The aim of this project is to create a modern and advanced program for controlling a vacuum furnace used for brazing plate heat exchangers and which includes functions for remote monitoring. A DAQ-unit (Data Acquisition) made by National Instruments connects with an already existing vacuum furnace to send control signals and receive measurements. There is already a control program available for the vacuum furnace but it has a number of shortcomings which the new program is intended to solve. A PID controller is implemented to control the temperature of the furnace. Temperature control is of utmost importance to get the brazing process as stable as possible. Therefore, a simulator has been developed that simulates the entire brazing process. The simulator serves as a tool to optimize values ​​of the constants included in the PID control algorithm. Everything is written in the C# programming language. The braze process has from a code stand point been divided into five phases; lowering pressure, heating, brazing, cooling and finish. A comparison between the new and the old control software shows that heating process is much faster now and that when the correct temperature level has been reached, the temperature variation is considerably lower than before. The entire soldering process is shortened by almost two hours. Temperature control is more efficient and stable than before because of the constants calculated using the simulator and that a PID controller is used instead of a PD controller. New technology is implemented so that a much larger number of samples are obtained. Functions for user access to the history of previous brazing processes has been developed and an interface to easily adjust settings is implemented. Even a web interface for remote monitoring has been created.

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Material handling and logistics are fundamental parts of today’s global societyand forklifts are a crucial part of the material handling process. Making these asefficient and reliable as possible are therefore of great interest. In this master thesis, an effort has been made to improve the control of the hydraulic lowering function of a specific forklift. Today the lowering function iscontrolled through an open-loop control scheme making the control performancesensitive to disturbances and system changes. One disturbance of special interestis the temperature of the hydraulic fluid. The goal of this thesis was therefore todesign a controller with improved robustness as well as improved performance. To solve this a model-based control design approach was used and a nonlineargrey-box model was derived, implemented and validated. The model parameterswere estimated using a nonlinear least-squares optimisation problem. The resulting model captures most of the system dynamics and the model fit is higher than 70% which was deemed good enough to use for control design. A PID controller was designed based on the estimated model and the controllerparameters were optimised. Furthermore, the controller was evaluated in simulations and implemented in a real forklift. The proposed controller was compared to the original controller for various scenarios. The results reveal improvedsteady state behaviour with enhanced temperature robustness compared to theoriginal controller. / Materialhantering och logistik är viktigt för att dagens globala samhälle ska fungera. En grundläggande del i materialhanteringsprocessen är gaffeltruckar, därför är det av intresse att göra gaffeltruckar så effektiva och pålitliga som möjligt. I det här examensarbetet har ett försök gjorts till att förbättra styrningen av den hydrauliska sänkningsfunktionen hos en specifik gaffeltruck. Dagens lösning använder sig av öppen styrning vilket gör reglerprestandan känslig för störningar och systemförändringar. En störning av extra intresse är temperaturen av hydraulvätskan. Målet med detta arbete var därför att designa en regulator med ökad robusthet och prestanda. För att lösa detta har en modellbaserad metod för regulatordesign använts där en olinjär gray-box modell härleddes, implementerades och validerades. Modellparametrarna skattades genom att ställa upp och lösa ett ickelinjärt minsta-kvadrat optimeringsproblem. Den resulterande modellen fångar det mesta av systemdynamiken och modellpassningen till uppmätt data var högre än 70\% vilket ansågs bra nog för att kunna använda modellen som en bas för regulatordesign. En PID regulator designades och regulatorparametrarna optimerades med hjälp av modellen. Regulatorn utvärderades i simuleringar och för att sedan implementeras den på en riktig gaffeltruck. Den föreslagna regulatorn jämfördes med den ursprungliga regulatorn i flera olika testfall. Resultaten visade ett bättre steady-state beteende och ökad robusthet mot temperaturförändringar för den designade regulatorn jämfört med den ursprungliga regulatorn.

This thesis describes the work done to implement and develop position and trajectory control of a quadcopter. The quadcopter was originally equipped with sensors and software to estimate and control the quadcopter's orientation, but did not estimate the current position. A GPS module, GPS antenna and a LIDAR have been added to measure the position in three dimensions. Filters have been implemented and developed to estimate the position, velocity and acceleration. Four controllers have been designed that use these estimates: one PID controller and one LQ controller for vertical movement, and a position controller and a trajectory controller for horizontal movement. The position controller maintains a constant position, while the trajectory controller maintains a constant velocity while travelling along a straight line. These position and trajectory controllers calculate the reference angles required to direct the thrust necessary to control the quadcopter's movement. Additionally, an algorithm has been developed to decrease overshoot by predicting future trajectories. These controllers have proven to be successful at controlling the quadcopter's position in all three dimensions, both in practice during outdoor flight and in simulations.

The objective of this work is focused on trains and their role in integrated transport systems. The functionality of public train transport is shown on 2 most developped integrated systems in Czech republic. My work include comparison of these 2 systems and the role of trains in both of them.

During this master thesis an adaptive control system for angular velocity was developed. The approach focuses on radio controlled quadrotors and thereby targets a computational efficient solution. The adaptation is divided into two steps. First, an Integral Squared Plus Time Delay (I2PD) model estimation is done through the Recursive Least Squares (RLS) algorithm. Second, control parameters for the quadrotors Proportional Integral Derivative (PID) controller are found by using empirically modified Tuning Rules (TRs) which are based on the I2PD model. Simulation results show the benefits of an adaptive tuning algorithm in regards of the time consuming process of manually tuning a PID controller as well as robustness against both predictable and unpredictable system changes. This includes actuator degradation, battery consumption, changes in weight or inertia etc. However, it is apparent that the tuning algorithm demands an arbitrary initial approximation to be stable at initialization.

