This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

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

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

System Identification I

Thermophysical Properties Research Literature Retrieval Guide Edited by Y. S. Touloukian, J. K. Gerritsen and N. Y. Moore Second edition, revised and expanded. Book 1: Pp. xxi + 819. Book 2: Pp.621. Book 3: Pp. ix + 1315. (New York: Plenum Press, 1967.) n.p.

/pdf/heat-and-mass-transfer-1yaijfx8vp.pdf

Heat and Mass Transfer

We present the closed-loop controlled compensation of the thermally induced lens in a high-power thin-disk oscillator to obtain fundamental-mode operation over a wide range of pump powers. The radius of the oscillating beam was measured in real time at the position of the thin-disk crystal. This signal was used by the control system to adapt the curvature of a spherically deformable mirror to maintain a constant radius of the oscillating laser beam.

https://iopscience.iop.org/article/10.1088/1612-202X/abd3fa/pdf

Closed-loop controlled compensation of thermal lensing in high-power thin-disk lasers using spherically deformable mirrors

Quantization errors occur when a signal is measured by digital sensors that have naturally a limited accuracy. When applying position control to a large scale robot, these quantization errors cause steps in the control input that possibly excite structural oscillations. To prevent this phenomenon, a state observer is designed that provides smooth estimated states with high accuracy for systems with quantized output. It is realized by observing the error dynamics of the measurement signal. The resulting observer is updated at each time instance where the quantized value of the measured signal changes. By using a corrected value of the output as well as an orthogonal projection, the updated estimation error leads to smooth estimated states. The design of this triggered observer does not have more design parameter than a conventional Luenberger observer and is therefore readily to implement. However, the overall estimation error is smaller in a direct comparison to such a Luenberger observer which is shown in simulations using a model of a mechanical drive system.

State Observer for Position Control of Systems with Quantized Outputs in Large Scale Robotics

Near Time Optimal Trajectory Generation for Over-Actuated Vehicles using Nonlinear Model Predictive Controller

PROBLEM TO BE SOLVED: To provide a system capable of determining a load capacity which is improved based on a cable force, in regard to a system for determining a load mass of a load to be carried by a hoist cable of a crane. SOLUTION: The system includes: a measuring device for measuring a cable load applied to a hoist cable; and a computing unit for determining a load mass based on the cable force. The computing unit includes a correcting unit for partially correcting the load mass by obtaining an influence of the indirect decision of the load mass by using the cable force by using a model. COPYRIGHT: (C)2011,JPO&INPIT

Oliver Sawodny

Papers

Closed-loop controlled compensation of thermal lensing in high-power thin-disk lasers using spherically deformable mirrors

State Observer for Position Control of Systems with Quantized Outputs in Large Scale Robotics

Near Time Optimal Trajectory Generation for Over-Actuated Vehicles using Nonlinear Model Predictive Controller

System for determining load mass of load carried by hoist cable of crane

On trajectory tracking control of fluid-driven actuators