Disturbance-Kalman state for linear offset free MPC

• Autorzy: Tuan Truong Thanh , Zabiri Haslinda , Mutalib Mohammad Ibrahim Abdul , Vo Dai-Viet N.

Identyfikatory

DOI

10.24425/acs.2022.140869

• Języki publikacji: EN

Abstrakty

EN

In model predictive control (MPC), methods of linear offset free MPC are well established such as the disturbance model, the observer method and the state disturbance observer method. However, the observer gain in those methods is difficult to define. Based on the drawbacks observed in those methods, a novel algorithm is proposed to guarantee offset-free MPC under model-plant mismatches and disturbances by combining the two proposed methods which are the proposed Recursive Kalman estimated state method and the proposed Disturbance-Kalman state method. A comparison is made from existing methods to assess the ability of providing offset-free MPC on Wood-Berry distillation column. Results shows that the proposed offset free MPC algorithm has better disturbance rejection performance than the existing algorithms.

Słowa kluczowe

EN

Kalman filter; plant-model mismatch; offset free MPC; disturbance model

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2022
• Tom: Vol. 32, No. 1
• Strony: 153--173
• Opis fizyczny: Bibliogr. 28 poz., rys., tab., wykr., wzory

Twórcy

autor

Tuan Truong Thanh

• Petrovietnam University, 762 Cach Mang Thang Tam Street, Long Toan Ward, Ba Ria City 78109, Ba Ria Vung Tau Province, Vietnam

autor

Zabiri Haslinda

• Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Tronoh, Perak, Malaysia

autor

Mutalib Mohammad Ibrahim Abdul

• Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Tronoh, Perak, Malaysia

autor

Vo Dai-Viet N.

• Center of Excellence for Green Energy and Environmental Nanomaterials (CE@GrEEN), Nguyen Tat Thanh University, 300A Nguyen Tat Thanh, District 4, Ho Chi Minh City755414, Viet Nam

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Uwagi

1. This work is funded by Petrovietnam University under grant code GV2002.

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)