scispace - formally typeset
Search or ask a question
Author

Rogelio Lozano

Bio: Rogelio Lozano is an academic researcher from University of Technology of Compiègne. The author has contributed to research in topics: Control theory & Adaptive control. The author has an hindex of 58, co-authored 496 publications receiving 14570 citations. Previous affiliations of Rogelio Lozano include University of Illinois at Urbana–Champaign & Instituto Politécnico Nacional.


Papers
More filters
Proceedings ArticleDOI
01 Nov 2011
TL;DR: In this paper, the authors discuss the use of robust control techniques applied to the attitude control of a UAV, when considering uncertainty in the mathematical model of the UAV's attitude.
Abstract: In this paper the modeling and the application of robust control design techniques to the attitude control of a mini-rotorcraft are discussed. More specifically, for controlling attitude, a controller is proposed by applying the robust control technique which is based on an inverse dynamics control law that cancels the mathematical model of the system. The main objective of this paper is to discuss the use of robust control techniques applied to the mini-rotorcraft UAV, when considering uncertainty in the mathematical model. The results are supported by simulation and experimental tests.

1 citations

Book ChapterDOI
01 Jan 2011
TL;DR: This chapter presents strategies for direct adaptive control in a deterministic and in a stochastic environment and the corresponding analysis of adaptive tracking and regulation with independent objectives, adaptive minimum variance control and their extensions.
Abstract: Direct adaptive control covers schemes where the parameters of the controller are directly updated from a signal error (adaption error) reflecting the performance error. The chapter presents strategies for direct adaptive control in a deterministic and in a stochastic environment and the corresponding analysis. This includes adaptive tracking and regulation with independent objectives, adaptive minimum variance control and their extensions. Robustification of direct adaptive control schemes is also discussed.

1 citations

Journal ArticleDOI
TL;DR: In this article , a fuzzy Takagi-Sugeno system was implemented, whose premises were developed using fuzzy C-means to estimate the power required in the different stages of the mission.
Abstract: An essential aspect to achieving safety with a UAV is that it operates within the limits of its capabilities, the available flight time being a key aspect when planning and executing a mission. The flight time will depend on the relationship between the available energy and the energy required by the UAV to complete the mission. This paper addresses the problem of estimating the energy required to perform a mission, for which a fuzzy Takagi–Sugeno system was implemented, whose premises were developed using fuzzy C-means to estimate the power required in the different stages of the mission. The parameters used in the fuzzy C-means algorithm were optimized using particle swarm optimization. On the other hand, an equivalent circuit model of a battery was used, for which fuzzy modeling was employed to determine the relationship between the open-circuit voltage and the state of charge of the battery, which in conjunction with an extended Kalman filter allows determining the battery charge. In addition, we developed a methodology to determine the minimum allowable battery charge level. From this, it is possible to determine the available flight time at the end of a mission defined as the flight time margin. In order to evaluate the developed methodology, a physical experiment was performed using an hexarotor UAV obtaining a maximum prediction error equivalent to the energy required to operate for 7 s, which corresponds to 2% of the total mission time.

1 citations

Journal ArticleDOI
TL;DR: In this article, the authors considered the adaptive control of multivaria-ble discrete time minimum phase systems and proposed an adaptive control design based on pole zero placement, where the a priori knowledge of the plant transfer matrix Hermite form is not necessary, this knowledge is replaced by that of the largest infinite zero order.

1 citations


Cited by
More filters
Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Some open problems are discussed: the constructive use of the delayed inputs, the digital implementation of distributed delays, the control via the delay, and the handling of information related to the delay value.

3,206 citations

Journal ArticleDOI
Arie Levant1
TL;DR: In this article, the authors proposed arbitrary-order robust exact differentiators with finite-time convergence, which can be used to keep accurate a given constraint and feature theoretically-infinite-frequency switching.
Abstract: Being a motion on a discontinuity set of a dynamic system, sliding mode is used to keep accurately a given constraint and features theoretically-infinite-frequency switching. Standard sliding modes provide for finite-time convergence, precise keeping of the constraint and robustness with respect to internal and external disturbances. Yet the relative degree of the constraint has to be 1 and a dangerous chattering effect is possible. Higher-order sliding modes preserve or generalize the main properties of the standard sliding mode and remove the above restrictions. r-Sliding mode realization provides for up to the rth order of sliding precision with respect to the sampling interval compared with the first order of the standard sliding mode. Such controllers require higher-order real-time derivatives of the outputs to be available. The lacking information is achieved by means of proposed arbitrary-order robust exact differentiators with finite-time convergence. These differentiators feature optimal asymptot...

2,954 citations

01 Nov 1981
TL;DR: In this paper, the authors studied the effect of local derivatives on the detection of intensity edges in images, where the local difference of intensities is computed for each pixel in the image.
Abstract: Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

1,829 citations