The need to save energy, cut costs, and increase profit margin in process manufactureincreases continually. There is also a global drive to reduce energy use and cut down co2 emission and combat climate change. These in turn have led to more stringent requirements on process control performance. Hence, the requirements for modern systems are often not achievable using classical control techniques. Therefore, advanced control strategies are often required to ensure optimal process performance. Despite these challenges, PID has continued to be the dominant industrial control scheme. However, for systems with complex dynamics and/or high performance requirements, PID control may not be sufficient. Therefore, a significant number of industrial control loops are not performing optimally and more advanced control than PID may be required in order to achieve optimal performance. MPC is one of the advanced control schemes that has had a significant impact in the industry. Despite the benefits associated with the implementation of MPC, the technology has remained a niche application in process manufacture. This thesis seeks to address these issues by developing ways that could lead to widespread application of MPC. In the first part of this thesis, a study was carried out to understand the characteristics of processes that would benefit from the application of MPC at the regulatory control level even in the single-input single-output (SISO) case. This is a departure from the common practice in which MPC is applied at the supervisory control layer delivering set points to PID controllers at the regulatory control layer. Both numerical simulation and industrial studies were used to show and quantify benefits of MPC for SISO applications at the regulatory control layer. Some issues that have led to the limited application of MPC include the cost and human efforts associated with modelling and controller design. And to achieve high process performance, accurate models are required. To address this issue, in the second part of this thesis, a novel technique for designing MPC from routine plant data – routine data MPC (RMPC) is proposed. The proposed technique was successfully implemented on process models. This technique would reduce the high human cost associated with MPC deployment, which could make it a widespread rather than niche application in the process manufacturing industry.

In this research, a security architecture based on the feedback control theory has been proposed. The first loop has been designed, developed and tested. The architecture proposes a feedback model with many controllers located at different stages of network. The controller at each stage gives feedback to the one at higher level and a decision about network security is taken. The first loop implemented in this thesis detects one important anomaly of virus attack, rate of outgoing connection. Though there are other anomalies of a virus attack, rate of outgoing connection is an important one to contain the spread. Based on the feedback model, this symptom is fed back and a state model using queuing theory is developed to delay the connections and slow down the rate of outgoing connections. Upon implementation of this model, whenever an infected machine tries to make connections at a speed not considered safe, the controller kicks in and sends those connections to a delay queue. Because of delaying connections, rate of outgoing connections decrease. Also because of delaying, many connections timeout and get dropped, reducing the spread. PID controller is implemented to decide the number of connections going to safe or suspected queue. Multiple controllers can be implemented to control the parameters like delay and timeout. Control theory analysis is performed on the system to test for stability, controllability, observability. Sensitivity analysis is done to find out the sensitivity of the controller to the delay parameter. The first loop implemented gives feedback to the architecture proposed about symptoms of an attack at the node level. A controller needs to be developed to receive information from different controllers and decision about quarantining needs to be made. This research gives the basic information needed for the controller about what is going on at individual nodes of the network. This information can also be used to increase sensitivity of other loops to increase the effectiveness of feedback architecture.

This work addresses the design and real-time implementation of adaptive control strategies on the parabolic solar collector to enhance the production efficiency under varying working conditions. For example, the unpredictable variations of the solar irradiance and thermal losses, these factors can be a major problem in the control design. The control objective is to force the outlet temperature of the collector fluid, to track a predefined reference temperature regardless of the environmental changes. In this work, two control strategies have been designed and analyzed. First, an intelligent proportional-integral feedback control, which combines the proportionalintegral feedback control with an ultra-local model is proposed. This strategy uses a transfer function model that has been derived and identified from real-time data and used to test the controller performance. Second, an adaptive nonlinear control using Lyapunov stability theory combined with the phenomenological representation of the system is introduced. This strategy uses a bilinear model derived from the heat transfer equation. Both control strategies showed good performance in the simulations with respect to the convergence time and tracking accuracy. Besides, the conventional proportional-integral controller has been successfully implemented in the real system.

A plasma arc erosion process can be used to create metal and metal oxide particles in the ultra-fine size range (<70 µm). An electric arc is struck between two metallic electrodes, submerged in water, melting the surface of the electrodes. When the arc collapses a high energy pressure wave strikes the molten surface of the electrode. When the pressure wave strikes the molten metal, small metallic particles are created from the molten metal and are immediately cooled in the water. Previous research developed a process that used a constant current power supply and electrode motion to create ultra-fine particles. This research improves upon previous research by using a pulsed power supply similar to those used in Electrical Discharge Machining (EDM). The pulsed power supply eliminates the need for electrode motion and improves the rate of particle production, provides control over size of the particles created, and reduces the amount of energy needed to produce the particles. The new process improves the maximum particle production rate from 3.6 g/hr to 14 g/hr, provides a method to control the mean diameter of the particles produced, and reduces the amount of energy needed from 200 kWh/kg(previous constant current process) to 10.6 kWh/kg(using the pulsed power supply).