Título principal
Control Design for Constrained LTI and LPV Systems via Polyhedral Set Invariance [recurso eletrônico] / Jackson Gonçalves Ernesto ; orientador, Eugênio de Bona Castelan Neto ; coorientador, Eduardo Camponogara
Data de publicação
2024
Descrição física
131 p. : il.
Nota
Disponível somente em versão on-line.
Tese (doutorado) – Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas Florianópolis, 2024.
Inclui referências.
Control Design for Constrained LTI and LPV Systems via Polyhedral Set Invariance [recurso eletrônico] / Jackson Gonçalves Ernesto ; orientador, Eugênio de Bona Castelan Neto ; coorientador, Eduardo Camponogara
Data de publicação
2024
Descrição física
131 p. : il.
Nota
Disponível somente em versão on-line.
Tese (doutorado) – Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas Florianópolis, 2024.
Inclui referências.
Assunto
Engenharia de automação e sistemas
Invariância
Realimentação
Sistema LTI
Sistema LPV
Controle
Responsabilidade
Ernesto, Jackson Gonçalves
Castelan Neto, Eugênio de Bona
Camponogara, Eduardo
Universidade Federal de Santa Catarina. Programa de Pós-Graduação em Engenharia de Automação e Sistemas
Idioma
Inglês
Engenharia de automação e sistemas
Invariância
Realimentação
Sistema LTI
Sistema LPV
Controle
Responsabilidade
Ernesto, Jackson Gonçalves
Castelan Neto, Eugênio de Bona
Camponogara, Eduardo
Universidade Federal de Santa Catarina. Programa de Pós-Graduação em Engenharia de Automação e Sistemas
Idioma
Inglês
Abstract: In this work, set invariance concepts applied to polyhedral sets are used to design stabilizing Output Feedback (OF) control laws for linear time-invariant (LTI) and linear parameter varying (LPV) discrete-time systems. The constrained controlled system may be subject to state, control amplitude, and control-rate constraints, and persistent disturbances. Firstly, we use the Robust Positive Invariance (RPI) property (also called ∆-Invariance) of polyhedral sets to design a stabilizing static Output Feedback (OF) control law for linear discrete-time systems subject to persistent disturbances, assuring the states and control constraints fulfillment. We deduce algebraic conditions to guarantee that any trajectory emanating from the∆-Invariant polyhedron remains in it and converges in finite time to another polyhedral set around the origin, where the trajectory remains ultimately bounded. Thus, the proposed staticOF solution for the constrained control problem also requires determining the∆-invariant and the ultimately bounded polyhedra. Next, we use the joint concepts of Robust Control Invariant (RCI) set and Robust OneStep Controllable sets (ROSC) to obtain a switching output regulator that steers the constrained system’s trajectory to the origin in a certain number of sample periods. A set of static output feedback control gains is computed offline, which later compose the online switching regulator. Then, based on the necessary and sufficient algebraic conditions that describe the polyhedral positive-invariance for LPV systems, we propose an incremental controller design, guaranteeing the regional closed-loop stability and that the control and state constraints are all respected. The proposed incremental output feedback controller feeds back both the measured outputs and control inputs. The constrained control design allows, inparticular, dealing with the control-rate variation bounds through a parameter-varying control law. Additionally, an alternative implementation is proposed, where the state and control constraints build part of the positive invariant set. Moreover, we extend the proposed LPV incremental control law design to deal with bounded persistent disturbances. The proposed algebraic design conditions are translated into bilinear optimization problems. Each Bilinear Problem (BP) considers an objective function that optimizes the polyhedron size in given directions, weighting the size of associated polyhedral sets (when necessary), whose constraints are formed by the robust positive invariance conditions and set inclusions. An efficient non-linear optimization solver (KNITRO) is employed to tackle the present bilinearities through the AMPL language. Furthermore, numerical examples showcase the proposals’ effectiveness and potential.