Adaptive control of nonlinear system based on QFT application to 3-DOF flight control system

Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research UAV, because of its high load carrying capacity with a smaller number of motor and requirement of forethought motor control dynamics. Various control algorithms are investigated and designed for the motion control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover, manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper, we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT) controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S. Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on structured uncertainties associated with controller for the flight conditions theoretically. The development of simulationbased design on flight control system response, opened a new dimension for researcher to design physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid controller that is QFT based adaptive controller for all the three angles

Modelling, estimation and control of a twin-helicopter slung load transportation system

The development of a control system to transport and assemble cargo using two helicopters is presented in this thesis. It is more economical to use multiple lower cost helicopters in a coordinated manner to carry cargo than to use a single high performance helicopter for the transportation task. The reason for the generally higher cost of hiring high performance helicopters, is because they are not required often, and so, remain idle for most of their lifetime. Thus, using less specialised, lower performing helicopters to share the load is cheaper. Beyond just sharing the load of the cargo, the objective in this investigation is to control the attitude such that precise placement of the cargo can be made. This objective cannot be achieved using a single helicopter, unless a sophisticated tethering mechanism is developed. The installation of wind-turbine blades, powerline towers and radio masts in remote locations, are examples of where the application of this technology may be useful. The investigation of this thesis is around modelling, estimation and control of the twinhelicopter slung load transportation system. The title reflects the investigation that was required to be done to determine whether a scheme could be realisable. To test the concept, an experimental platform was developed. A small, light-weight and high performance avionics system was designed and interfaced to the helicopters. The experimentation was done indoors, and hence, the flying volume was limited. For the purpose of feedback and analysis, a motion capture system was developed to track the position and attitude of the helicopters. A high-fidelity mathematical model of a small-scale helicopter was developed. Estimation algorithms were then developed to optimally fuse the data from the instrumentation designed. The data was then used in a system identification exercise to find the parameters that capture the dynamics of the helicopter. The full constrained model of the twin-helicopter slung load dynamics was then developed. The high-fidelity multivariable, interacting system was then linearised to generate a set of uncertain plants. Unexpected resonant modes were investigated using modal analysis to understand their source. Robust controllers were designed using Quantitative Feedback Theory (QFT) for the individual helicopter attitude and altitude loops. A solution was found for the twin-helicopter load transportation system by decoupling the plant with a static pre-compensator and then designing a decentralised QFT controller for the 6 × 6 plant. The effort of this thesis is towards the (practical) realisation of a twin-helicopter aerial crane capable of attitude control; the architecture for the industrialisation of the twin-helicopter load transportation system is proposed

Automatic Flight Control Systems

The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks

Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications

Dynamic modeling and control of a Quadrotor using linear and nonlinear approaches

With the huge advancements in miniature sensors, actuators and processors depending mainly on the Micro and Nano-Electro-Mechanical-Systems (MEMS/NEMS), many researches are now focusing on developing miniature flying vehicles to be used in both research and commercial applications. This thesis work presents a detailed mathematical model for a Vertical Takeo ff and Landing (VTOL) type Unmanned Aerial Vehicle(UAV) known as the quadrotor. The nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method, the formulated model is detailed including aerodynamic effects and rotor dynamics that are omitted in many literature. The motion of the quadrotor can be divided into two subsystems; a rotational subsystem (attitude and heading) and a translational subsystem (altitude and x and y motion). Although the quadrotor is a 6 DOF underactuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is underactuated. The derivation of the mathematical model is followed by the development of four control approaches to control the altitude, attitude, heading and position of the quadrotor in space. The fi rst approach is based on the linear Proportional-Derivative-Integral (PID) controller. The second control approach is based on the nonlinear Sliding Mode Controller (SMC). The third developed controller is a nonlinear Backstepping controller while the fourth is a Gain Scheduling based PID controller. The parameters and gains of the forementioned controllers were tuned using Genetic Algorithm (GA) technique to improve the systems dynamic response. Simulation based experiments were conducted to evaluate and compare the performance of the four developed control techniques in terms of dynamic performance, stability and the effect of possible disturbances

Adaptive control of nonlinear system based on QFT application to 3-DOF flight control system

Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research UAV, because of its high load carrying capacity with a smaller number of motor and requirement of forethought motor control dynamics. Various control algorithms are investigated and designed for the motion control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover, manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper, we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT) controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S. Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on structured uncertainties associated with controller for the flight conditions theoretically. The development of simulationbased design on flight control system response, opened a new dimension for researcher to design physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid controller that is QFT based adaptive controller for all the three angles

Dexterous Hexrotor UAV Platform

Mobile manipulation is a hot area of study in robotics as it unites the two classes of robots: locomotors and manipulators. An emerging niche in the field of mobile manipulation is aerial mobile manipulation. Although there has been a fair amount of study of free-flying satellites with graspers, the more recent trend has been to outfit UAVs with graspers to assist various manipulation tasks. While this recent work has yielded impressive results, it is hampered by a lack of appropriate testbeds for aerial mobile manipulation, similar to the state of ground-based mobile manipulation a decade ago. Typical helicopters or quadrotors cannot instantaneously resist or apply an arbitrary force in the plane perpendicular to the rotor axis, which makes them inadequate for complex mobile manipulation tasks. Based on the concept of force closure (a term from the dexterous manipulation community), this thesis introduces the new type of dexterous, 6-DoF UAV which provides the unique capability of being able to resist any applied wrench, or generalized force-torque. In this thesis, we describe the importance of force closure for mobile manipulation, explain why it is lacking in current UAV platforms, and describe how our hexrotor provides this important capability as well as exhibiting holonomic behavior

A System of Autonomously Flying Helicopters for Load Transportation

Die Arbeit beschreibt Entwurf, Umsetzung und Validierung eines autonomen Lastentransportsystems, welches auf Basis mehrerer Modellhubschrauber realisiert wurde. Abhängig von den Anforderungen der zu transportierenden Last kann die Anzahl der verwendeten Hubschrauber individuell angepasst werden. Die präsentierten Modelle und Regler wurden durch Computersimulationen und reale Flugversuche verifiziert. Zwei nichtlineare Modelle werden präsentiert: Ein Model für Konfigurationen bestehend aus einem Helikopter und einer Last (single-lift) und eines für Konfigurationen bestehend aus zwei bzw. mehreren Helikoptern und einer Last (dual- und multi-lift). Neben diesen komplexen Modellen werden vereinfachte Modelle vorgestellt, die für den Reglerentwurf verwendet werden. Ein generischer Orientierungsregler wird entwickelt, der für die Regelung aller beschriebenen Transportkonfigurationen verwendet werden kann. Durch die Nutzung dieses Reglers vereinfacht sich der Entwurf der Translationsregler erheblich. Drei Translationsregler werden beschrieben: Ein Regler für single-lift Konfigurationen, der eine aktive Unterdrückung von Lastschwingungen erlaubt, und ein verteilter Regler für multi-lift Konfigurationen. Weiterhin wird ein dual-lift Regler präsentiert, der eine Kombination der anderen Regler darstellt. Die Regler für dual- und multi-lift Konfigurationen verwenden keine mechanischen Hilfskonstrukte wie Abstandshalter. Die Position der Last wird durch die Orientierung des Seils, gemessen nahe dem Helikopterrumpf, bestimmt. Externe Störungen wie Windstöße können eine Eigenschwingung des Seils anregen, welche die ermittelte Lastposition verfälscht. Die Eigenschwingung des Seils sowie der Einfluss der verwendeten Messeinrichtung werden analysiert. Auf Basis dieser Analyse wird ein Lastbeobachter entwickelt und in mehreren Experimenten verifiziert. Dieser Lastbeobachter ist von essentieller Wichtigkeit für den sicheren Betrieb des Lastentransportsystems, insbesondere bei schlechten Wetterbedingungen. Die entwickelten nichtlinearen Modelle des Systems wie auch die Regler der single- und multi-lift Konfigurationen wurden durch Flugversuche validiert. Dabei hat das System bewiesen, dass es auch bei sehr schlechten Wetterbedingungen einsetzbar iThis work covers the design, realization and validation of an autonomous load transportation system, utilizing several small size helicopters. The number of participating helicopters is configurable for the described system, depending on the requirements of the transported load. The presented models and controllers have been validated in computer simulation and flight experiments. Two non-linear models are presented: One model covers single-lift and one model covers dual- and multi-lift configurations. Simplified models are introduced beside the complex models, which are utilized for the translation controller design. A generic orientation controller is presented, which is applicable for the control of all presented slung load configurations. The utilization of this controller significantly simplifies the design of the translation controllers. The independence from the actual slung load configuration is achieved through measurement of the rope force vector in the rope attachment point, which is located on the helicopter fuselage. Three translation controllers are described: A controller for single-lift configurations, which allows the active compensation of load oscillations and a distributed controller for multi-lift configurations. A dual-lift translation controller is presented, which resembles a combination of single- and multi-lift translation controller. The presented controllers for dual- or multi-lift configurations do not utilize auxiliary constructs, like spreader-bars. The position of the load is estimated from the measured orientation of the rope, close to the helicopter fuselage. External disturbances, like wind gusts, are able to stimulate internal oscillations of the rope, which disturb the estimated load position. The internal motion of the rope as well as the influence of the used measurement device are analyzed and a flexible rope model is presented. Based on the results a load motion observer is developed and validated in several experiments. This load motion observer is essential for the safe operation of the slung load system, especially during bad weather conditions. The derived non-linear models of the system as well as the proposed controllers for single- and multi-lift configurations have been validated in flight experiments. The system has been proven to be operable even in presence of adverse weather conditions

Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles

With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances. This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults