Adaptive Control of Systems with Quantization and Time Delays

This thesis addresses problems relating to tracking control of nonlinear systems in the presence of quantization and time delays. Motivated by the importance in areas such as networked control systems (NCSs) and digital systems, where the use of a communication network in NCS introduces several constraints to the control system, such as the occurrence of quantization and time delays. Quantization and time delays are of both practical and theoretical importance, and the study of systems where these issues arises is thus of great importance. If the system also has parameters that vary or are uncertain, this will make the control problem more complicated. Adaptive control is one tool to handle such system uncertainty. In this thesis, adaptive backstepping control schemes are proposed to handle uncertainties in the system, and to reduce the effects of quantization. Different control problems are considered where quantization is introduced in the control loop, either at the input, the state or both the input and the state. The quantization introduces difficulties in the controller design and stability analysis due to the limited information and nonlinear characteristics, such as discontinuous phenomena. In the thesis, it is analytically shown how the choice of quantization level affects the tracking performance, and how the stability of the closed-loop system equilibrium can be achieved by choosing proper design parameters. In addition, a predictor feedback control scheme is proposed to compensate for a time delay in the system, where the inputs are quantized at the same time. Experiments on a 2-degrees of freedom (DOF) helicopter system demonstrate the different developed control schemes.publishedVersio

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

Modelling of a Flexible Manoeuvring System Using ANFIS Techniques

The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years. Robust optimal control of flexible structures with active feedback techniques requires accurate models of the base structure, and knowledge of uncertainties of these models. Such information may not be easy to acquire for certain systems. An adaptive Neuro-Fuzzy inference Systems (ANFIS) use the learning ability of neural networks to adjust the membership function parameters in a fuzzy inference system. Hence, modelling using ANFIS is preferred in such applications. This paper discusses modelling of a nonlinear flexible system namely a twin rotor multi-input multi-output system using ANFIS techniques. Pitch and yaw motions are modelled and tested by model validation techniques. The obtained results indicate that ANFIS modelling is powerful to facilitate modelling of complex systems associated with nonlinearity and uncertainty

Modeling and Adaptive Hybrid Fuzzy Control of a Nonlinear Rotor System

The paper deals with the hierarchical modeling, simulation and model-based investigation of a nonlinear 1 DOF helicopter model, which is the most important building block of complex multi-rotor systems. The motivation behind the work is the increasing number of multi-rotor drones with various applications in diverse areas like smart cities and smart infrastructures, such as intelligent surveillance, autonomous (or semi-autonomous) flight, automatic object detection and recognition, carrying various payloads (sensors, packages) etc. In order to make these flying robots intelligent, a sophisticated control strategy is required, which is partly based on sensory information provided by the on-board sensors (gyroscope, accelerometer) - recently supported by visual data provided by on-board camera(s) - concerning the low-level feedback control loops. Most of the modern drones are built on an embedded computer, and the first layer of control is usually implemented in the firmware, thus the low level control commands are given per se. For the accomplishment of complex tasks (specific "behavior" of the drone) high level control strategies have to be implemented. In order to make these control loops efficient and robust, model based analysis of the controlled system had been carried out along with the real-life tests of the various control strategies. Since both the structure and the parameter set of the model system can be easily changed, model based study is a very efficient way of experimenting with novel control approaches

Optimal control of a helicopter unmanned aerial vehicle (UAV)

This thesis addresses optimal control of a helicopter unmanned aerial vehicle (UAV). Helicopter UAVs may be widely used for both military and civilian operations. Because these helicopters are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This thesis presents an optimal controller design via both state and output feedback for trajectory tracking of a helicopter UAV using a neural network (NN). The state and output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers while the output feedback approach uses an observer in addition to these controllers. The online approximator-based dynamic controller learns the Hamilton-Jacobi-Bellman (HJB) equation in continuous time and calculates the corresponding optimal control input to minimize the HJB equation forward-in-time. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking. A description of the hardware for confirming the theoretical approach, and a discussion of material pertaining to the algorithms used and methods employed specific to the hardware implementation is also included. Additional attention is devoted to challenges in implementation as well as to opportunities for further research in this field. This thesis is presented in the form of two papers --Abstract, page iv

