Bosso, Alessandro
  
(2020)
Advanced Computational-Effective Control and Observation Schemes for Constrained Nonlinear Systems, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. 
 Dottorato di ricerca in 
Ingegneria biomedica, elettrica e dei sistemi, 32 Ciclo. DOI 10.6092/unibo/amsdottorato/9428.
  
 
  
  
        
        
        
  
  
  
  
  
  
  
    
  
    
      Documenti full-text disponibili:
      
    
  
  
    
      Abstract
      Constraints are one of the most common challenges that must be faced in control systems design. The sources of constraints in engineering applications are several, ranging from actuator saturations to safety restrictions, from imposed operating conditions to trajectory limitations. Their presence cannot be avoided, and their importance grows even more in high performance or hazardous applications. As a consequence, a common strategy to mitigate their negative effect is to oversize the components. This conservative choice could be largely avoided if the controller was designed taking all limitations into account. Similarly, neglecting the constraints in system estimation often leads to suboptimal solutions, which in turn may negatively affect the control effectiveness. Therefore, with the idea of taking a step further towards reliable and sustainable engineering solutions, based on more conscious use of the plants' dynamics, we decide to address in this thesis two fundamental challenges related to constrained control and observation.
In the first part of this work, we consider the control of uncertain nonlinear systems with input and state constraints, for which a general approach remains elusive.
In this context, we propose a novel closed-form solution based on Explicit Reference Governors and Barrier Lyapunov Functions. Notably, it is shown that adaptive strategies can be embedded in the constrained controller design, thus handling parametric uncertainties that often hinder the resulting performance of constraint-aware techniques.
The second part of the thesis deals with the global observation of dynamical systems subject to topological constraints, such as those evolving on Lie groups or homogeneous spaces. Here, general observability analysis tools are overviewed, and the problem of sensorless control of permanent magnets electrical machines is presented as a case of study. Through simulation and experimental results, we demonstrate that the proposed formalism leads to high control performance and simple implementation in embedded digital controllers.
     
    
      Abstract
      Constraints are one of the most common challenges that must be faced in control systems design. The sources of constraints in engineering applications are several, ranging from actuator saturations to safety restrictions, from imposed operating conditions to trajectory limitations. Their presence cannot be avoided, and their importance grows even more in high performance or hazardous applications. As a consequence, a common strategy to mitigate their negative effect is to oversize the components. This conservative choice could be largely avoided if the controller was designed taking all limitations into account. Similarly, neglecting the constraints in system estimation often leads to suboptimal solutions, which in turn may negatively affect the control effectiveness. Therefore, with the idea of taking a step further towards reliable and sustainable engineering solutions, based on more conscious use of the plants' dynamics, we decide to address in this thesis two fundamental challenges related to constrained control and observation.
In the first part of this work, we consider the control of uncertain nonlinear systems with input and state constraints, for which a general approach remains elusive.
In this context, we propose a novel closed-form solution based on Explicit Reference Governors and Barrier Lyapunov Functions. Notably, it is shown that adaptive strategies can be embedded in the constrained controller design, thus handling parametric uncertainties that often hinder the resulting performance of constraint-aware techniques.
The second part of the thesis deals with the global observation of dynamical systems subject to topological constraints, such as those evolving on Lie groups or homogeneous spaces. Here, general observability analysis tools are overviewed, and the problem of sensorless control of permanent magnets electrical machines is presented as a case of study. Through simulation and experimental results, we demonstrate that the proposed formalism leads to high control performance and simple implementation in embedded digital controllers.
     
  
  
    
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Bosso, Alessandro
          
        
      
        
          Supervisore
          
          
        
      
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          32
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Nonlinear Control, Adaptive Control, Constrained Control, Sensorless Observers, Electric Drives, Barrier Lyapunov Functions, Time-Varying Systems
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.6092/unibo/amsdottorato/9428
          
        
      
        
          Data di discussione
          31 Marzo 2020
          
        
      
      URI
      
      
     
   
  
    Altri metadati
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Bosso, Alessandro
          
        
      
        
          Supervisore
          
          
        
      
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          32
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          Nonlinear Control, Adaptive Control, Constrained Control, Sensorless Observers, Electric Drives, Barrier Lyapunov Functions, Time-Varying Systems
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.6092/unibo/amsdottorato/9428
          
        
      
        
          Data di discussione
          31 Marzo 2020
          
        
      
      URI
      
      
     
   
  
  
  
  
  
    
    Statistica sui download
    
    
  
  
    
      Gestione del documento: 
      
        