Abstract:SUMMARYThis paper addresses the problem of controlling a linear system subject to actuator saturations and to L 2 -bounded disturbances. Linear matrix inequality (LMI) conditions are proposed to design a state feedback gain in order to satisfy the closed-loop input-to-state stability (ISS) and the closed-loop finite gain L 2 stability. By considering a quadratic candidate Lyapunov function, two particular tools are used to derive the LMI conditions: a modified sector condition, which encompasses the classical … Show more
“…As a second example, we consider an unstable F-8 aircraft MIMO example borrowed from [4], given by: To evaluate the degree of conservatism of the sets S0(Pan) and S0(Psynan) in which the trajectories are uniformly ultimately bounded, the time-evolution of x ′ Panx (solid line, associated to the control gain Kan) and x ′ Psynanx (dashed line, associated to the control gain Ksyn) are plotted in Figure 6. They show that, once the trajectory enters the ellipsoidal set S0(P ), i.e.…”
Abstract-This paper deals with the stability analysis and stabilization of linear systems with backlash in the input. Uniform ultimate boundedness stability and stabilization problems are tackled allowing to characterize suitable regions of the state space in which the closedloop trajectories can be captured. In the state feedback control design, computational oriented solutions are derived to solve suboptimal convex optimization problems able to give a constructive solution.
“…As a second example, we consider an unstable F-8 aircraft MIMO example borrowed from [4], given by: To evaluate the degree of conservatism of the sets S0(Pan) and S0(Psynan) in which the trajectories are uniformly ultimately bounded, the time-evolution of x ′ Panx (solid line, associated to the control gain Kan) and x ′ Psynanx (dashed line, associated to the control gain Ksyn) are plotted in Figure 6. They show that, once the trajectory enters the ellipsoidal set S0(P ), i.e.…”
Abstract-This paper deals with the stability analysis and stabilization of linear systems with backlash in the input. Uniform ultimate boundedness stability and stabilization problems are tackled allowing to characterize suitable regions of the state space in which the closedloop trajectories can be captured. In the state feedback control design, computational oriented solutions are derived to solve suboptimal convex optimization problems able to give a constructive solution.
“…Semiglobale Ergebnisse wurden in [125,127,163] publiziert. Lokale Stabilität des Ursprungs garantieren die Reglerentwürfe [31,74,91,93]. Durch eine Modifikation des Regelgesetzes können auch andere Ruhelagen stabilisiert werden [19,104,106].…”
Section: Ein Unendlich Großes Einzugsgebietunclassified
“…Der in [31] vorgestellte Zustandsreglerentwurf gibt hinreichende Bedingungen für die Matrix K in Form linearer Matrixungleichungen an, die obige Anforderungen sicherstellen. Die Grundidee ist, das Gebiet G u durch eine Höhenlinie der quadratischen Ljapunov-Funktion …”
Section: Parametrierung Der Anti-windup-matrixunclassified
“…dass die Realteile der Eigenwerte von A s − B s,u K kleiner als −λ sind [31]. Der Zustandsreglerentwurf lässt sich folglich als konvexes Optimierungsproblem formulieren.…”
Section: Satz 92 (Nach [31]) Gegeben Sei Das Systeṁunclassified
“…The analysis and synthesis problems for the deterministic linear systems with actuator saturation have been widely studied (see, e.g., [7][8][9][10][11][12][13][14][15][16], and the references therein). Hu et al [14,15] presented a new method to deal with the saturation nonlinearity, i.e., placing the saturation function into a convex hull.…”
The design of robust H-infinity controller for uncertain discrete-time Markovian jump systems with actuator saturation is addressed in this paper. The parameter uncertainties are assumed to be norm-bounded. Linear matrix inequality (LMI) conditions are proposed to design a set of controllers in order to satisfy the closed-loop local stability and closed-loop H-infinity performance. Using an LMI approach, a set of state feedback gains is constructed such that the set of admissible initial conditions is enlarged and formulated through solving an optimization problem. A numerical example is given to illustrate the effectiveness of the proposed methods.
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