Adaptive Backstepping Attitude Control of a Rigid Body with State Quantization

Author's accepted manuscript© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, the attitude tracking control problem of a rigid body is investigated where the states are quantized. An adaptive backstepping based control scheme is developed and a new approach to stability analysis is developed by constructing a new compensation scheme for the effects of the vector state quantization. It is shown that all closed-loop signals are ensured uniformly bounded and the tracking errors converge to a compact set containing the origin. Experiments on a 2 degrees-of-freedom helicopter system illustrate the proposed control scheme.acceptedVersio

Six degree of freedom manual controls study report

The feasibility of using degree of freedom manual controls in space in an on orbit environment was determined. Several six degree of freedom controls were tested in a laboratory environment, and replica controls were used to control robot arms. The selection of six degrees of freedom as a design goal was based on the fact that six degrees are sufficient to define the location and orientation of a rigid body in space

Graphical User Interface for Robust Control Education Based on 3DOF Helicopter System

Robustness is an important characteristic of feedback controllers. Many systems with non-linearities and parameter uncertainties usually require sucient robustness to stay stable. Robust control education is therefore very important for graduate students. However, many educational programs in robust control are exclusively theoretical. This thesis work aims at designing and developing a user-friendly Graphical User Interface (GUI) based on MATLAB for robust-control education based on a nonlinear and highly-coupled helicopter system. Although the control design method is limited to the S/KS mixed-sensitivity method, it oers a convenient and ready-to-use GUI for robust control design, dynamic response simulation, robust stability/robust performance assessment, and control implementation. Users can generate the controller by inputting parameters of two weighting functions. Linear and nonlinear simulations based on a discrete-time model are used to assess performance. Structured singular values are used to assess robust stability and robust performance conditions with three typical types of uncertainty. In the end, the designed controller can be loaded into Simulink to control the actual helicopter device. This robust-control educational experiment oers an easy way to test in practice fundamentals of robust control theory

Robust model-based fault estimation and fault-tolerant control : towards an integration

To maintain robustly acceptable system performance, fault estimation (FE) is adopted to reconstruct fault signals and a fault-tolerant control (FTC) controller is employed to compensate for the fault effects. The inevitably existing system and estimation uncertainties result in the so-called bi-directional robustness interactions defined in this work between the FE and FTC functions, which gives rise to an important and challenging yet open integrated FE/FTC design problem concerned in this thesis. An example of fault-tolerant wind turbine pitch control is provided as a practical motivation for integrated FE/FTC design.To achieve the integrated FE/FTC design for linear systems, two strategies are proposed. A H∞ optimization based approach is first proposed for linear systems with differentiable matched faults, using augmented state unknown input observer FE and adaptive sliding mode FTC. The integrated design is converted into an observer-based robust control problem solved via a single-step linear matrix inequality formulation.With the purpose of an integrated design with more freedom and also applicable for a range of general fault scenarios, a decoupling approach is further proposed. This approach can estimate and compensate unmatched non-differentiable faults and perturbations by combined adaptive sliding mode augmented state unknown input observer and backstepping FTC controller. The observer structure renders a recovery of the Separation Principle and allows great freedom for the FE/FTC designs.Integrated FE/FTC design strategies are also developed for Takagi-Sugeno fuzzy modelling nonlinear systems, Lipschitz nonlinear systems, and large-scale interconnected systems, based on extensions of the H∞ optimization approach for linear systems.Tutorial examples are used to illustrate the design strategies for each approach. Physical systems, a 3-DOF (degree-of-freedom) helicopter and a 3-machine power system, are used to provide further evaluation of the proposed integrated FE/FTC strategies. Future research on this subject is also outlined