Tito L.M. Santos

Practical MPC with Robust Dead-Time Compensation Applied to a Solar Desalination Plant

Abstract A practical model predictive control (MPC) for solar collector plants is proposed in this paper. By exploiting the non-linear structure of the solar collector model, the optimization problem is posed as a quadratic program similarly to a linear MPC. As applied in some recent publications, a robust dead-time compensation scheme is used to improve robustness. A different state-space interpretation of the robust compensation scheme is also presented. Simulation results including comparisons with other control schemes are shown in order to improve discussions.

Temperature control in a solar collector field using Filtered Dynamic Matrix Control

This paper presents the output temperature control of a solar collector field of a desalinization plant using the Filtered Dynamic Matrix Control (FDMC). The FDMC is a modified controller based on the Dynamic Matrix Control (DMC), a predictive control strategy widely used in industry. In the FDMC, a filter is used in the prediction error, which allows the modification of the robustness and disturbance rejection characteristics of the original algorithm. The implementation and tuning of the FDMC are simple and maintain the advantages of DMC. Several simulation results using a validated model of the solar plant are presented considering different scenarios. The results are also compared to nonlinear control techniques, showing that FDMC, if properly tuned, can yield similar results to more complex control algorithms.

On the prediction error of dead-time compensation control for constrained nonlinear systems

This paper presents a dead-time compensation strategy to control constrained nonlinear systems with single-input delay by using a dead-time free model. Prediction error and disturbance effects are analyzed in order to guarantee input-to-state stability (ISS) and robust constraint satisfaction in the presence of bounded disturbances. It is shown robust constraint satisfaction and ISS are ensured by imposing tighter constraints and a modified ISS condition to the dead-time free model. These modified specifications are derived in terms of a K function description in order to reduce Lipschitz constant conservatism. A numerical comparison based on the CSTR reactor model is presented to illustrate the advantage of the proposed approach.

Unified dead-time compensation structure for SISO processes with multiple dead times

This paper proposes a dead-time compensation structure for processes with multiple dead times. The controller is based on the filtered Smith predictor (FSP) dead-time compensator structure and it is able to control stable, integrating, and unstable processes with multiple input/output dead times. An equivalent model of the process is first computed in order to define the predictor structure. Using this equivalent model, the primary controller and the predictor filter are tuned to obtain an internally stable closed-loop system which also attempts some closed-loop specifications in terms of set-point tracking, disturbance rejection, and robustness. Some simulation case studies are used to illustrate the good properties of the proposed approach.

Unified approach for minimal output dead time compensation in MIMO non-square processes

This paper presents a multivariable dead-time compensating structure for non-square systems with multiple time delays. The proposed strategy compensates the minimal output dead time and it can be used to control stable, integrating, and unstable processes. Additionally, it is shown that simple tuning rules can be used to balance a tradeoff between performance and robustness. Two simulation case studies are presented to show the good properties of the proposed approach and also to compare the obtained solutions with some recent results from the control literature.

Robust design of dead-time compensator controllers for constrained non-linear systems

This paper presents a predictor based approach to design robust controllers for nonlinear dead-time systems. A dead-time compensation structure is proposed for constrained control systems with bounded disturbances and dead-time. It is shown that input-to-state stability (ISS) and constraint satisfaction of the controlled system can be guaranteed if the control law stabilizes (in the ISS sense) an equivalent nonlinear dead-time free system. This result allows the simplification of the controller synthesis which is performed for the dead-time free model of the process. Some simulation results are used to illustrate the performance obtained with the proposed scheme.

Multivariable filtered Smith predictor for systems with sinusoidal disturbances

ABSTRACT This paper presents a new design condition for the multivariable filtered Smith predictor (MFSP) in order to achieve sinusoidal disturbance rejection in steady state. The proposed MFSP strategy is based on a transfer matrix description with multiple delays. A suitable prediction error filter is presented to deal with this new design condition. The proposed design requirement can be used in model predictive controllers with inactive constraints in steady state. Two case studies are used to illustrate the main benefits of the proposed framework.

Explicit input-delay compensation for robustness improvement in MPC

Abstract This paper proposes a filtered Smith predictor (FSP) delay compensation strategy for model predictive control (MPC) robustness improvement. The intrinsic MPC delay compensation is analyzed for a class of systems with a common input-delay to show that robustness can be enhanced by using a different predictor structure. Moreover, FSP robust compensation scheme is applied in a tube based MPC strategy in order to guarantee robust stability. Finally, a simulation example is presented to illustrate the usefulness of the proposed approach.

Robust Model Predictive Controller with Terminal Weighting for Multivariable Dead-Time Processes*

Abstract This paper presents a robust model predictive controller with terminal cost weighting based on a filtered Smith predictor structure. A special state-space representation is applied in order that the states are composed by past control actions and predicted outputs up to the nominal delay. This strategy can be used to control multiple dead-time multivariable processes is such way that: (i) a terminal cost is applied to ensure nominal stability and (ii) the filtered Smith predictor structure is used to improve robustness. The proposed formulation avoids the high order model representation of long dead-time processes. A simulation example is used to illustrate the usefulness of the proposed approach.

Stable MPC with reduced representation for linear systems with multiple input delays

It is well known that MPC recursive feasibility and asymptotic stability is related to the so called stabilizing elements, namely: (i) terminal cost, (ii) terminal stabilizing control law, and terminal constraint. For systems with multiple delays, it is commonly used an augmented representation, which avoid the use of input delays. However, although the augmented description permits an easy inclusion of the stabilizing elements, the control problem dimension could be prohibitively enlarged (mainly from a computational point of view). In this paper it is shown that a stable MPC with enlarged domain of attraction can be easily applied to control open-loop stable systems with multiple input delays by considering the original (reduced) representation. Stabilizing conditions are presented and a modified cost function is proposed in order to avoid the augmented representation. A simulation example is presented to illustrate the simplicity of the proposed approach.