Optimeringen av PID-parametrarna har varit en utmaning sedan uppfinningen avPID-regulatorer. Många olika optimeringsmetoder har tagits fram sedan 1940-talet,i detta arbete testades och jämfördes Ziegler-Nichols stegsvarmetoden, Lambdametoden och AMIGO-metoden.Målsättningen med detta examensarbete var att kunna utse vilken optimeringsmetodsom lämpade sig bäst för processinstrumenten som designats på avdelningen Custimized Bioprocess Solutions (CBS) på Cytiva. Optimeringsmetoden som utses kommer att föreslås som en som en del i en arbetsprocess att följa när ett system behöveroptimeras.Testerna genomfördes med hjälp av stegsvarsmetoden, där de förinställda PIDparametrarna på ett processinstrument användes som referens. Utifrån tre parametrarmodellen kunde nödvändiga data samlas in, sedan beräknades nya PID-parametrarmed de valda optimeringsmetodernas beräkningsregler. De nya PID-parametrarnaanvändes sedan för att generera nya stegsvar. Slutligen jämfördes de nya stegsvarenmot stegsvaret från de förinställda PID-parametrarna för att kunna utse den mestlämpade optimeringsmetoden.Detta arbete resulterade i slutsatsen att fler tester behöver utföras, men att beräkningsverktyget som användes under examensarbetet skall ingå som en del av den efterfrågade arbetsprocessen. / The optimization of the PID parameters has been a challenge since the invention ofPID controllers. Many different optimization methods have been developed sincethe 1940s, in this work the Ziegler-Nichols step response method, the Lambdamethod and the AMIGO method were tested and compared.The aim of this thesis was to be able to choose which optimization method was bestsuited for process instruments designed at the Custimized Bioprocess Solutions(CBS) department at Cytiva . The optimization method that is chosen will be proposed as part of a work process to follow when a system needs to be optimized.The tests were performed using the step response method, where the preset PID parameters on a system were used as a reference. Based on the three parameters model,the necessary data could be collected, then new PID parameters were calculatedwith the calculation rules of the selected optimization methods. The new PID parameters were then used to generate new step responses. Finally, the new step responses were compared to the step response from the preset PID parameters to designate the most suitable optimization method.This work resulted in the conclusion that more tests need to be performed, but thatthe calculation tool used during the degree project should be included as part of therequested work process.

<p>Today electronics becomes more and more complex and to keep low costs and power consumption, both digital and analog parts are implemented on the same chip. The degree of automization for the digital parts have increased fast and is high, but for the analog parts this has not come through. This have created a big gap between the degrees of automization for the two parts and makes the analog parts the bottleneck in electronics develop. </p><p>Research is ongoing at Electronics systems group at Linköping University target the increase of design automization for analog circuits. An optimizationbased approach for device sizing is developed and for this a good optimization method is needed which can find good solutions and meet the specification parameters. </p><p>This report contains an evaluation of the optimization method Simulated Annealing. Many test runs have been made to find out good control parameters, both for Adaptiv Simulated Annealing (ASA) and a standard Simulated Annealing method. The result is discussed and all the data is in the enclosures. A popular science and mathematical description is given for Simulated Annealing as well.</p>

Today electronics becomes more and more complex and to keep low costs and power consumption, both digital and analog parts are implemented on the same chip. The degree of automization for the digital parts have increased fast and is high, but for the analog parts this has not come through. This have created a big gap between the degrees of automization for the two parts and makes the analog parts the bottleneck in electronics develop. Research is ongoing at Electronics systems group at Linköping University target the increase of design automization for analog circuits. An optimizationbased approach for device sizing is developed and for this a good optimization method is needed which can find good solutions and meet the specification parameters. This report contains an evaluation of the optimization method Simulated Annealing. Many test runs have been made to find out good control parameters, both for Adaptiv Simulated Annealing (ASA) and a standard Simulated Annealing method. The result is discussed and all the data is in the enclosures. A popular science and mathematical description is given for Simulated Annealing as well.