Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control

Yizhou Fang, Antonios Armaou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An output feedback control structure is proposed for processes in the presense of disturbance and incomplete state information. It combines moving horizon estimation (MHE) and model predictive control (MPC), where Carleman approximation is employed to reduce the nonlinear process plant model and then pair and streamline the computations between the two components. After Carleman approximation, the CMHE/CMPC pair reduces the dynamic optimization problem using analytical expressions for the cost functionals and constraints. CMHE provided state estimates become the initial conditions for CMHE to decide the optimal control signals. With these signals continuously updated in the process model used in CMHE, the state estimates accuracy increases. Analytical gradient vectors and Hessian matrices are supplied to the CMHE/CMPC pair to further reduce computation expenses. We present case studies on a nonlinear CSTR system to show the improvement in computational efficiency with the proposed CMHE/CMPC pair.

Original languageEnglish (US)
Title of host publication2019 18th European Control Conference, ECC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3152-3158
Number of pages7
ISBN (Electronic)9783907144008
DOIs
StatePublished - Jun 1 2019
Event18th European Control Conference, ECC 2019 - Naples, Italy
Duration: Jun 25 2019Jun 28 2019

Publication series

Name2019 18th European Control Conference, ECC 2019

Conference

Conference18th European Control Conference, ECC 2019
CountryItaly
CityNaples
Period6/25/196/28/19

Fingerprint

Output Feedback Control
Model predictive control
Model Predictive Control
feedback control
Pairing
Feedback control
horizon
Horizon
output
Approximation
Computational efficiency
approximation
Hessian matrices
Nonlinear systems
optimal control
estimates
nonlinear systems
Gradient vector
functionals
Dynamic Optimization Problems

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Control and Optimization

Cite this

Fang, Y., & Armaou, A. (2019). Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control. In 2019 18th European Control Conference, ECC 2019 (pp. 3152-3158). [8795820] (2019 18th European Control Conference, ECC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ECC.2019.8795820
Fang, Yizhou ; Armaou, Antonios. / Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control. 2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 3152-3158 (2019 18th European Control Conference, ECC 2019).
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Fang, Y & Armaou, A 2019, Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control. in 2019 18th European Control Conference, ECC 2019., 8795820, 2019 18th European Control Conference, ECC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 3152-3158, 18th European Control Conference, ECC 2019, Naples, Italy, 6/25/19. https://doi.org/10.23919/ECC.2019.8795820

Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control. / Fang, Yizhou; Armaou, Antonios.

2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 3152-3158 8795820 (2019 18th European Control Conference, ECC 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Fang Y, Armaou A. Pairing moving horizon estimation and model predictive control via carleman approximation for output feedback control. In 2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 3152-3158. 8795820. (2019 18th European Control Conference, ECC 2019). https://doi.org/10.23919/ECC.2019.8795820