Search

This article discusses the tracking control problem of full-state constrained nonlinear systems with unknown time-varying powers. With the help of a nonlinear state-dependent transformation, by introducing lower and higher powers in control design and skillfully combining the adding a power integrator method with the dynamic gain method, a full-state constrained tracking control design is developed without frequently used feasibility conditions. It is rigorously proved that all the signals of the closed-loop system are bounded, full-state constraints are not violated, and the tracking error converges to a compact set around the origin in a finite-time. [ABSTRACT FROM AUTHOR]

This article studies full-state constrained control for high-order nonlinear systems with unknown multiple time-varying powers and serious parameter unknowns. Due to the simultaneous existence of unknown powers and full-state constraints, we construct a log-type quadratic barrier Lyapunov function (BLF) rather than a quadratic Lyapunov function. By skillfully combining the log-type BLF, adding a power integrator technique and adaptive technique, an adaptive state feedback controller is developed. Under feasibility conditions, which are provided as sufficient conditions for the existence of proposed full-state constrained control, it is proved that all the signals of the closed-loop system are bounded, original system states converge to zero and full-state constraints are not violated. [ABSTRACT FROM AUTHOR]

In this article, tracking control is considered for a class of uncertain multi-input–multi-output (MIMO) nonlinear systems, where the time-varying parameters, the time-varying control coefficient and the time-varying disturbance are assumed to be unknown but to be bounded. Three stable adaptive tracking schemes for a given reference signal are proposed by devising different control algorithms. In the first scheme, bounded-error tracking is achieved in the sense that the tracking error converges exponentially to an adjustable region around the origin, where the $\sigma $ -modification adaptive laws are used to ensure the boundedness of all closed-loop signals. In the second scheme, asymptotic tracking is obtained in the sense that the tracking error converges to zero asymptotically, where the strictly positive and integral functions are employed in the control law to ensure the signal boundedness and zero-error tracking. In the third scheme, exponential tracking is gotten in the sense that the tracking error exponentially converges to zero with a given convergence speed, where exponential functions are incorporated into control law and adaptive laws to ensure system stability and the faster convergence. Three adaptive tracking schemes are, respectively, applied to nonlinear chaotic Chua’s circuit with control inputs. The parametric model is developed for Chua’s circuit with uncertain parameters and external disturbances. The effectiveness of the proposed control algorithms is demonstrated by comparative simulation studies. [ABSTRACT FROM AUTHOR]

In this paper, for uncertain nonlinear systems with time-varying full state constraints, input saturation and unknown control direction, time-varying asymmetric barrier Lyapunov functions, the auxiliary subsystem, and the Nussbaum gain technique are employed. It is shown that all the closed-loop signals are bounded in the semi-global sense, error signals converge to bounded compact sets, and time-varying full state constraints and input saturation are not violated. [ABSTRACT FROM AUTHOR]