Robust tuning procedures of dead-time compensating controllers

This paper describes tuning procedures for dead-time compensating controllers (DTC). Both stable and integrating processes are considered. Simple experiments are performed to obtain process models as well as bounds on the allowable bandwidth for stability. The DTC's used have few parameters with clear physical interpretation so that manual tuning is possible. Furthermore, it is shown how the DTC's can be made robust towards dead-time variations. </p

Microalgae production and maintenance optimization via mixed-integer model predictive control

This paper studies the joint production and maintenance scheduling in microalgae manufacturing systems comprised of multiple machines, which are subject to coupled production demand agreements and operational maintenance constraints. Namely, there are some microalgae production demands to be met over a given horizon, and the maintenance of each microalgae manufacturing unit must be done before a given deadline. Moreover, the number of units whose maintenance can be done simultaneously over the same day is limited, and the units that undergo maintenance cannot contribute to microalgae production during their maintenance day. To solve the considered problem, we design a mixed-integer nonlinear model predictive controller, which is implemented in two optimization stages. The former regards a mixed-integer model predictive control problem, while the latter considers a nonlinear model predictive control problem. The proposed approach allows us to decouple the mixed-integer and nonlinear parts of the whole problem, and thus provides more flexibility on the optimization solvers that can be employed. In addition, the first stage also evaluates the attainability of the demand agreements, and provides a mechanism to minimally adjust such constraints so that their satisfaction can be guaranteed at the second stage. The overall model predictive control approach is based on experimental data collected at VAXA Technologies Ltd., and the effectiveness of the proposed method is validated through numerical simulations including multiple manufacturing units and uncertainties.Juan Martinez-Piazuelo gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of his predoctoral grant FPI-UPC. In addition, the authors would like to thank VAXA Technologies Ltd. as well as the project PID2020-115905RB-C21 (L-BEST) funded by MCIN/ AEI /10.13039/501100011033 for supporting this research.Peer ReviewedPostprint (published version

Dead-Time Compensation and Performance Monitoring in Process Control

The thesis contains two parts, dead-time compensation and performance monitoring. The first part on dead-time compensation is about robust tuning procedures for dead-time compensating controllers (DTC). Both stable and integrating processes are considered. Simple experiments are performed to obtain process models as well as bounds on the allowable bandwidth for stability. The DTCs used have few parameters with clear physical interpretation so that manual tuning is possible. In the second part on dead-time compensation the performance of PID controllers is compared to the performance of DTCs. The aim is to answer the question: ``When can a simple dead-time compensator be expected to perform better than a PID?''. The performance criterion used is the integrated absolute error (IAE). It is compared for PI and PID controllers and a simple dead-time compensator (DTC) when a step load disturbance is applied at the plant input. The topic of the second part of the thesis is performance monitoring of lambda-tuned feedback controllers. A lambda tuned loop is a loop with an one-degree-of freedom controller whose set point response is of first order plus dead time. Lambda is the time constant of the set-point response. For these loops a non intrusive performance monitoring methods is described which is thought to be a first indicator of bad performance after which existing diagnosis algorithms could be applied. For online implementation in distributed control systems a simple recursive algorithm to estimate the index is presented. All parameters of the monitoring method are set by using the lambda tuning. The method applies equally to stochastic or deterministic disturbances. Finally an algorithm to estimate a synthetic gradient of a quadratic cost function is presented. It is demonstrated that the gradient can provide valuable information for maintenance of controllers as the gradient gives information about the disturbances affecting the loop

Performance monitoring of PI controllers using a synthetic gradient of a quadratic cost function

The paper shows how a synthetic gradient of a quadratic cost functioncan be used to monitor performance. The method requires a model of theclosed loop system. In the current paper this is obtained from therecommended tuning rule. The tuning rule requires a simple model of theprocess.The method is non-invasive, only closed loopdata from normal operation is used. By monitoring the gradient, information aboutthe state of the loop is obtained

A synthesis method for robust PID controllers for a class of uncertain systems

PID controller design is considered where optimal controllerparametersare found with constraint on maximum sensitivity and robustness withregard to a cone bounded static nonlinearity acting in feedback withpart of the plant. Thedesign procedure has been successfully applied in the synthesis of acontroller for an Anti-lock Braking System (ABS)

Closed-loop performance monitoring using loop tuning

In this article it is shown how the tuning of a loop is used to commission a closed-loop performance monitoring method. The extended prediction horizon index is used to monitor disturbance rejection properties expressed with the impulse response. The impulse response is obtained from the tuning of the loop. All parameters of the monitoring method are set by using the impulse response. The presented method works equally well when disturbances are stochastic or deterministic. It is shown how typical performance problems are detected by the method. Simple rules of thumb to commission the method for lambda-tuned loops are given. Finally an industrial evaluation is presented for 18 lambda-tuned loops from a pulp and paper mill

On a synthesis method for robust PID controllers for a class of uncertainties

PID controller design is considered where optimal controller parametersare found with constraint on maximum sensitivity and robustness withregard to cone bounded static nonlinearity acting on the plant

Robust tuning procedures of dead-time conpensating controllers

This paper describes tuning procedures for dead-time compensating controllers (DTC). Both stable and integrating processes are considered. Simple experiments are performed to obtain process models as well as bounds on the allowable bandwidth for stability. The DTC's used have few parameters with clear physical interpretation so that manual tuning is possible. Furthermore, it is shown how the DTC's can be made robust towards dead-time variations

Performance comparison between PID and dead-time compensating controllers

This paper is intended to answer the question: “When is a simple dead-time compensator expected to perform better than a PID?”. The performance criterion used is the integrated absolute error (IAE). It is compared for PI and PID controllers and a simple dead-time compensator (DTC) when a step load disturbance is applied at the plant input. Both stable and integrating processes are considered. For a fair comparison the controllers should provide equal robustness in some sense. Here, as a measure of robustness, the maximum of the absolute value of the sensitivity function is used. Since this is not a sufficient measure of robustness when errors in the dead time are considered, performance of the DTC's is given also as a function of dead-time margin (DM) where appropriate

Robust automatic tuning of an industrial PI controller for dead-time systems

This paper describes an automatic tuning procedure for dead-time compensating controllers. A first order plus dead time model is identified from two step response experiments. The identification is based on the methods of moments. The model uncertainty is estimated automatically and used in the design to obtain a robust controller