Fault Tolerant Model Predictive Control applied on the Barcelona Sewer Network

Ocampo‐Martínez, Carlos; Puig, Vicenç; Quevedo, Joseba; Ingimundarson, Ari

doi:10.1109/cdc.2005.1582346

Cited by 22 publications

(23 citation statements)

References 7 publications

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“…According to [5], different assumptions can be done for the rain prediction when an optimal/predictive control law is used for the RTC of sewer networks. Results show that the assumption of constant rain over a short prediction horizon gives results that can be compared with the the case of considering known rain over the prediction horizon, confirming similar results reported in [2,21].…”

Section: Mpc Disturbancessupporting

confidence: 84%

Piece-wise linear functions-based model predictive control of large-scale sewage systems

Ocampo‐Martínez

Puig

2010

IET Control Theory &Amp; Applications

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Section: Mpc Disturbancessupporting

confidence: 84%

Piece-wise linear functions-based model predictive control of large-scale sewage systems

Ocampo‐Martínez

Puig

2010

IET Control Theory &Amp; Applications

Self Cite

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“…According to [40], different assumptions can be done for the rain prediction when an optimal control law is used in the RTC of sewer networks. Results show that the assumption of constant rain over a short prediction horizon gives results that can be compared with the assumption of known rain over the considered horizon, confirming similar results reported in [35,41]. In the latter case, matrix A d can be set as an identity matrix of suitable dimensions.…”

Section: 12supporting

confidence: 81%

Fault‐tolerant model predictive control within the hybrid systems framework: Application to sewer networks

Ocampo‐Martínez

Puig

2008

Adaptive Control & Signal

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SUMMARYIn this paper, model predictive control (MPC) problem with fault-tolerance capabilities is formulated within the hybrid systems framework. In particular, the mixed logical dynamic form to represent hybrid systems is considered. Using this approach, a hybrid model of the system to be controlled is obtained, which includes inherent hybrid phenomena and possible modes caused by faults occurrence. This allows to adapt the system model on-line by taking into account the fault information provided by a fault diagnosis and isolation module. In this way, the controller can cope with the considered faults. Additionally, different implementation schemes and fault-tolerance evaluation procedures for hybrid MPC (HMPC) considering fault-tolerance capabilities are proposed and discussed. Finally and in order to exemplify the implementation of the proposed approach, it is applied to include actuator fault tolerance in the design of a HMPC controller for a portion of the sewer network of Barcelona. q

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“…It is hard to get an explicit expression of (26). Therefore, CVaR is usually calculated through discretization.…”

Section: Minimization Of Conditional Value At Risk (Lp-cvar)mentioning

confidence: 99%

“…Model Predictive Control (MPC) is an advanced fault-tolerant control method since it has many benefits arising from its features, such as prediction model [21][22][23], constraints [24][25][26], objective function [23,27], etc. Based on these features, the MPC controller can effectively deal with the influence on a WECS suffering from a fault.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

et al. 2018

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Abstract:Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs), how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC) fault-tolerant controller with the Conditional Value at Risk (CVaR) objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC) problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.

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Fault Tolerant Model Predictive Control applied on the Barcelona Sewer Network

Cited by 22 publications

References 7 publications

Piece-wise linear functions-based model predictive control of large-scale sewage systems

Piece-wise linear functions-based model predictive control of large-scale sewage systems

Fault‐tolerant model predictive control within the hybrid systems framework: Application to sewer networks

Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

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