Jakob Rehrl

Temperature control for HVAC systems based on exact linearization and model predictive control

This paper focuses on the controller design for heating, ventilating and air conditioning systems. The proposed model based design technique relies on the method of feedback linearization in combination with model predictive control. The design is based on a simplified model derived from thermodynamic equations. The control loop is evaluated in numerical simulation as well as on an industrial real world system. It is compared to a control technique which uses a state controller with feedback linearization.

Optimized continuous pharmaceutical manufacturing via model-predictive control.

This paper demonstrates the application of model-predictive control to a feeding blending unit used in continuous pharmaceutical manufacturing. The goal of this contribution is, on the one hand, to highlight the advantages of the proposed concept compared to conventional PI-controllers, and, on the other hand, to present a step-by-step guide for controller synthesis. The derivation of the required mathematical plant model is given in detail and all the steps required to develop a model-predictive controller are shown. Compared to conventional concepts, the proposed approach allows to conveniently consider constraints (e.g. mass hold-up in the blender) and offers a straightforward, easy to tune controller setup. The concept is implemented in a simulation environment. In order to realize it on a real system, additional aspects (e.g., state estimation, measurement equipment) will have to be investigated.

RTD Modeling of a Continuous Dry Granulation Process for Process Control and Materials Diversion

Disturbance propagation during continuous manufacturing processes can be predicted by evaluating the residence time distribution (RTD) of the specific unit operations. In this work, a dry granulation process was modelled and four scenarios of feeding events were simulated. We performed characterization of the feeders and developed RTD models for the blender and the roller compactor based on impulse-response measurements via color tracers. Out-of-specification material was defined based on the active pharmaceutical ingredient (API) concentration. We calculated the amount of waste material at various diversion points, considering four feeder-related process-upset scenarios and formulated considerations for the development of a control concept. The developed RTD models allow material tracking of materials that may be used for following the spread contaminants within the process and for batch definition. The results show that RTD modeling is a valuable tool for process development and design, as well as for process monitoring and material tracking.

Sensitivity analysis of a pharmaceutical tablet production process from the control engineering perspective

This paper presents a sensitivity analysis of a pharmaceutical direct compaction process. Sensitivity analysis is an important tool for gaining valuable process insights and designing a process control concept. Examining its results in a systematic manner makes it possible to assign actuating signals to controlled variables. This paper presents mathematical models for individual unit operations, on which the sensitivity analysis is based. Two sensitivity analysis methods are outlined: (i) based on the so-called Sobol indices and (ii) based on the steady-state gains and the frequency response of the proposed plant model.

A Modeling Approach for HVAC Systems Based on the LoLiMoT Algorithm

Abstract In heating ventilating and air conditioning (HVAC) systems, typically two variables (air temperature and air humidity) have to be controlled via several (at least two) actuators. Some of the components show nonlinear behaviour. Therefore, HVAC systems belong to the class of nonlinear multi-input-multi-output systems. A well suited approach to control this class of systems is model predictive control, since the time constants of HVAC systems are high (typically in the range of tens or hundreds of seconds) offering enough time to perform the required online optimization. In order to apply linear predictive control methods, while taking into account the nonlinearities of the plant, a modeling concept based on a physical plant model and a neuro-fuzzy model is proposed. The neuro-fuzzy model is obtained via the so called local linear model tree (LoLiMoT) algorithm. The generation of a linear state space representation from the neuro-fuzzy model is demonstrated. This linear state space model can then be used in a predicitive control scheme, where the linear model is updated each sampling instant from the neuro-fuzzy model. This technique allows the application of standard linear predictive control while taking into account the nonlinearities of the plant. Simulation and measurement results obtained from an industrial test plant are presented.

Model Predictive Control of Temperature and Humidity in Heating, Ventilating and Air Conditioning Systems

The major application of heating, ventilating and air-conditioning (HVAC) systems is the simultaneous control of air temperature and air humidity. Therefore, in a typical industrial HVAC plant the following actuators are available: A cooling coil is used to decrease the air temperature and relative humidity by cooling below the dew point temperature. A steam humidifier is installed to increase the air humidity whereas the air temperature is influenced via a heating coil. Additionally, air temperature and humidity are affected by disturbances acting on the system. These disturbances include outer air temperature and humidity as well as the temperatures of hot water and cool water supply. Consequently, in the setup at hand, a plant with three manipulated inputs, four measurable disturbances and two controlled outputs has to be considered. A predictive control scheme based on a discrete time plant model is presented. The proposed controller computes the manipulated variables by solving an optimization problem at each time step. Simulation and measurement results obtained from an industrial HVAC system are shown.

Analyse und Synthese eines Temperaturregelkreises mit Hilfe der harmonischen Balance (Analysis and Synthesis of a Temperature Control System Using Describing Functions)

Im vorliegenden Aufsatz wird die rechnergestützte Simulation des Temperaturregelkreises einer klimatechnischen Anlage beschrieben. Ziel der Untersuchungen ist es, durch Anwenden der Methode der harmonischen Balance das in realen Anlagen beobachtete Auftreten von unerwünschten Dauerschwingungen mathematisch nachzuweisen und in weiterer Folge durch gezielte Maßnahmen zu verhindern. This article presents the simulation of a temperature control system, which ist part of a real world heating, ventilation and air conditioning (HVAC) system. Based on the describing function method it is possible to design controllers which eliminate undesirable limit cycles.

Residence time distribution of a continuously-operated capsule filling machine: Development of a measurement technique and comparison of three volume-reducing inserts

Graphical abstract Figure. No Caption available. Abstract This paper presents the measurement and analysis of the residence time distribution (RTD) of a tamping‐pin capsule filling machine. The tamping speed and the amount of material inside the powder bowl proved to have a significant effect on the RTD. Various inserts into the powder bowl that reduce the volume and alter mixing and transport in the bowl were experimentally investigated. To obtain the RTD, a tracer‐based measurement method was applied and a sophisticated data processing strategy was developed. The tracer‐based method also allowed investigations of stagnant zones in the powder bowl, another important aspect in continuous manufacturing (CM). The suitability of tracer material was assessed based on a detailed characterization of bulk and tracer material. Characteristic parameters of the RTD were extracted and compared, proposing a systematic strategy for selection of a suitable insert.

Material tracking in a continuous direct capsule-filling process via residence time distribution measurements

Graphical abstract Figure. No Caption available. Abstract Continuous production of pharmaceuticals requires traceability from the raw material to the final dosage form. With that regard, understanding the residence time distribution (RTD) of the whole process and its unit operations is crucial. This work describes a structured approach to characterizing and modelling of RTDs in a continuous blender and a tamping pin capsule filling machine, including insights into data processing. The parametrized RTD models were interconnected to model a continuous direct capsule‐filling process, showing the batch transition as well as the propagation of a 2 min feed disturbance throughout the process. Various control strategies were investigated in‐silico, aiding in the selection of optimal material diversion point to minimize the material waste. Additionally, the RTD models can facilitate process design and optimization. In this work, adaptions to the capsule filling machine were made and their influence on the RTD was examined to achieve an optimal machine setup.

Control of Three Different Continuous Pharmaceutical Manufacturing Processes: Use of Soft Sensors

&NA; One major advantage of continuous pharmaceutical manufacturing over traditional batch manufacturing is the possibility of enhanced in‐process control, reducing out‐of‐specification and waste material by appropriate discharge strategies. The decision on material discharge can be based on the measurement of active pharmaceutical ingredient (API) concentration at specific locations in the production line via process analytic technology (PAT), e.g. near‐infrared (NIR) spectrometers. The implementation of the PAT instruments is associated with monetary investment and the long term operation requires techniques avoiding sensor drifts. Therefore, our paper proposes a soft sensor approach for predicting the API concentration from the feeder data. In addition, this information can be used to detect sensor drift, or serve as a replacement/supplement of specific PAT equipment. The paper presents the experimental determination of the residence time distribution of selected unit operations in three different continuous processing lines (hot melt extrusion, direct compaction, wet granulation). The mathematical models describing the soft sensor are developed and parameterized. Finally, the suggested soft sensor approach is validated on the three mentioned, different continuous processing lines, demonstrating its versatility. Graphical abstract Figure. No caption available.