Weighted-coupling CSTR modeling and model predictive control with parameter adaptive correction for the goethite process

Xie, Shiwen; Xie, Yongfang; Gui, Weihua; Yang, Chunhua

doi:10.1016/j.jprocont.2018.05.006

Cited by 18 publications

(8 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[4][5][6] Moreover, the nonlinearities of process systems have to be considered during design of controllers, especially for the chemical process systems leading to large-scale MPC problems. 7,8 There are some common approaches for MO-MPC, such as weighted MO-MPC, utopia-tracking MO-MPC and lexicographic MO-MPC, etc. The weighted MO-MPC is to summarize multiple objectives with some weights reflecting the relative importance of the objectives.…”

Section: Introductionmentioning

confidence: 99%

“…The weighted MO-MPC is to summarize multiple objectives with some weights reflecting the relative importance of the objectives. 3,[7][8][9][10] The stability properties of weighted MO-MPC are established by proving that the weighted sum is a Lyapunov function of resulting systems. Although this strategy can reduce computational effort, the selection of appropriate weights is not a trivial task as the weights do not lead to proportion changes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prioritized multi‐objective model predictive control without terminal constraints and its applications to nonlinear processes

Yongda

2021

Optim Control Appl Methods

View full text Add to dashboard Cite

Many process control problems encapsulate multiple and often conflicting objective criteria spanning different levels of relative importance. In this paper, we consider a class of multi-objective receding horizon optimal control problems and propose a novel multi-objective model predictive control (MO-MPC) scheme for nonlinear systems subject to constraints and several prioritized (economic) criteria. Combining the lexicographic optimization and the receding horizon principle, a prioritized MO-MPC scheme without terminal constraints is presented to solve economically optimal control problems of the constrained nonlinear system. The results on recursive feasibility and stability of the MO-MPC are established in the context of economy optimization and no terminal constraints. Particularly, for the systems without state constraints, the computational burden of the MO-MPC is reduced due to the removal of terminal constraints. Using an intuitive optimizaiton, the feasible set of initial states is offline estimated to move out the initial feasibility condition. The proposed MO-MPC strategy is verified by the multiple control problems of a coupled-tank system and a six-order fluidized bed combustion process.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prioritized multi‐objective model predictive control without terminal constraints and its applications to nonlinear processes

Yongda

2021

Optim Control Appl Methods

View full text Add to dashboard Cite

show abstract

“…The unit has the potential to increase the rate and adequacy of chemical reactions [1]. From the viewpoint of control, the dynamic model of a CSTR is nonlinear, and the system is subject to external disturbances and system uncertainty [2][3][4][5]. These characteristics provide control challenges and a number of methods have been proposed to deal with such complex systems, including neural network control [6], optimal output tracking control [7] and model predictive control [8].…”

Section: Introductionmentioning

confidence: 99%

Disturbance Observer Based Adaptive Sliding Mode Control for Continuous Stirred Tank Reactor

Zhao

2019

2019 Chinese Control Conference (CCC)

View full text Add to dashboard Cite

The continuous stirred tank reactor (CSTR) typifies an important class of process control systems. Is is a nonlinear system and is sensitive to both external disturbances and system uncertainty. Given these challenges, a nonsingular terminal sliding mode observer is proposed to estimate any external disturbance. Then, a continuous adaptive sliding mode control method is combined with the proposed disturbance observer. This is found to reduce chattering and improve control accuracy when compared with other methods. A full Lyapunov stability proof of the resulting closed-loop system is performed and the effectiveness of the proposed approach is demonstrated by simulation experiments.

show abstract

“…Literatürde örnekleri mevcut olan model yapısının özgün yazılımla uygulaması yapılırsa, gömülü sistemlere adaptasyon ve nesnel yazılımlara modül olarak ekleme olanaklarına kavuşulur. Yazılımdan beklentimiz, model yapısını oluşturan hem zaman serisinin hem de lineer olmayan fonksiyonun katsayılarını gerçek sistemi ifade edecek şekilde optimize Pamukkale Univ Muh Bilim Derg, 24 (8), 1418-1424, 2018(TOK'2017 İ. Alışkan edebilmesidir. Temel yaklaşım olarak, en küçük kareler yönteminin kullanıldığı çalışmalar literatürde rahatlıkla bulunabilir [12], [13], [17], [18].…”

Section: Introductionunclassified

“…Örneğin[27]'de sistem parametrelerindeki belirsizliklerle mücadele etme amacı ile adaptif yapay sinir ağı geliştirilmiş ve MÖK içerisinde tahmin modeli olarak kullanılmıştır. Başka bir çalışmada ise götit prosesine ağırlıklı sürekli karıştırma reaktörü modeli uygulanmış ve Lyapunov fonksiyonu kullanılarak sistem tanımlama ile elde edilen model çalışma sırasında özgün yazılım ile optimize edilmiştir[28]. Her iki çalışmada MÖK performans artışı sayısal ve görsel veriler ile ortaya koyulmuştur.…”

unclassified

Gradient Based Identification of Wiener Systems

Aliskan¹

2018

Pamukkale J Eng Sci

View full text Add to dashboard Cite

Tek bir bloktan oluşan sistemlerde geribesleme ile kontrol ve giriş-çıkış ilişkisinin kurulması klasik kontrolde yaygın olarak görülmektedir. Fakat doğal sistemler göz önüne alındığında çok bloklu yapılar ve bu bloklar içerisinde de lineer olmayan fonksiyonlar görülür. Bu çalışmanın konusu, giriş işaretinin lineer bloka uygulandığı ve çıkışın lineer olmayan fonksiyondan alındığı sistem yapısı olan Wiener tipi sistemlerin tanımlamasıdır. Durum geribeslemenin mümkün olmadığı bu sistem tipinde tanımlama ile farklı kontrol algoritmalarının kullanımı mümkündür. Sistem tanımlamada harici girişli otoregresif ağ (ARX)-polinom kaskad bağlantısı tercihi ile en küçük kareler yöntemi ve eğim bilgileri sayesinde sistemin giriş-çıkışı arasındaki matematiksel ilişki elde edilmiştir. Üç farklı örnek sistem üzerinde çalışmalar yapılmış, MATLAB/Simulink ortamında veri kümeleri elde edilmiş ve yapılan sistem tanımlamalarının başarımı grafikler ile sunulmuştur. In systems consisting of a single block, the establishment of feedback control and input-output relationship is common in classical control. However, considering natural systems, there are many block structures and non-linear functions within these blocks. The subject of this study is the identification of Wiener type systems, which is the system structure in which the input signal is applied to the linear block and its output is taken from the nonlinear function. It is possible to use different control algorithms with identification in this type of system where state feedback control is not possible. In system identification, the mathematical relationship between the input and output of the system has been obtained by the choice of auto regressive with exogenous inputs (ARX)-polynomial cascade connection with using the least squares method and gradient information. Three different benchmark systems have been studied in MATLAB/Simulink and the performances of the identifications made with the dataset are presented graphically.

show abstract

Weighted-coupling CSTR modeling and model predictive control with parameter adaptive correction for the goethite process

Cited by 18 publications

References 26 publications

Prioritized multi‐objective model predictive control without terminal constraints and its applications to nonlinear processes

Prioritized multi‐objective model predictive control without terminal constraints and its applications to nonlinear processes

Disturbance Observer Based Adaptive Sliding Mode Control for Continuous Stirred Tank Reactor

Gradient Based Identification of Wiener Systems

Contact Info

Product

Resources

About