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Abstract

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 onWood-Berry distillation column. Results shows that the proposed offset free MPC algorithm has better disturbance rejection performance than the existing algorithms.
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Authors and Affiliations

Truong Thanh Tuan
1
Haslinda Zabiri
2
Mohammad Ibrahim Abdul Mutalib
2
Dai-Viet N. No
3

  1. Petrovietnam University, 762 Cach Mang Thang Tam Street, Long Toan Ward, Ba Ria City 78109, Ba Ria Vung Tau Province, Vietnam
  2. Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Tronoh, Perak, Malaysia
  3. 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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