Fractional Order Fault Tolerant Control - A Survey

In this paper, a comprehensive review of recent advances and trends regarding Fractional Order Fault Tolerant Control (FOFTC) design is presented. This novel robust control approach has been emerging in the last decade and is still gathering great research efforts mainly because of its promising results and outcomes. The purpose of this study is to provide a useful overview for researchers interested in developing this interesting solution for plants that are subject to faults and disturbances with an obligation for a maintained performance level. Throughout the paper, the various works related to FOFTC in literature are categorized first by considering their research objective between fault detection with diagnosis and fault tolerance with accommodation, and second by considering the nature of the studied plants depending on whether they are modelized by integer order or fractional order models. One of the main drawbacks of these approaches lies in the increase in complexity associated with introducing the fractional operators, their approximation and especially during the stability analysis. A discussion on the main disadvantages and challenges that face this novel fractional order robust control research field is given in conjunction with motivations for its future development. This study provides a simulation example for the application of a FOFTC against actuator faults in a Boeing 747 civil transport aircraft is provided to illustrate the efficiency of such robust control strategies

Intelligent tracking control of a DC motor driver using self-organizing TSK type fuzzy neural networks

[[abstract]]In this paper, a self-organizing Takagi–Sugeno–Kang (TSK) type fuzzy neural network (STFNN) is proposed. The self-organizing approach demonstrates the property of automatically generating and pruning the fuzzy rules of STFNN without the preliminary knowledge. The learning algorithms not only extract the fuzzy rule of STFNN but also adjust the parameters of STFNN. Then, an adaptive self-organizing TSK-type fuzzy network controller (ASTFNC) system which is composed of a neural controller and a robust compensator is proposed. The neural controller uses an STFNN to approximate an ideal controller, and the robust compensator is designed to eliminate the approximation error in the Lyapunov stability sense without occurring chattering phenomena. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived to speed up the convergence rates of the tracking error. Finally, the proposed ASTFNC system is applied to a DC motor driver on a field-programmable gate array chip for low-cost and high-performance industrial applications. The experimental results verify the system stabilization and favorable tracking performance, and no chattering phenomena can be achieved by the proposed ASTFNC scheme.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Multi-objective Optimization of Multi-loop Control Systems

Cascade Control systems are composed of inner and outer control loops. Compared to the traditional single feedback controls, the structure of cascade controls is more complex. As a result, the implementation of these control methods is costly because extra sensors are needed to measure the inner process states. On the other side, cascade control algorithms can significantly improve the controlled system performance if they are designed properly. For instance, cascade control strategies can act faster than single feedback methods to prevent undesired disturbances, which can drive the controlled system’s output away from its target value, from spreading through the process. As a result, cascade control techniques have received much attention recently. In this thesis, we present a multi-objective optimal design of linear cascade control systems using a multi-objective algorithm called the non-dominated sorting genetic algorithm (NSGA-II), which is one of the widely used algorithms in solving multi-objective optimization problems (MOPs). Two case studies have been considered. In the first case, a multi-objective optimal design of a cascade control system for an underactuated mechanical system consisting of a rotary servo motor, and a ball and beam is introduced. The setup parameters of the inner and outer control loops are tuned by the NSGA-II to achieve four objectives: 1) the closed-loop system should be robust against inevitable internal and outer disturbances, 2) the controlled system is insensitive to inescapable measurement noise affecting the feedback sensors, 3) the control signal driving the mechanical system is optimum, and 4) the dynamics of the inner closed-loop system has to be faster than that of the outer feedback system. By using the NSGAII algorithm, four design parameters and four conflicting objective functions are obtained. The second case study investigates a multi-objective optimal design of an aeroelastic cascade controller applied to an aircraft wing with a leading and trailing control surface. The dynamics of the actuators driving the control surfaces are considered in the design. Similarly, the NSGA-II is used to optimally adjust the parameters of the control algorithm. Ten design parameters and three conflicting objectives are considered in the design: the controlled system’s tracking error to an external gust load should be minimal, the actuators should be driven by minimum energy, and the dynamics of the closed-loop comprising the actuators and inner control algorithm should be faster than that of the aeroelastic structure and the outer control loop. Computer simulations show that the presented case studies may become the basis for multi-objective optimal design of multi-loop control systems

