Nowadays, the interest in Multirotor Unmanned Aerial Vehicles (UAVs) has increased exponentially[5] in various military and civil applications; these activities call for high-level requirements to be fulfilled by the design of high-performance and robust control laws, which usually rely on physical modeling of the system: system identification, which is the science of building mathematical models of dynamical processes from experimental data, play a significant role. Model identification tools are broadly available nowadays. The topic is mature enough to identify models with great certainty. However, the pro- cess is nowhere close to being accessible and requires a lot of care. Experiment design and the input sequence are a whole other topic. Data collection, sensors, and the environment are other requirements that can sometimes be very expensive and out of reach. Time is also an important factor to consider. Thus, the need for a faster and cheaper process, even if it compromises the accuracy, is necessary at least for the prototype stage. Froude Scaling is novel a technique that suggests scaling the dynamics of one multirotor to another. The original paper suggests computing the dimensionless Froude Number as the ratio between a selected dimension of the reference multirotor to the target one. In this research, the uncertain models of 4 multirotors were scaled and analyzed, then compared to the true model through the frequency response and eigenvalue locations. The closed-loop response was also evaluated and analyzed using Robust Control which was optimized using the H∞ synthesis algorithm. The Froude Scaling idea is appealing and interesting, being able to approximate the location of poles/zeros of the model without even running the rotors is powerful. How- ever, the study concludes that the Dimensionless Froude Number cannot be enough to describe the variability between the multirotors. Other factors like the configuration (the way the rotors are set up) and the number of rotors can be of huge effect. It was already concluded[6] that changing the configuration does not change the dynamics, however, it does change the control authority since the number of rotors to perform a task is different. Before trying to scale the dynamics, one needs to understand how the size, number of rotors, and change in configuration may affect the dynamics. Then the models can be scaled based on those factors accordingly.
Al giorno d’oggi, l’interesse per gli Unmanned Aerial Vehicles (UAV) multirotore è aumen- tato esponenzialmente[5] in varie applicazioni militari e civili; queste attività richiedono requisiti di alto livello da soddisfare mediante la progettazione di leggi di controllo robuste e ad alte prestazioni, che di solito si basano sulla modellazione fisica del sistema: la scienza della costruzione di modelli matematici di processi dinamici a partire da dati sperimentali é chiamata "identificazione del sistema" e svolge un ruolo significativo. Gli strumenti di identificazione del modello sono ampiamente disponibili al giorno d’oggi. L’argomento è abbastanza maturo per identificare i modelli con grande certezza. Tuttavia, il pro- cesso non è neanche lontanamente accessibile e richiede molta cura. La progettazione dell’esperimento e la sequenza di input sono altre questioni problematiche. La raccolta dei dati, i sensori e l’ambiente sono altri requisiti che a volte possono essere molto costosi e fuori portata. Anche il tempo è un fattore importante da considerare. Pertanto, c’é la necessità di un processo più rapido ed economico, anche se compromette l’accuratezza, almeno per la fase di prototipazione. Froude Scaling è una nuova tecnica che suggerisce di ridimensionare le dinamiche di un multirotore a un altro. Il documento originale suggerisce di calcolare il numero di Froude adimensionale come il rapporto tra una dimensione selezionata del multirotore di riferimento e quella di destinazione. In questa ricerca, i modelli incerti di 4 multiro- tori sono stati scalati e analizzati, quindi confrontati con il modello reale attraverso la risposta in frequenza e le posizioni degli autovalori. Anche la risposta a circuito chiuso è stata valutata e analizzata utilizzando Robust Control che è stato ottimizzato utilizzando l’algoritmo di sintesi H∞. L’idea di Froude Scaling è allettante e interessante, dato che, essere in grado di ap- prossimare la posizione dei poles/zeros del modello senza nemmeno far funzionare i rotori è potente. Tuttavia, lo studio conclude che il Dimensionless Froude Number non può essere sufficiente per descrivere la variabilità tra i multirotori. Altri fattori come la con- figurazione (il modo in cui sono installati i rotori) e il numero di rotori possono avere un effetto enorme. È già stato concluso[6] che cambiare la configurazione non cambia le dinamiche, tuttavia, cambia l’autorità di controllo poiché il numero di rotori per eseguire un compito è diverso. Prima di provare a scalare le dinamiche, è necessario capire in che modo le dimensioni, il numero di rotori e il cambiamento di configurazione possono influire sulle dinamiche. Di conseguenza i modelli possono essere ridimensionati in base a tali fattori.
Exploring the idea of dynamic scaling using froude scaling technique
SHEFAT, ABDULMALEK SALEM
2021/2022
Abstract
Nowadays, the interest in Multirotor Unmanned Aerial Vehicles (UAVs) has increased exponentially[5] in various military and civil applications; these activities call for high-level requirements to be fulfilled by the design of high-performance and robust control laws, which usually rely on physical modeling of the system: system identification, which is the science of building mathematical models of dynamical processes from experimental data, play a significant role. Model identification tools are broadly available nowadays. The topic is mature enough to identify models with great certainty. However, the pro- cess is nowhere close to being accessible and requires a lot of care. Experiment design and the input sequence are a whole other topic. Data collection, sensors, and the environment are other requirements that can sometimes be very expensive and out of reach. Time is also an important factor to consider. Thus, the need for a faster and cheaper process, even if it compromises the accuracy, is necessary at least for the prototype stage. Froude Scaling is novel a technique that suggests scaling the dynamics of one multirotor to another. The original paper suggests computing the dimensionless Froude Number as the ratio between a selected dimension of the reference multirotor to the target one. In this research, the uncertain models of 4 multirotors were scaled and analyzed, then compared to the true model through the frequency response and eigenvalue locations. The closed-loop response was also evaluated and analyzed using Robust Control which was optimized using the H∞ synthesis algorithm. The Froude Scaling idea is appealing and interesting, being able to approximate the location of poles/zeros of the model without even running the rotors is powerful. How- ever, the study concludes that the Dimensionless Froude Number cannot be enough to describe the variability between the multirotors. Other factors like the configuration (the way the rotors are set up) and the number of rotors can be of huge effect. It was already concluded[6] that changing the configuration does not change the dynamics, however, it does change the control authority since the number of rotors to perform a task is different. Before trying to scale the dynamics, one needs to understand how the size, number of rotors, and change in configuration may affect the dynamics. Then the models can be scaled based on those factors accordingly.File | Dimensione | Formato | |
---|---|---|---|
Malek_Thesina.pdf
accessibile in internet per tutti
Descrizione: Dec 2022
Dimensione
14.23 MB
Formato
Adobe PDF
|
14.23 MB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/198865