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 …

I and i

Time-delay systems: an overview of some recent advances and open problems

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...

/pdf/higher-order-sliding-modes-differentiation-and-output-438zdzb0ld.pdf

Higher-order sliding modes, differentiation and output-feedback control

Differential-Difference Equations. By Richard Bellman and Kenneth L. Cooke. Pp. xvi, 465. 1963. (Academic Press)

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:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

In this paper, the modeling and control design of a vertical flight attitude control for a mini tail-sitter with variable pitch propeller is discussed. Tail-sitters VTOL-UAVs have operational flexibility of typical helicopters while having the cruise performance of fixed wing airplanes. The configuration proposed in this work is highly unstable in its natural flight state in vertical mode. A dynamic model is developed and a linear control strategy has been developed to stabilize the platform. The results are supported by experimental tests.

/pdf/attitude-stabilization-in-hover-flight-of-a-mini-tail-sitter-5d9u1hchzm.pdf

Attitude stabilization in hover flight of a mini tail-sitter UAV with variable pitch propeller

Stabilization of the Furuta Pendulum Around Its Homoclinic Orbit

Brief Adaptive control for linear slowly time-varying systems using direct least-squares estimation

Technical Communique: PD control of robot manipulators with joint flexibility, actuators dynamics and friction

The aim of this paper is to present a configuration for a Convertible Unmanned Aerial Vehicle, which incorporates the advantages of the coaxial rotorcraft for hover flight and the efficiencies of a fixed-wing for forward flight. A detailed dynamical model, including the aerodynamics, is obtained via the Newton-Euler formulation. It is proposed a nonlinear control law that achieves global stability for the longitudinal vertical-mode motion. Indeed, we have performed a simulation study to test the proposed controller in presence of external perturbations, obtaining satisfactory results. We have developed an embedded autopilot to validate the proposed prototype and the control law in hover-mode flight.

Rogelio Lozano

Papers

Attitude stabilization in hover flight of a mini tail-sitter UAV with variable pitch propeller

Stabilization of the Furuta Pendulum Around Its Homoclinic Orbit

Brief Adaptive control for linear slowly time-varying systems using direct least-squares estimation

Technical Communique: PD control of robot manipulators with joint flexibility, actuators dynamics and friction

Modeling and Global Control of the Longitudinal Dynamics of a Coaxial Convertible Mini-UAV in Hover Mode