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Design, Implementation and Testing of Advanced Control Laws for Fixed-wing UAVs

The present PhD thesis addresses the problem of the control of small fixed-wing Unmanned Aerial Vehicles (UAVs). In the scientific community much research is dedicated to the study of suitable control laws for this category of aircraft. This interest is motivated by the several applications that these platforms can perform and by their peculiarities as dynamical systems. In fact, small UAVs are characterized by highly nonlinear behavior, strong coupling between longitudinal and latero-directional planes, and high sensitivity to external disturbances and to parametric uncertainties. Furthermore, the challenge is increased by the limited space and weight available for the onboard electronics. The aim of this PhD thesis is to provide a valid confrontation among three different control techniques and to introduce an innovative autopilot configuration suitable for the unmanned aircraft field. Three advanced controllers for fixed-wing unmanned aircraft vehicles are designed and implemented: PID with H1 robust approach, L1 adaptive controller and nonlinear backstepping controller. All of them are analyzed from the theoretical point of view and validated through numerical simulations with a mathematical UAV model. One is implemented on a microcontroller board, validated through hardware simulations and tested in flight. The PID with H1 robust approach is used for the definition of the gains of a commercial autopilot. The proposed technique combines traditional PID control with an H1 loop shaping method to assess the robustness characteristics achievable with simple PID gains. It is demonstrated that this hybrid approach provides a promising solution to the problem of tuning commercial autopilots for UAVs. Nevertheless, it is clear that a tradeoff between robustness and performance is necessary when dealing with this standard control technique. The robustness problem is effectively solved by the adoption of an L1 adaptive controller for complete aircraft control. In particular, the L1 logic here adopted is based on piecewise constant adaptive laws with an adaptation rate compatible with the sampling rate of an autopilot board CPU. The control scheme includes an L1 adaptive controller for the inner loop, while PID gains take care of the outer loop. The global controller is tuned on a linear decoupled aircraft model. It is demonstrated that the achieved configuration guarantees satisfying performance also when applied to a complete nonlinear model affected by uncertainties and parametric perturbations. The third controller implemented is based on an existing nonlinear backstepping technique. A scheme for longitudinal and latero-directional control based on the combination of PID for the outer loop and backstepping for the inner loop is proposed. Satisfying results are achieved also when the nonlinear aircraft model is perturbed by parametric uncertainties. A confrontation among the three controllers shows that L1 and backstepping are comparable in terms of nominal and robust performance, with an advantage for L1, while the PID is always inferior. The backstepping controller is chosen for being implemented and tested on a real fixed-wing RC aircraft. Hardware-in-the-loop simulations validate its real-time control capability on the complete nonlinear model of the aircraft adopted for the tests, inclusive of sensors noise. An innovative microcontroller technology is employed as core of the autopilot system, it interfaces with sensors and servos in order to handle input/output operations and it performs the control law computation. Preliminary ground tests validate the suitability of the autopilot configuration. A limited number of flight tests is performed. Promising results are obtained for the control of longitudinal states, while latero-directional control still needs major improvements

CFD Modelling and Simulation of Water Turbines

The design and development of water turbines requires accurate methods for performance prediction. Numerical methods and modelling are becoming increasingly important tools to achieve better designs and more efficient turbines, reducing the time required in physical model testing. This book is focused on applying numerical simulations and models for water turbines to predict tool their performance. In this Special Issue, the different contributions of this book are classified into three state-of-the-art Topics: discussing the modelling of pump-turbines, the simulation of horizontal and vertical axis turbines for hydrokinetic applications and the modelling of hydropower plants. All the contributions to this book demonstrate the importance of the modelling and simulation of water turbines for hydropower energy. This new generation of models and simulations will play a major role in the global energy transition and energy crisis, and, of course, in the mitigation of climate change

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Aeronautical engineering: A continuing bibliography with indexes (supplement 309)

This bibliography lists 212 reports, articles, and other documents introduced into the NASA scientific and technical information system in Oct. 1994. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics