of each model variant to the affinity parameters for light and nutrient, respectively. Models with fixed stoichiometry are more sensitive to parameter perturbations, but the inclusion of photoacclimation in the fixed-stoichiometry model generally captures Chl observations better than other variants when individually tuned for each site and when using similar parameter sets for both sites. Compared to the fixed stoichiometry model including photoacclimation, models with variable C:N ratio perform better in cross-validation experiments using model-specific parameter sets tuned for the other site; i.e., they are more portable. Compared to typical variable composition approaches, instantaneous acclimation, which requires fewer state variables, generally yields better performance but somewhat lower portability than the fully dynamic variant. Further assessments using objective optimisation and more contrasting stations are suggested.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Liang Qiao ◽  
Zhaomin Lv

The finite-time admissibility analysis and controller design issues for extended T-S fuzzy stochastic singular systems (FSSSs) with distinct differential term matrices and Brownian parameter perturbations are discussed. When differential term matrices are allowed to be distinct in fuzzy rules, such fuzzy models can describe a wide class of nonlinear stochastic systems. Using fuzzy Lyapunov function (FLF), a new and relaxed sufficient condition is proposed via strict linear matrix inequalities (LMIs). Different from the existing stability conditions by FLF, the derivative bounds of fuzzy membership functions are not required in this condition. Based on admissibility analysis results, a design method for parallel distribution compensation (PDC) controller of FSSSs is given to guarantee the finite-time admissibility of the closed-loop system. Finally, the feasibility and effectiveness of the proposed methods in this article are illustrated with three examples.


2021 ◽  
Author(s):  
Aristofanis Tsiringakis ◽  
Wim de Rooy ◽  
Sibbo van der Veen ◽  
Jan Barkmeijer

<p>In an ensemble prediction system (EPS) the uncertainty in the initial atmospheric conditions is usually represented via perturbation of the initial atmospheric state and different boundary conditions at the beginning and throughout the duration of the forecast. These approaches exclude the uncertainty due to the representation of physical processes within the parameterization schemes of a numerical weather prediction model (NWP). Much of the uncertainty in the presentation of physical process arises from uncertain parameter values regulating key physical processes in the boundary-layer and microphysics schemes. This uncertainty can be represented with a Stochastically Perturbed Parameterization (SPP) scheme, where parameter values for the different model grid points are randomly selected from a defined probability density function. The SPP scheme can improve model performance and increase ensemble spread, but may lead to unrealistic parameter values, which can introduce additional model bias. A potential solution is to use coupled/correlated perturbations for relevant SPP parameters to increase the model performance and ensemble spread, while maintaining physically realistic ranges for the parameters. In this study, we investigate the impact of coupled perturbations in key parameters within the boundary-layer and microphysics schemes of the HarmonEPS model using the new SPP scheme. The performance of the coupled perturbations experiment is evaluated against HarmonEPS experiments using independent parameter perturbations, and perturbations in the initial atmospheric state and boundary conditions for both a winter and a summer period.  We find that coupled perturbations in the SPP scheme can decrease model bias and increase the ensemble spread for the 2m temperature and relative humidity, 10m-wind speed and total cloud cover.</p>


2021 ◽  
Author(s):  
Suli Pan ◽  
Yue-Ping Xu ◽  
Haiting Gu ◽  
Zhixu Bai ◽  
Weidong Xuan

Abstract Hydrological and climatic data at finer temporal resolutions are considered essential to model hydrological processes, especially for short duration flood events. Parameter transferability is an essential approach to obtain sub-daily hydrological simulations at many regions without sub-daily data. In this study, the objective is to investigate temporary dependency of parameter sensitivity for different flood types, which contributes to research of parameter transferability. This study is conducted in a medium-sized basin using a distributed hydrological model, DHSVM. Thirty-six flood events in the period of 04/12/2006–07/01/2013 in the Jinhua River basin, China, are classified into three flood types (FF: flash flood, SRF: short rainfall flood and LRF: long rainfall flood) by using the fuzzy decision tree method. The results show that SRF is the dominant flood type in the study area, followed by LRF and FF. Runoff simulations of FF and SRF are more sensitive to parameter perturbations than that of LRF. Sensitive parameters are highly dependent on temporal resolutions. The temporary dependency of LRF is the highest, followed by SRF and FF. More attention should be payed to sensitive and highly temporal dependent parameters in a subsequent parameter transfer process. Further study referring this result is required to test the applicability.


Author(s):  
Evan A. Kalina ◽  
Isidora Jankov ◽  
Trevor Alcott ◽  
Joseph Olson ◽  
Jeffrey Beck ◽  
...  

AbstractThe High-Resolution Rapid Refresh Ensemble (HRRRE) is a 36-member ensemble analysis system with nine forecast members that utilizes the Advanced Research Weather Research and Forecasting (ARW-WRF) dynamic core and the physics suite from the operational Rapid Refresh/High-Resolution Rapid Refresh deterministic modeling system. A goal of HRRRE development is a system with sufficient spread amongst members, comparable in magnitude to the random error in the ensemble mean, to represent the range of possible future atmospheric states. HRRRE member diversity has traditionally been obtained by perturbing the initial and lateral boundary conditions of each member, but recent development has focused on implementing stochastic approaches in HRRRE to generate additional spread. These techniques were tested in retrospective experiments and in the May 2019 Hazardous Weather Testbed Spring Experiment (HWT-SE). Results show a 6–25% increase in the ensemble spread in 2-m temperature, 2-m mixing ratio, and 10-m wind speed when stochastic parameter perturbations are used in HRRRE (HRRRE-SPP). Case studies from HWT-SE demonstrate that HRRRE-SPP performed similar to or better than the operational High-Resolution Ensemble Forecast system version 2 (HREFv2) and the non-stochastic HRRRE. However, subjective evaluations provided by HWT-SE forecasters indicated that overall, HRRRE-SPP predicted lower probabilities of severe weather (using updraft helicity as a proxy) compared to HREFv2. A statistical analysis of the performance of HRRRE-SPP and HREFv2 from the 2019 summer convective season supports this claim, but also demonstrates that the two systems have similar reliability for prediction of severe weather using updraft helicity.


2021 ◽  
pp. 1-14
Author(s):  
Sangeeta Gupta ◽  
Pragya Varshney ◽  
Smriti Srivastava

This paper proposes a scheme to synchronize fractional order chaotic systems employing fractional PID controller. The parameters of FOPID are tuned using Swarm based optimization techniques, viz.: Whale optimization algorithm and Particle swarm optimization techniques. To assert the complete synchronization, master-slave method has been implemented. Chaotic systems are highly dependent upon initial conditions and parameter perturbations. Therefore, taking these properties into consideration, synchronization of two identical fractional order financial chaotic systems is performed with distinct initial conditions. To show the efficacy of the proposed method, analysis is performed for orders between 0 to 1, and also for sensitivity to initial conditions.


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