The aim of the thesis is to improve the control quality of the adaptive systems (Self Tuning Controllers). The thesis mainly deals with problematical identification part of the adaptive system. This part demonstrates a weak point for existing adaptive systems. Paradoxically, the quality of the adaptive system depends mainly on the identification part because on the basis of the process model obtained by identification are worked out parameters of a control part, afterwards the control action plan is established. Knowledge of the modern control methods is used and a new identification algorithm for closed loop identification is proposed. This simple, fast and efficient algorithm overcomes all disadvantages of current classical identification methods based on least mean-square algorithms. The possibility of the choice of a short sample time, one tuning parameter ability to adjust the control process, the ability to identify processes in real use belong to its main goals. This algorithm was built in the adaptive system and then it was tested on a set of simulation and real models with surprisingly excellent results. The successful implementation of the algorithm into the programmable logic controller was also realized. One part of the thesis introduces a new universal graphics environment for testing and verifying control algorithms.

The electrification era has been marked up by an increase in volume of electric vehicles which are directly or indirectly powered by electricity. Railways, roadways and airways are being electrified as we speak at their own respective rate. In addition to that upcoming concepts for transport solution such as hyperloop also described as the fifth mode of transportation will be electrified. The current thesis work is based on developing the model and control of the propulsion system of a scaled Hyperloop pod designed by student team KTH Hyperloop representing KTH. The team competes in Hyperloop competition organized by Spacex and the goal is to achieve the highest possible speed in a given distance and track designed by SpaceX. In order to achieve the goal of being the fastest, the scaled pod uses a Double Sided Linear Induction Motor (DSLIM) as mentioned in the subsequent chapter. The motor modelling is done on Simulink and is similar to a rotary induction motor (RIM). However the presence of end effect in DSLIM makes it different from RIM and has been discussed subsequently. The control strategy uses a synchronous frame PI control for the current control and sensor based speed control for controlling the speed of the pod.The speed control output is a reference current which is used as an input to the current controller which finally gives voltage as the control output. The corresponding bandwidth for the various loops have been calculated based on motor parameters as discussed in the method section. The validation of the motor model and the corresponding controller has been discussed in the result section, where the accuracy of the controller for the designed modelled is discussed. / Elektrifieringstiden har präglats av en ökning i volym av elfordon som direkt eller indirekt drivs med el. Järnvägar, vägar och luftvägar elektrifieras just nu med deras respektive takt. Utöver det kommer kommande koncept för transportlösning som hyperloop som också beskrivs som det femte transportsättet att elektrifieras. Detta examensarbete bygger på att utveckla modellen och regleringen av framdrivningssystemet för en nedskalad Hyperloop-pod utvecklad av studentteamet KTH Hyperloop som representerar KTH. Teamet tävlar i Hyperloop-tävlingen organiserad av SpaceX och målet är att uppnå högsta möjliga hastighet på ett visst avstånd och spår framtaget av SpaceX. För att uppnå målet om att vara snabbast använder den nedskalade podden en dubbelsidig elektrisk linjär induktionsmotor (DSLIM) som nämns i det följande kapitlet. Den elektriska motormodelleringen görs i Simulink och liknar en roterande induktionsmotor(RIM). Men närvaron av ’end effect’ i DSLIM gör den annorlunda än RIM och har diskuterats därefter. Styrstrategin använder en synkron ram-PI-styrning för strömstyrning och sensorbaserad hastighetsreglering för att styra hastigheten på podden. Varvtalsstyrningsutgången är en referensström som används som en ingång till den nuvarande styrenheten som slutligen ger spänning som slutling styrning. Motsvarande bandbredd för de olika slingorna har beräknats baserat på elektriska motorparametrar som diskuterats i metodavsnittet.Valideringen av elmotormodellen och motsvarande styrenhet har diskuterats i resultatsektionen, där noggrannheten hos styrenheten för den konstruerade modellerna diskuteras.

thermal manikin, thermophysiological model, thermal comfort, climatic chamber, clothing thermal resistence