Constraints are intrinsic to any dynamical system in control design and addressing them effectively is paramount for ensuring the system’s safety. This chapter delves into the characterization of constraints in nonlinear systems, typically involving state and input constraints as well as derivatives of state and inputs. Pedagogical examples, such as quadcopter and wheeled mobile robots are used to illustrate complex, non-trivial cases, and demonstrate the need for meticulous handling. The chapter covers the application of state feedback controllers with an emphasis on the design and utility of Control Lyapunov functions (CLFs), outlining the steps for computational implementation. Additionally, optimization-based control, saturated control and reference governor are explored as methods for constrained control design, with an analysis of computational complexity and performance efficiency. Theoretical insights are reinforced with practical examples, including the nanodrone and turtlebot, where CLF-based control implementations are applied in both simulation and experimental settings. This chapter offers a hands-on approach supported by foundational tools and methodologies necessary for advancing in constrained control and nonlinear dynamics.
Nonlinear Constrained Control Systems
Blanchini F.;
2025-01-01
Abstract
Constraints are intrinsic to any dynamical system in control design and addressing them effectively is paramount for ensuring the system’s safety. This chapter delves into the characterization of constraints in nonlinear systems, typically involving state and input constraints as well as derivatives of state and inputs. Pedagogical examples, such as quadcopter and wheeled mobile robots are used to illustrate complex, non-trivial cases, and demonstrate the need for meticulous handling. The chapter covers the application of state feedback controllers with an emphasis on the design and utility of Control Lyapunov functions (CLFs), outlining the steps for computational implementation. Additionally, optimization-based control, saturated control and reference governor are explored as methods for constrained control design, with an analysis of computational complexity and performance efficiency. Theoretical insights are reinforced with practical examples, including the nanodrone and turtlebot, where CLF-based control implementations are applied in both simulation and experimental settings. This chapter offers a hands-on approach supported by foundational tools and methodologies necessary for advancing in constrained control and nonlinear dynamics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
