An Adaptive PPI Controller

Processes with long dead times are among the most difficult to control. This has urged the development of controllers that cope with this kind of delays. A possible approach is to use a model predictive controller, i.e. a controller with an internal model of the process and its dead time. In ABB’s new control system, Control IT, there exists such a controller, namely the PPI controller. PPI stands for Predictive PI, and as the name indicates it shares some of its features with the common PI controller. The system contains an auto-tuner that is able to detect long dead times and to design a PPI controller. Another feature of Control IT is adaptive control. An adaptive controller has the ability to change its parameters in order to optimize its performance. Today, there is no adaptation mechanism for the PPI controller. This thesis investigates the possibilities of an adaptive version of the PPI controller. A test version has been implemented and simulation results show that there are processes that would benefit from an adaptive PPI. The big flaw is however that adaptation is possible only at set point changes, an event that might not be that common in industry. This implies that industrial studies must be performed before the solution is included in the final product. Other problems that have been encountered are sensitivity to noise and ramped set point changes. It has also been shown that the existing auto-tuner sometimes chooses a PPI design in cases were a PID design would be more useful. The thesis further discusses the subject of switching controller structure while in adaptation mod

Identification and energy optimization of supercritical carbon dioxide batch extraction

Abstract. The emergence of green chemistry, aiming to increase ecological and energy efficiency of processes, has gained supercritical fluid extraction increasing amounts of prominence. Traditional extraction methods utilize hazardous chemicals, have low extractive yield in relation to energy consumption, and produce large amounts of organic waste. Supercritical fluid extraction offers improvements to these challenges in the form of reduced processing energy inputs and an alternative solvent approach. Carbon dioxide is the most commonly employed solvent in supercritical fluid extraction due to the many advantages it brings over other solvents including price, smaller environmental and health risks, and simple separation. The research on data-driven system identification and advanced process control of supercritical extraction has been very scarce. According to past research, the control of supercritical is mostly carried out using basic, non-model-based control schemes. Challenges such as coupling between control loops and nonlinearities of fluid and process dynamics create major challenges for the basic control schemes. With advanced control methods, it could be possible to address these challenges better. Model-based control schemes, in theory, pose many advantages and benefits over basic control, such as improved production economics, optimized product quality and yields, and further possibilities in model-driven research and development. The goal of this thesis was to improve control performance and optimize energy consumption a pilot-scale batch supercritical carbon dioxide extraction process by utilizing model predictive control strategies. The modeling of the unit processes of the target batch extraction was based on measurement data gathered by experimental design and careful examination of the system. The models were utilized in a simulator developed in this study. The arrangement of the implemented experimental design (central composite design, CCD) allowed the exploitation of linear regression analysis; the results of which indicated the existence of possible nonlinearities between steady-state electricity consumption and the operative variables of the process. Model predictive control schemes were developed in a simulator environment for carbon dioxide pressure control, carbon dioxide volumetric flow control, extractor temperature control and separator temperature control. The developed control schemes showed major improvements in control performance of the simulated unit processes, resulting in significant decreases in total electricity and heating water consumptions (up to 25% and 21% respectively). Model predictive control also proved to be quite flexible over the base control system for some processes, providing the possibility of modifying control performance by simple tuning adjustments. The simulated control strategies demonstrate the benefits of model-based control in terms of process energy efficiency and economy. In addition to these results, the identified process and controller models have further potential in future research on control and process developments of supercritical fluid extraction.Ylikriittisen hiilidioksidipanosuuton identifiointi ja energiaoptimointi. Tiivistelmä. Prosessien ekologisuuden ja energiatehokkuuden lisäämiseen tähtäävä vihreä kemia edistää ylikriittisen uuton merkittävyyttä yhä enemmän. Perinteiset erotusmenetelmät käyttävät haitallisia kemikaaleja, niillä on alhainen uuteainesaanto suhteessa energian kulutukseen, ja ne tuottavat suuren määrän orgaanista jätettä. Ylikriittinen uutto tarjoaa parannuksia näihin haasteisiin prosessointienergian kulutuksen vähentymisen ja vaihtoehtoisen liuotinratkaisun muodossa. Hiilidioksidi on yleisimmin käytetty liuotin ylikriittisessä uutossa, koska sillä on monia etuja muihin liuottimiin verrattuna, mukaan lukien hinta, pienemmät ympäristö- ja terveysriskit sekä yksinkertainen erottaminen. Ylikriittiseen uuttoprosessiin liittyvän datapohjaisen identifioinnin ja kehittyneen säädön tutkimus on ollut hyvin vähäistä. Aiempien tutkimusten perusteella ylikriittisen uuton säätö toteutetaan pääasiassa perustason ei-mallipohjaisilla säätörakenteilla. Ohjaussilmukoiden vuorovaikutukset sekä neste- ja prosessidynamiikan epälineaarisuudet luovat suuria haasteita perussäätörakenteille. Kehittyneillä säätömenetelmillä olisi mahdollista käsitellä näitä haasteita paremmin. Mallipohjaiset säätöratkaisut tuovat teoriassa useita etuja ja hyötyjä perussäätöön verrattuna parantuvan tuotantoekonomian, optimoidun tuotelaadun ja -saannon sekä malliperusteisen tutkimuksen ja -kehityksen lisämahdollisuuksien muodossa. Tämän työn tavoitteena oli nostaa pilottikoon ylikriittisen hiilidioksidipanosuuttoprosessin säädön suorituskykyä ja optimoida energiankulutusta hyödyntämällä mallipredikriivisiä säätöstrategioita. Tutkimuksen kohteena olleen panosuuton yksikköprosessien mallinnus perustui koesuunnittelulla kerättyyn mittausaineistoon ja järjestelmän huolelliseen tarkkailuun. Malleja hyödynnettiin työssä kehitetyssä prosessisimulaattorissa. Toteutettu koessunnitelma (central composite design, CCD) mahdollisti lineaarisen regressioanalyysin hyödyntämisen, jonka tulokset osoittivat mahdollisten epälineaarisuuksien olemassaolon prosessin vakaan tilan sähkönkulutuksen ja operatiivisten muuttujien välillä. Malliprediktiiviset säätörakenteet kehitettiin simulaatioympäristössä hiilidioksidin paineen, hiilidioksidin tilavuusvirtauksen, uuttoreaktorin lämpötilan, ja erottajan lämpötilan säädöille. Kehitetyt säätörakenteet toivat suuria säätöparannuksia simuloituihin yksikköprosesseihin, johtaen merkittäviin vähennyksiin käyttösähkön- ja lämmitysveden kulutuksissa (vastaavat vähennykset 25 % ja 21 % saakka). Malliprediktiivinen säätö osoitti myös joustavuutensa perusäätöjärjestelmään verrattuna joissakin prosesseissa, mahdollistaen säätösuorituskyvyn modifioinnin yksinkertaisilla viritysmuutoksilla. Simuloidut säätöstrategiat havainnollistavat mallipohjaisen säädön mahdollisia hyötyjä prosessin energiatehokkuuden ja taloudellisuuden kannalta. Näiden tulosten lisäksi identifioiduilla prosessi- ja säädinmalleilla on lisäpotentiaalia tulevaisuuden ylikriittisen uuton säädön tutkimuksissa ja prosessikehityksissä

