Finn Haugen

State estimation and model-based control of a pilot anaerobic digestion reactor

A state estimator and various model-based control systems have been designed for a real anaerobic digestion (AD) pilot reactor fed with dairy manure. The model used is a modified Hill model which is a relatively simple dynamical AD process model. The state estimator is an Unscented Kalman Filter (UKF) which uses only methane gas flow measurement to update its states. The model and the state estimates are used in different control systems. One of the control systems aims at controlling the methane gas flow to a setpoint. Simulations indicate that the setpoint tracking performance of a predictive control system is considerably better comparing with PI control, while disturbance compensation is not much better. Consequently, assuming the setpoint is constant, the PI controller competes well with the predictive controller. A successful application of predictive control of the real reactor is presented. Also, three different control systems aiming at retaining the reactor at an operating point where the volatile fatty acids (VFA) concentration has a maximum, safe value are designed. A simulation study indicates that the best control solution among the three alternatives is PI control based on feedback from estimated VFA.

A complete programming framework for process control education

This paper presents the programming features that are desirable in Process Simulation and Control Education Software. These programming features facilitate the understanding of the control subject by showing the effect of physical parameters in dynamic systems. These software features also deal with data acquisition through different hardware systems in an effective and simple way. Data acquisition is important not only to bring process variables to the controller, but also for system identification and off-line model-base control design. A complete programming language allows a user to simulate the controller performance, and later implement it. All these tasks are expected to use the same programming framework for smooth transition between design and implementation of a model-based controller. An air heater case study is used to illustrate the importance of having a friendly software/hardware programming framework.

Optimal design and operation of a UASB reactor for dairy cattle manure

Optimal design and operation of a UASB reactor at a dairy farm is determined.Brute force optimization is based on a dynamic AD model and temperature models.Solutions provided are maximum gas flow, minimum volume, and maximum power surplus.The optimal solutions are improved if the biomass retention time is increased. Optimal design and operation of a planned full-scale UASB reactor at a dairy farm are determined using optimization algorithms based on steady state simulations of a dynamic AD process model combined with models of the reactor temperature and heat exchanger temperatures based on energy balances. Available feedstock is 6m3/d dairy manure produced by the herd. Three alternative optimization problems are solved: Maximization of produced methane gas flow, minimization of reactor volume, and maximization of power surplus. Constraints of the optimization problems are an upper limit of the VFA concentration, and an upper limit of the feed rate corresponding to a normal animal waste production at the farm. The most proper optimization problem appears to be minimization of the reactor volume, assuming that the feed rate is fixed at its upper limit and that the VFA concentration is at its upper limit. The optimal result is a power surplus of 49.8MWh/y, a hydraulic retention time of 6.1d, and a reactor temperature of 35.9?C, assuming heat recovery with an heat exchanger, and perfect reactor heat transfer insulation. In general, the optimal solutions are improved if the ratio of the solids (biomass) retention time to the hydraulic retention time is increased.

A Revised View on Teaching Basic Process Control

Abstract A revised view on teaching basic process control for bachelor and master students is presented. Practical topics are emphasized at the expense of a number of traditional theoretical topics. New teaching material in the form of interactive simulators, instructional videos, and a number of identical portable laboratory rigs have increased the pedagocical quality. The main results are an increase of the practical applicability of the course and more content students and instructors.

Implementation of performance indicators for automatic assessment

Abstract Simulator training is widely used in different industries and in academia as a teaching tool. An expert instructor, who guides the users through the learning process with the simulator by giving verbal feedback, pausing the scenarios if necessary, and sometimes by developing certain evaluations, leads the simulation sessions. However, the availability of instructors is not always enough for the training demand, which can slow down the training process, as the trainees often need to wait for the instructor’s feedback before they can proceed with their tasks. This research evaluates the feasibility of combining the guidance of the instructor with an automatic live assessment tool, based on performance indicators, to improve simulator training. Two simulator training sessions were evaluated. The strategy used for the simulation sessions consists of three stages: briefing, simulation and debriefing. During both sessions, it was observed that the assessment tool makes the users aware of the state of the process and in most of the cases helps them to find faster the source of an abnormality in the system. However, further development of the automatic assessment tool is needed in order to require less instructor guidance during the simulator training.