Hybrid nonlinear model predictive control of a cooling water network

Viljoen, Johannes Henning; Muller, Cornelius Jacobus; Craig, I.K.

doi:10.1016/j.conengprac.2020.104319

Cited by 13 publications

(6 citation statements)

References 52 publications

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“…is the state at time step k, θ c (•) is a possibly nonlinear constraint function (which is shown in (20)), f (•) is the state transitions as given in (1) -(7), g(•) = I 7 • x is the output function and since only Q is controlled may be simplified to be y k = Q k , u k contains the exogenous input (the lockdown level l as in (13)), θ k represents the system parameters, and d k ∈ D represents the disturbance, which is later introduced in (19). The performance index (or objective function) to be minimized, J(•), depends on the policy in place as presented in the rest of this section, and is given in (15) and (17).…”

Section: Controller Designmentioning

confidence: 99%

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Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study

2020

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To curb the spread of COVID-19, many governments around the world have implemented tiered lockdowns with varying degrees of stringency. Lockdown levels are typically increased when the disease spreads and reduced when the disease abates. A predictive control approach is used to develop optimized lockdown strategies for curbing the spread of COVID-19. The strategies are then applied to South African data. The South African case is of interest as the South African government has defined five distinct levels of lockdown, which serves as a discrete control input. An epidemiological model for the spread of COVID-19 in South Africa was previously developed, and is used in conjunction with a hybrid model predictive controller to optimize lockdown management under different policy scenarios. Scenarios considered include how to flatten the curve to a level that the healthcare system can cope with, how to balance lives and livelihoods, and what impact the compliance of the population to the lockdown measures has on the spread of COVID-19. The main purpose of this article is to show what the optimal lockdown level should be given the policy that is in place, as determined by the closed-loop feedback controller.

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Section: Controller Designmentioning

confidence: 99%

“…Given that compliance to lockdown regulations has seemingly waned over time in South Africa, the compliance parameter (d) in (19) is initiated with a value of 1, and reduced linearly after a number of weeks in lockdown down to a value of 0.3 (as seen in the bottom panel of Fig. 7).…”

Section: Compliance To Lockdown Regulationsmentioning

confidence: 99%

Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study

2020

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“…Online model predictive control considering a piecewise-defined state-to-input matrix and reduced number of state transitions Pistikopoulos et al [24][25][26][27][28] Hybrid multiparametric model predictive control algorithms and applications Viljoen et al 29 Online model predictive control using a tree traversal algorithm…”

Section: Pregelj and Gerkšic ˇ23mentioning

confidence: 99%

Data‐driven prescriptive maintenance toward fault‐tolerant multiparametric control

Gordon

Pistikopoulos

2021

AIChE Journal

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Prescriptive maintenance can improve system effectiveness and system safety via integrated production and maintenance optimization. However due to system disruptions there is potential for abnormal operations and an undesirable increased occurrence of process safety incidents. This research provides a multiparametric‐based framework for safety‐aware, maintenance‐aware, and disruption‐aware process control. It leverages ensemble classification via machine learning classifiers for fault detection, mixed‐integer nonlinear programming for integrated safety‐aware production and maintenance scheduling, as well as hybrid multiparametric model predictive control for fault‐tolerant setpoint tracking. The results show that the ensemble classifier outperforms the individual classifiers in terms of fault detection accuracy, sensitivity, and specificity. Furthermore, it is seen that the developed controllers are able to reconfigure the control actions based on process disruption information. The framework is illustrated with a chemical complex system, and a cooling water system. The approach can be used to help improve the safety and productivity of industrial processes.

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“…A scholar divides the used car market into four development stages, analyzes each stage, and finally selects 8 indicators such as car brand, new car guide price, and car registration time to evaluate the price. The BP neural network algorithm is used as the core to construct Used car valuation model [4]. The model is then validated, and it is verified that the accuracy of the model is good.…”

Section: Introductionmentioning

confidence: 99%

Hybrid forecasting model in used car price forecasting based on stochastic algorithm

Li-li

Tian

Liu

2023

Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022)

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With the quiet change of people's consumption habits, the used car market has been unprecedentedly prosperous and developed. However, the current second-hand car market does not have a unified price evaluation standard, which leads to frequent occurrences of wanton price listings and excessively low or high transaction prices, which create great obstacles to the transaction process and seriously affect the health and order of the second-hand car market development. This paper selects 13 index variables that affect the price of used cars and analyzes the correlation between each index and the current price of used cars. Through the random forest prediction model, GBDT prediction model and SVM prediction model proposed in this paper, the used car prices are predicted and compared. It is hoped that the research in this paper will have important significance for promoting the standardization of car pricing in the used car market.

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Hybrid nonlinear model predictive control of a cooling water network

Cited by 13 publications

References 52 publications

Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study

Optimized Lockdown Strategies for Curbing the Spread of COVID-19: A South African Case Study

Data‐driven prescriptive maintenance toward fault‐tolerant multiparametric control

Hybrid forecasting model in used car price forecasting based on stochastic algorithm

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