Control of Inverse Response Processes by Model Predictive Control (MPC)

Due to the presence of Right Half Plane (RHP) zeros in the system, inverse response processes becomes hard to be identified and controlled. It happens when two separate effects are taking place at the same time but in different direction. Although inverse response problem is not infrequent to occur in industry especially chemical process industry, not many researchers pay attention towards controlling and solving this problem. In this paper, the author aims to compare the performance of the Model Predictive Control (MPC), Proportional Integral Derivative (PID), and Simple Internal Model Control (SIMC) in producing satisfactory control output for inverse response processes. Under this main objective, the author specifies it into three sub objectives. The first one is to design a MPC, PID, and SIMC for typical inverse response process. The second one is to measure the performance of the various controllers for set-point tracking or servo problem and lastly to compare the performance of the designed controllers. To ensure that all the objectives can be accomplished, proper methods need to be set and done throughout the progress of the project. To achieve objective 1, the author will make a proper selection on the type of controller to be used for this project and write the MATLAB coding for the selected controller, MPC, PID, and SIMC. It is crucial to identify the suitable methods and make a proper analysis on the performance of the controller. Three methods, Integral of Absolute Error (IAE), Integral of Squared Error (ISE), and Integral of Time-weighted Absolute Error (ITAE) have been proposed in order to analyse and measure the performance of the designed controller. These methods will be further elaborated in the research methodology part of this paper. And in the end, to attain last objective, the author will compare the results of measurements based on set-point tracking condition. This project principally covers the simulation analysis and project design where the author will accomplish most of the task by using the MATLAB software during the course of this project. In end of this project, the author determines that MPC provides the quickest response compared to PID and SIMC controller other than producing satisfactory overall performance and is suitable to be used to control an inverse response process. Not only that this project can achieve its objective within time constraint, it is also feasible as the project is easily understood and the software that will be used to design the controller is fairly available

