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Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults

Author

Listed:
  • Da Xue

    (Department of Chemical Engineering, University of California, Davis, CA 95616, USA)

  • Nael H. El-Farra

    (Department of Chemical Engineering, University of California, Davis, CA 95616, USA)

Abstract

This paper addresses the problem of fault-tolerant stabilization of nonlinear processes subject to input constraints, control actuator faults and limited sensor–controller communication. A fault-tolerant Lyapunov-based model predictive control (MPC) formulation that enforces the fault-tolerant stabilization objective with reduced sensor–controller communication needs is developed. In the proposed formulation, the control action is obtained through the online solution of a finite-horizon optimal control problem based on an uncertain model of the plant. The optimization problem is solved in a receding horizon fashion subject to appropriate Lyapunov-based stability constraints which are designed to ensure that the desired stability and performance properties of the closed-loop system are met in the presence of faults. The state-space region where fault-tolerant stabilization is guaranteed is explicitly characterized in terms of the fault magnitude, the size of the plant-model mismatch and the choice of controller design parameters. To achieve the control objective with minimal sensor–controller communication, a forecast-triggered communication strategy is developed to determine when sensor–controller communication can be suspended and when it should be restored. In this strategy, transmission of the sensor measurement at a given sampling time over the sensor–controller communication channel to update the model state in the predictive controller is triggered only when the Lyapunov function or its time-derivative are forecasted to breach certain thresholds over the next sampling interval. The communication-triggering thresholds are derived from a Lyapunov stability analysis and are explicitly parameterized in terms of the fault size and a suitable fault accommodation parameter. Based on this characterization, fault accommodation strategies that guarantee closed-loop stability while simultaneously optimizing control and communication system resources are devised. Finally, a simulation case study involving a chemical process example is presented to illustrate the implementation and evaluate the efficacy of the developed fault-tolerant MPC formulation.

Suggested Citation

  • Da Xue & Nael H. El-Farra, 2018. "Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults," Mathematics, MDPI, vol. 6(6), pages 1-20, June.
  • Handle: RePEc:gam:jmathe:v:6:y:2018:i:6:p:104-:d:153346
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    References listed on IDEAS

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    1. Allen, James T. & El-Farra, Nael H., 2017. "A model-based framework for fault estimation and accommodation applied to distributed energy resources," Renewable Energy, Elsevier, vol. 100(C), pages 35-43.
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