Singular Value Decomposition-Based Method for Sliding Mode Control and Optimization of Nonlinear Neutral Systems

The sliding mode control and optimization are investigated for a class of nonlinear neutral systems with the unmatched nonlinear term. In the framework of Lyapunov stability theory, the existence conditions for the designed sliding surface and the stability bound α∗ are derived via twice transformations. The further results are to develop an efficient sliding mode control law with tuned parameters to attract the state trajectories onto the sliding surface in finite time and remain there for all the subsequent time. Finally, some comparisons are made to show the advantages of our proposed method

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Parameterization for Time-Delay Systems Based on Passivity and LMI Approach

Control systems can be solved using optimization after being parameterized. Time-delays and uncertainty make it more difficult to obtain optimal solutions. In this work, it is proved that the stability properties of the time delay system can be easily and efficiency achieved using passivity properties in terms of Linear Matrix Inequality techniques (LMI) through effective and reliable optimization algorithms especially convex optimization tools. In this thesis we exploit an appropriate Lyapunov-Krasovskii function that contains both double and triple integral terms and to our knowledge no one have used triple integral term with combination of the passivity conditions; thus constitute the main contribution of this thesis. Thus, constitute moreover, Jensen’s inequality was utilized to deal with cross product terms that appeared when we derive the derivation of Lyapunov-Krasovskii function. Both delay-independent and delay-dependent cases are considered. New delay dependent stability bound for particular time delay systems is derived. This is clear through various numerical examples solved by convex optimization algorithm specifically by CVX toolbox under MATLAB package. Also we deal with the uncertainty that appeared in the control systems with delay. The above technique is used to construct passive robust controller renders the closed loop uncertain time delay system (UTDS) asymptotically stable; in addition, the stability analysis and synthesis of time varying systems with state and input delays is investigated using proposed method with " change of variables method" which make the solution of the particular problem easy and construct the controller directly by inverse transformation as well be seen in the sequel. The effectiveness of the proposed method is shown through several numerical examples. Based on the proposed method exploited in this thesis, at analysis phase, the time delay bound achieved by our approach is less conservative. In the synthesis phase concerns uncertain passive and uncertain controller design less disturbance attenuation level of the time delay has been obtained using proposed method

Constructing 3D faces from natural language interface

This thesis presents a system by which 3D images of human faces can be constructed using a natural language interface. The driving force behind the project was the need to create a system whereby a machine could produce artistic images from verbal or composed descriptions. This research is the first to look at constructing and modifying facial image artwork using a natural language interface. Specialised modules have been developed to control geometry of 3D polygonal head models in a commercial modeller from natural language descriptions. These modules were produced from research on human physiognomy, 3D modelling techniques and tools, facial modelling and natural language processing. [Continues.

New Results on Delay-Dependent Stability Analysis and Stabilization of Time-Delay Systems

The interconnection between physical systems is accomplished by flow of information, energy and material, alternatively known as transport or propagation. As such flows may take a finite amount of time, the reaction of real world systems to exogenous or feedback control signals, from automatic control perspective, are not instantaneous. This results time-delays in systems connected by real-world physical media. Indeed, examples of time-delay systems span biology, ecology, economy, and of course, engineering. To this end, it is known that an arbitrary small delay may destabilize a stable system whereas, a delay in the controller may be used to stabilize a system that is otherwise not stabilizable by using a delay-free controller. In general, the presence of time-delay in a system makes the system dynamics infinite-dimensional, and analysis of such systems is complex.This thesis investigates stability analysis and stabilization of time-delay systems. It proposes a delay-decomposition approach for stability analysis of systems with single delay that leads to a simple LMI condition using a Lyapunov-Krasovskii functional. Moreover, a static state feedback controller is designed for systems with state and input-delay using this delay-decomposition approach. Numerical comparison of the present results vis-`a-vis the existing ones for the systems with constant delay considered shows that the present ones are superior. Next, a PI-type controller is implemented for systems with input-delay to improve the tolerable delay bound. Other problems considered is to analyze the stability of systems with two delays. As the number of delays incorporated in the system dynamics increases, it becomes further complex for analysis

Automatic Landmarking for Non-cooperative 3D Face Recognition

This thesis describes a new framework for 3D surface landmarking and evaluates its performance for feature localisation on human faces. This framework has two main parts that can be designed and optimised independently. The first one is a keypoint detection system that returns positions of interest for a given mesh surface by using a learnt dictionary of local shapes. The second one is a labelling system, using model fitting approaches that establish a one-to-one correspondence between the set of unlabelled input points and a learnt representation of the class of object to detect. Our keypoint detection system returns local maxima over score maps that are generated from an arbitrarily large set of local shape descriptors. The distributions of these descriptors (scalars or histograms) are learnt for known landmark positions on a training dataset in order to generate a model. The similarity between the input descriptor value for a given vertex and a model shape is used as a descriptor-related score. Our labelling system can make use of both hypergraph matching techniques and rigid registration techniques to reduce the ambiguity attached to unlabelled input keypoints for which a list of model landmark candidates have been seeded. The soft matching techniques use multi-attributed hyperedges to reduce ambiguity, while the registration techniques use scale-adapted rigid transformation computed from 3 or more points in order to obtain one-to-one correspondences. Our final system achieves better or comparable (depending on the metric) results than the state-of-the-art while being more generic. It does not require pre-processing such as cropping, spike removal and hole filling and is more robust to occlusion of salient local regions, such as those near the nose tip and inner eye corners. It is also fully pose invariant and can be used with kinds of objects other than faces, provided that labelled training data is available

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies