Kouamana Bousson

University of Beira Interior, Covilhã, Portugal · Department of Aerospace Sciences

Nonlinear state estimation problem is an important and complex topic, especially for real-time applications with a highly nonlinear environment. This scenario concerns most aerospace applications, including satellite trajectories, whose high standards demand methods with matching performances. A very well-known framework to deal with state estimati...

4D flight trajectory optimization is an essential component to improve flight efficiency and to enhance air traffic capacity. this technique not only helps to reduce the operational costs, but also helps to reduce the environmental impact caused by the airliners. This study considers Dynamic Programming (DP), a well-established numerical method ide...

Given an array (or matrix) of values for a function of one or more variables, it is often desired to find a value between two given points. Multivariable interpolation and approximation by radial basis functions are important subjects in approximation theory that have many applications in Science and Engineering fields. During the last decades, rad...

Nonlinear state estimation is a desirable and required technique for many situations in engineering (e.g., aircraft/spacecraft tracking, space situational awareness, collision warning, radar tracking, etc.). Due to high standards on performance in these applications, in the last few decades, there was an increasing demand for methods that are able...

The purpose of this work is to develop a trajectory optimization method that generates a fuel optimal trajectory from a predefined 4D waypoint networks, where the arrival time is specified for each waypoint in the network. A single source shortest path algorithm is presented to generate the optimal flight trajectory that minimizes fuel burn. Genera...

Flight trajectory optimization has become an important factor not only to reduce the operational costs (e.g., fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g., emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory...

A wise feature selection from minute-to-minute Electrocardiogram (ECG) signal is a challenging task for many reasons, but mostly because of the promise of the accurate detection of clinical disorders, such as the sleep apnea. In this study, the ECG signal was modeled in order to obtain the Heart Rate Variability (HRV) and the ECG-Derived Respiratio...

One of the most demanded assets nowadays is energy. Over many options to generate it, humankind must seek sustainable ways; therefore, renewable energies must be empowered. Moreover, wind provides great benefits, granting uncalculated power at our disposition. Since this task is executed by big structures, their maintenance represents a difficult t...

Online parameter estimation for time-varying systems is a fundamental part of adaptive control, real-time system monitoring and prediction. A well-known framework for dealing with such a task is the Kalman filtering. Meanwhile Kalman filtering may be cumbersome for some time-critical systems and inappropriate for systems whose stochastic characteri...

This paper provides a survey of nonlinear filtering methods for state estimation based on Kalman filtering. Early applications relied mostly on the extended Kalman filter, and since these applications, several new approaches have been developed, where various modifications are employed to provide better convergence or to improve other performance c...

The problem of nonlinear state estimation is a crucial task and deserves a special attention particularly when it comes to time-critical applications in a highly nonlinear environment. The performance of the estimation is particularly dependent on the accuracy of the models and the availability of highly accurate information, however real-world phy...

Trajectory optimization is a vital area in aeronautic industry. This technique enables generating optimal trajectories for vehicles with consideration of fuel consumption, travel time, obstacle avoidance, and many other requirements. However, there is no best method to solve the trajectory optimization problem, but some methods might do a better jo...

The main purpose of this paper is to develop a trajectory optimization method to generate optimal trajectories that minimize aircraft total trip time between the initial and final waypoint in predefined 4D waypoint networks. In this paper, the 4D waypoint networks only consist of waypoints for climb, cruise and descent approach without the take-off...

Fuel consumption is one of the main sources of high operating cost of commercial aircraft. Besides, environmental impact due to commercial flights has also been a major concern for air transportation. Fuel saving and environmental impact reduction have been dealt with so far in the context of 2D and 3D trajectory optimization, which is inefficient...

In nature, most physical systems are inherently nonlinear so nonlinear filters are extremely useful in diverse real world applications, including target tracking, navigation of aerospace vehicle, multi-sensor data fusion, robotics, communication systems, inertial navigation, chemical plant control, predicting weather, as well as estimating structur...

The estimation of space object trajectories in the framework of space situational awareness and collision warning is based on the availability of highly accurate information about the orbiting objects. Such a task is critical and radar tracking of space objects requires robust filtering methods that are able to deal not only with the uncertainties...

Background and objective: Sleep apnea syndrome (SAS), which can significantly decrease the quality of life is associated with a major risk factor of health implications such as increased cardiovascular disease, sudden death, depression, irritability, hypertension, and learning difficulties. Thus, it is relevant and timely to present a systematic r...

This chapter provides an overview of the Machine Learning (ML) concepts in the clinical field which data may be collected, either by Health Care Professionals (HCP) or patients. These data may include activities and medication reminders, objective measurement of physiological parameters, feedback based on observed patterns, questionnaires and score...

This paper deals with a nonlinear feedback control method based on Lie derivatives for the navigation guidance of unmanned aerial vehicles (UAVs). The paper proposes a modelling concept for planar and three-dimensional navigation together with proven algorithms to cope with the autonomous navigation along waypoints and on loiters. The steps that we...

The estimation of space object trajectories in the framework of space situational awareness and collision warning is based on the availability of highly accurate information about the orbiting objects. Such a task is critical, for instance, for monitoring the trajectories of space vehicles, space debris, and threatening incoming asteroids. Radar tr...

Background: Mobile and web technologies are becoming increasingly used to support the treatment of chronic pain conditions. However, the subjectivity of pain perception makes its management and evaluation very difficult. Pain treatment requires a multi-dimensional approach (e.g., sensory, affective, cognitive) whence the evidence of technology eff...

The most common location for campsites is in forested or arborous areas. Given the regular use of combustible material by campers and the frequent use of campfires to cook, campsites become areas with a high propensity for the occurrence of fires. Moreover, fires occurring close to campsites can cause evacuations, disturbing their regular activitie...

Real-world dynamical systems are nonlinear in nature and require bounded controls due to electrical, mechanical and other input limitations. The present paper proposes a method to synchronize chaotic systems with controls subject to magnitude and rate constraints. The method consists in decomposing the driven system into a stabilizable linear part...

Verification of electrical lines and their infrastructure is an essential activity to ensure the undisturbed operation of the electrical grid and supply energy to final consumers. Performing the survey work in safety is the primary objective of the inspection teams and with this doctoral program to create tools that help in this task. For this purp...

Existing autonomous navigation procedures are mostly done in 3D whilst actual flight plan fulfillment requires 4D navigation. The present work deals with 4D navigation trajectory generation for autonomous aerial vehicles along given sequences of waypoints with time constraints at specified check points. Because passing through the exact position of...

The present work aims to improve the safety of overhead power line inspection and similar tasks. Due to the proximity of objects imposed by the inspection missions, the appliance of Extended Kalman Filter for quadrotor attitude control in a supervised environment was proposed. Verification of electrical lines and their infrastructure is an essentia...

The main challenge of big data processing includes the extraction of relevant information, from a high dimensionality of a wide variety of medical data by enabling analysis, discovery and interpretation. These data are a useful tool for helping to understand disease and to formulate predictive models in different areas and support different tasks,...

The complexity of the clinical context requires systems with the capability to make decisions based on reduced sets of data. Moreover, the adoption of mobile and ubiquitous devices could provide personal health-related information. In line with this, eHealth application faces several challenges so as to provide accurate and reliable data to both he...

The common location of camping parks in forested or wooded areas, the normal use of combustible material by the campers and the frequent use of campfires to cook turn camping parks into areas with a high propensity for the occurrence of fires. Moreover, fires occurring close to parks induce to evacuations that disturb their normal activities. Despi...

A generalization of collision cone concept applied to real-time Collision Avoidance System (CAS) is proposed. Mostly due to the current trend of a wide range of applications which use unmanned air vehicles (UAV), the Collision Avoidance Systems take an important role either on airborne systems or even Air Traffic Collision Systems (ATC). Thus, a po...

In recent years, Internet-delivered treatments have been largely used for pain monitoring, offering healthcare professionals and patients the ability to interact anywhere and at any time. Electronic diaries have been increasingly adopted as the preferred methodology to collect data related to pain intensity and symptoms, replacing traditional pen-a...

This chapter proposes a robust control approach for the class of chaotic systems subject to magnitude and rate actuator constraints. The approach consists of decomposing the chaotic system into a linear part plus a nonlinear part to form an augmented system comprising the system itself and the integral of the output error. The resulting system is p...

This chapter provides an overview of the Machine Learning (ML) concepts in the clinical field which data may be collected, either by Health Care Professionals (HCP) or patients. These data may include activities and medication reminders, objective measurement of physiological parameters, feedback based on observed patterns, questionnaires and score...

The main challenge of big data processing includes the extraction of relevant information, from a high dimensionality of a wide variety of medical data by enabling analysis, discovery and interpretation. These data are a useful tool for helping to understand disease and to formulate predictive models in different areas and support different tasks,...

One of the operational requirements for unmanned aerial vehicles is the autonomous navigation and control along a given sequence of waypoints, or along a predefined trajectory. Existing autonomous navigation procedures are mostly done in 3D because of the stringent certification requirements for 4D flight and due to the complexity in coping with ti...

A simple and easy-to-implement method that guarantees the effective active synchronization of a chaotic gyroscopic system within a specified settling time limit is presented. A closed-form expression is given for the determination of the appropriate synchronizing control signal. The method is successfully validated through simulations for various i...

ADS-B is a very useful system to solve surveillance precision problems mainly if installation, operation and maintenance costs of alternative ones are too expensive when they are based on air traffic figures. This paper begins with some remarks about ADS-B technology, precisely to introduce the case study of Azores archipelago within Santa Maria FI...

This paper deals with the viability analysis of the implementation of RNAV and RNP AR approaches to Pico Island airport in the Azorean archipelago. The main objective is to prove that this new type of approach technology can be implemented in the Azorean islands airports in accordance with the ICAO rules providing an increase in safety and lowering...

Congestion in the Terminal Maneuvering Areas (TMAs) of larger airports impacts all aspects of air traffic flow not only at national level but may also induce arrival delays at international level. Hence, there is a need to forecast the air traffic flow density in TMAs so that appropriate decisions may be taken to optimize their occupancy rates. The...

The optimization and control problem for 4D trajectories is a subject rarely addressed in literature. In the 4D navigation problem we define waypoints, for each mission, where the arrival time is specified in each of them. One way to design trajectories for achieving this kind of mission is to use the trajectory optimization concepts. To solve a tr...

A method for global and robust stabilization of aeroelastic wing vibrations based on optimal feedback control concepts is described in the present paper using Lyapunov stability theory. The method consists in decomposing the system model into a stabilizable linear part and a nonlinear part that satisfies sector-bound inequality; then a control law...

The present paper deals with the active control of chaotic systems. The main contribution is the use of a simple linear optimal robust control method to drive chaotic systems to generate specified pattern signals intended to be used as carriers for communication matters, contrarily to existing methods that use complex and not necessarily robust non...

Purpose Most of the existing approaches for flight collision avoidance are concerned with local traffic alone for which the separation is based on the pairwise analysis of aircraft trajectory trends, which is not efficient with regard to some flight path requirements along waypoints. The purpose of this paper is to deal with the global collision av...

Purpose This paper is concerned with an online parameter estimation algorithm for nonlinear uncertain time‐varying systems for which no stochastic information is available. Design/methodology/approach The estimation procedure, called nonlinear learning rate adaptation (NLRA), computes an individual adaptive learning rate for each parameter instead...

Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, wh...

Most of the existing linearization methods for nonlinear flight dynamics are based on the first order approximation of the model in the neighborhood of a given reference or equilibrium point. The resulting linear model approximates the nonlinear flight within relatively small variations of the state and the control around the reference point. Howev...

A Dynamic Programming (DP) method is presented in the framework of trajectory optimization. The method is based on the use of a single state gridpoint at each stage, and on the successive reductions of the value of the cost-to-go at each iteration up to convergence. The method has the advantage of requiring less computation memory and time than Ite...

The present paper proposes an optimization algorithm for dealing with optimal control issues based on direct methods. Since direct methods involve the discretization of the differential equations modelling the dynamics of the system and the cost function, the dimension of the resulting problem may be very high, which can be a challenge for most opt...

Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable, have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method which re...

The time and space complexity required by conventional dynamic programming (DP) is usually prohibitive even for problems with moderate search dimensions due to the very large number of grid points required to obtain satisfactory results. An iterative version of DP, called Iterative Dynamic Programming (IDP), was proposed recently, and has shown gre...

The future solution for the increasing air traffic density appears to be the free flight for which each airplane will have the possibility to choose its own trajectory and to follow it with only minor ground air traffic controllers' guides. The present paper deals with global collision avoidance which aims at separating aircraft taking into conside...

The paper proposes a framework for global optimization in the context of optimal control. The approach is based on successive local optimizations stemming from optimally chosen re-start points. The optimization method which is dealt with for that matter is the Dynamic Canonical Descent algorithm which was proven to have better performances over mos...

In this paper we propose an accurate online parameter identification algorithm for nonlinear time-varying systems. For such systems, techniques based on cross-validation to achieve regularization or model selection are not possible, and classical least square techniques are not reliable when the dynamics of the system are highly nonlinear. To overc...

Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable, have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper briefly reviews the advantages and the l...

This chapter deals with monitoring and diagnosing a fedbatch fermentation process by means of a real-time expert system. The first part of the chapter presents the rule-based expert system BIOTECH which, among other tasks, detects the abnormalities in the process behaviour beforehand, advises the operator about what to do to correct unwanted behavi...

This paper deals with the monitoring and diagnosis of fedbatch biological processes. It reports two aspects of experience conducted on the same pilot plant. The first part of the paper presents the rule-based approach which was used to build the expert system BIOTECH, and the second part presents the dynamic model-based approach followed later to b...

After preliminary work in economics and control theory, qualitative reasoning emerged in AI at the end of the 70s and beginning of the 80s, in the form of Naive Physics and Commonsense Reasoning. This way was progressively abandoned in aid of more formalised approaches to tackle modelling problems in engineering tasks. Qualitative Reasoning became...

Qualitative Reasoning (QR) is a branch of Artificial Intelligence that arose from research on engineering problem solving. This paper describes the major QR methods and techniques, which, we believe, are capable of addressing some of the problems that are emphasized in the literature and posed by CELSS modeling, simulation, and control at the super...

This paper presents the qualitative simulator CA-EN (CAusal ENgine). CA-EN is a causal and constraint-based reasoning system for real-time applications whose first version was devised and implemented for the biotechnology application domain to be part of a model-based supervision system. Having considered to use CA-EN in the framework of the Esprit...

The paper describes the work of the TIGER ESPRIT Project in performing real-time situation assessment of dynamic systems. The goal of TIGER is to monitor a complex dynamic system in real time and make an assessment of whether it is working properly. If it is not working properly, it is desirable to identify the cause of the problem either from a se...

Qualitative models of dynamical systems fall into noncausal or causal approaches. The noncausal approach is widely used in part because traditional physics describes phenomena by means of symmetric functional relations. It supports the idea that causality can be ignored or inferred from the model itself. Nevertheless, when people explain how things...

This paperpresentsa causalsimulationmethod forincompletelyknown dynamic systems inprocessengineering . The causalmodel of a processisrepresentedas both a causal network ofinteractingelementarydynamic systems,calledqualitative automata,influencing one another,and a setofqualitative constraints linkingpossiblyseveralofsuchautomata.Associated with eac...

This paper proposes a causal modeling framework for the purpose of process supervision. It is based on a qualitative automata (or q-automata) concept that we have devised. A q-automaton captures both the dynamics of a process variable and the expert knowledge necessary for supervising the variable's behavior. We use a two-level representation schem...

This paper proposes a causal modeling framework for the purpose of process supervision. It is based on a qualitative automata (or q-automata) concept that we have devised. A q-automaton captures both the dynamics of a process variable and the expert knowledge necessary for supervising the variable's behavior. We use a two-level representation schem...

The purpose of qualitative simulation is to derive all the possible behaviors of an ill-known dynamical system from its structural description. The ability to operate with incomplete knowledge is one of its impressive trumps in comparison with classical quantitative simulation of flabby numerical models. However qualitative simulation often yields...