Jaime A. Moreno

Learn More
In this paper a strong Lyapunov function is obtained, for the first time, for the supertwisting algorithm, an important class of second order sliding modes (SOSM). This algorithm is widely used in the sliding modes literature to design controllers, observers and exact differentiators. The introduction of a Lyapunov function allows not only to study more(More)
A method to construct a family of strict Lyapunov functions, i.e., with negative definite derivative, for the super-twisting algorithm, without or with perturbations, is provided. This second order sliding modes algorithm is widely used to design controllers, observers and exact differentiators. The proposed Lyapunov functions ascertain finite time(More)
An arbitrary order differentiator that, in the absence of noise, converges to the true derivatives of the signal after a finite time independent of the initial differentiator error is presented. The only assumption on a signal to be differentiated (n−1)-times is that its n-th derivative is uniformly bounded by a known constant. The proposed differentiator(More)
In this paper a novel, Lyapunov-based, variable-gain supertwisting algorithm is proposed. It ensures for linear time invariant systems the global, finite-time convergence to the desired sliding surface, when the matched perturbations/uncertainties are Lipschitz-continuous functions of time, that are bounded, together with their derivatives, by known(More)
A novel adaptive-gain twist sliding mode controller is proposed. The disturbance term is assumed to be bounded with unknown bounds. The proposed Lyapunov-based approach consists in using dynamically adaptive control gains that ensure the establishment, in finite time, of a real second order sliding mode. Also the adaptation algorithm doesn’t overestimate(More)