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

Robust tuning of a generalized predictor-based controller for integrating and unstable systems with long time-delay

In this work, a general structure to control long time-delay plants is proposed and an easy methodology to tune the control parameters is outlined. All the sensitivity transfer functions are delay free. The proposed scheme is equivalent to the Smith predictor but able to cope with any kind of systems, including nonminimum phase, unstable and integrating plants. The controllers are designed based on the delay free model. Contrary to other approaches, other than for the digital implementation, no delay approximation is used. A tuning parameter is provided in order to reach an intuitive tradeoff between performance and robust stability. A comparative analysis with respect to recently successful proposals shows a substantial improvement in the performance/robustness tradeoff as well as in the tuning process.This work has been partially granted by the Spanish Ministry of Education research Grants DPI2011-28507-C02-01 and PAID-06-12. The authors are also grateful to the Associate Editor and anonymous reviewers for their valuable feedback and comments.García Gil, PJ.; Albertos Pérez, P. (2013). Robust tuning of a generalized predictor-based controller for integrating and unstable systems with long time-delay. Journal of Process Control. 23(8):1205-1216. https://doi.org/10.1016/j.jprocont.2013.07.008S1205121623

Control of a Solar Energy Systems

8th IFAC Symposium on Advanced Control of Chemical ProcessesThe International Federation of Automatic Control Singapore, July 10-13This work deals with the main control problems found in solar power systems and the solutions proposed in literature. The paper first describes the main solar power technologies, its development status and then describes the main challenges encountered when controlling solar power systems. While in other power generating processes, the main source of energy can be manipulated, in solar energy systems, the main source of power which is solar radiation cannot be manipulated and furthermore it changes in a seasonal and on a daily base acting as a disturbance when considering it from a control point of view. Solar plants have all the characteristics needed for using industrial electronics and advanced control strategies able to cope with changing dynamics, nonlinearities and uncertainties.Ministerio de Ciencia e Innovación PI2008-05818Ministerio de Ciencia e Innovación DPI2010-21589-C05-01/04Junta de Andalucía P07-TEP-0272

Process Control & Automation of a Batch Reactor

The development of a split range PID controller with SCADA screens to facilitate manual and automatic control of a pilot plant scale batch reactor is presented in this thesis. Since the characteristics of the system were unknown a step response was obtained from the system and from the experimental results a model of the system was developed and analysed. The PID controller for the system was implemented via an Allen Bradley MicroLogix 1100 Programmable Logic Controller with the human interface for the controller being a SCADA system that was developed using the software package LabVIEW a visual programming language. From the experimental results two models of the system were developed using Simulink a graphical multi domain simulation package. PID controllers were developed for both models using various tuning methods including the Ziegler-Nichols tuning rules; an industry standard method of tuning a PID controller and through rigorous testing and development the controller that produced the best system response was chosen and implemented as the controller for the syste

Testing and implementation of a backlash detection algorithm

Backlash is a well documented and rather common non-linearity which is present in most mechanical and hydraulic systems. The amount of backlash varies depending on the dynamics of the system, for example a gear box in a car needs some space for heat expansion and consequently some amount of backlash in order to function. It is of interest to detect and estimate the amount of backlash automatically, since the time between the manual inspections often is long. This thesis covers the method described in 'Automatic on-line estimation of backlash in control loops' written by Tore Hägglund and published in the Journal of Process Control in January 2007. One of the main objectives of this master thesis is to extend the safety net to guarantee the robustness of the backlash estimation procedure described in the article. The purpose of the safety net is to make sure that backlash estimates are only calculated when the system behavior resembles backlash. Conditions for period time, curve form and setpoint are discussed and investigated. The backlash estimation procedure is implemented as a control module in a prototype library in ABB Control Builder, a software used for PLC programming in an ABB 800xA environment. Finally, industrial field tests are performed to confirm the robustness of the method