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

Hybrid active force control for fixed based rotorcraft

Disturbances are considered major challenges faced in the deployment of rotorcraft unmanned aerial vehicle (UAV) systems. Among different types of rotorcraft systems, the twin-rotor helicopter and quadrotor models are considered the most versatile flying machines nowadays due to their range of applications in the civilian and military sectors. However, these systems are multivariate and highly non-linear, making them difficult to be accurately controlled. Their performance could be further compromised when they are operated in the presence of disturbances or uncertainties. This dissertation presents an innovative hybrid control scheme for rotorcraft systems to improve disturbance rejection capability while maintaining system stability, based on a technique called active force control (AFC) via simulation and experimental works. A detailed dynamic model of each aerial system was derived based on the Euler–Lagrange and Newton-Euler methods, taking into account various assumptions and conditions. As a result of the derived models, a proportional-integral-derivative (PID) controller was designed to achieve the required altitude and attitude motions. Due to the PID's inability to reject applied disturbances, the AFC strategy was incorporated with the designed PID controller, to be known as the PID-AFC scheme. To estimate control parameters automatically, a number of artificial intelligence algorithms were employed in this study, namely the iterative learning algorithm and fuzzy logic. Intelligent rules of these AI algorithms were designed and embedded into the AFC loop, identified as intelligent active force control (IAFC)-based methods. This involved, PID-iterative learning active force control (PID-ILAFC) and PID-fuzzy logic active force control (PID-FLAFC) schemes. To test the performance and robustness of these proposed hybrid control systems, several disturbance models were introduced, namely the sinusoidal wave, pulsating, and Dryden wind gust model disturbances. Integral square error was selected as the index performance to compare between the proposed control schemes. In this study, the effectiveness of the PID-ILAFC strategy in connection with the body jerk performance was investigated in the presence of applied disturbance. In terms of experimental work, hardware-in-the-loop (HIL) experimental tests were conducted for a fixed-base rotorcraft UAV system to investigate how effective are the proposed hybrid PID-ILAFC schemes in disturbance rejection. Simulated results, in time domains, reveal the efficacy of the proposed hybrid IAFC-based control methods in the cancellation of different applied disturbances, while preserving the stability of the rotorcraft system, as compared to the conventional PID controller. In most of the cases, the simulated results show a reduction of more than 55% in settling time. In terms of body jerk performance, it was improved by around 65%, for twin-rotor helicopter system, and by a 45%, for quadrotor system. To achieve the best possible performance, results recommend using the full output signal produced by the AFC strategy according to the sensitivity analysis. The HIL experimental tests results demonstrate that the PID-ILAFC method can improve the disturbance rejection capability when compared to other control systems and show good agreement with the simulated counterpart. However, the selection of the appropriate learning parameters and initial conditions is viewed as a crucial step toward this improved performance

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

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

Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System

In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated by comparing the system response with a desired reference response. The algorithm tests new solution candidates using step signals iteratively. The results showed the algorithm effectiveness to drive the system response. The simulation results illustrate that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real-time calibration problem

Robust adaptive LQR control of nonlinear system application to 3-Dof flight control system

This paper contains a new proposed regarding on robust adaptive control method merge with Linear-Quadratic Regulator (LQR), to design a faster response controller for uncertain characterized three degree of freedom (3-DOF) flight control module. 3-DOF helicopter is a bench-top module use in laboratory for experimental purposes only. From the previous experiments, it has seen that the transient response of designed PD controller has significantly very large steady state error which is around 50%. For highly uncertain plants it is highly destructive. A 3-DOF flight control system or bench-top helicopter developed by Quanser is intrinsically nonlinear, unstable and totally uncertain because of the nature of three individual angles well-known as pitch, travel and elevation. The target of this proposed control design is to improve the performance of three angles control of 3-DOF helicopter by integration of LQR controller and robust adaptive controller. Usually standard adaptive controller will produce zero steady state error. But for achieving faster response with zero steady state error is quite difficult. Therefore, this paper proposed a robust adaptive with deadbeat algorithm to overcome the limitations. Our proposal is to introduce robustness to parameter uncertainties and disturbances, by using adaptive laws for the plant parameters’ uncertainty, as a replacement for the traditional ones. This controller may handle large parameter uncertainties and disturbance with rugged stability. The arbitrary combined optimizing method is engaged in this design to optimize the overall performance of the controller. Simulation results and equations are used to demonstration the effectiveness of the proposed control methodology

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

A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions

This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural gait, lying with position changed and resting while watching TV. Then from the signals of these physiological conditions specific features exclusive to each subject were extracted employing the Cardioid graph based model. In this model, features were extracted solely from the graph derived of the QRS complexes. Subjects were recognized with Multilayer Perceptron classification algorithm. Results were obtained through two approaches. Classification was performed on the whole dataset, Cardioid graph based method resulted in 96.4% of correctly classified instances, whereas QRS complex based ECG produced 94.7% accuracy rates. Later, sensitivity and specificity analysis was done to determine the robustness of the model which produced higher outcomes for Cardioid graph based technique of 96.4% and 99.9% respectively. These results suggest that subject identification in different physiological conditions with Cardioid graph based technique produces better classification rates than that of employing only QRS complexes

Approximate Model Predictive Control for Nonlinear Multivariable Systems

The control of multi-input multi-output (MIMO) systems is a common problem in practical control scenarios. However in the last two decades, of the advanced control schemes, only linear model predictive control (MPC) was widely used in industrial process control (Ma-ciejowski, 2002). The fundamental common idea behind all MPC techniques is to rely o

Implementation of Decentralized Formation Control on Multi-Quadrotor Systems

We present real-time autonomous implementations of a practical distributed formation control scheme for a multi-quadrotor system for two different cases: parameters of linearized dynamics are exactly known, and uncertain system parameters. For first case, we design a hierarchical, decentralized controller based on the leader-follower formation approach to control a multi-quadrotor swarm in rigid formation motion. The proposed control approach has a two-level structure: high-level and low-level. At the high level, a distributed control scheme is designed with respect to the relative and global position information of the quadrotor vehicles. In the low-level, we analyze each single quadrotor control design in three parts. The first is a linear quadratic controller for the pitch and roll dynamics of quadrotors. The second is proportional controller for the yaw motion. The third is proportional-integral-derivative controller in altitude model. For the second case, where inertial uncertainties in the pitch and roll dynamics of quadrotors are considered, we design an on-line parameter estimation with the least squares approach, keeping the yaw, altitude and the high-level controllers the same as the first case. An adaptive linear quadratic controller is then designed to be used with lookup table based on the estimation of uncertain parameters. Additionally, we study on enhancement of self and inter-agent relative localization of the quadrotor agents using a single-view distance-estimation based localization methodology as a practical and inexpensive tool to be used in indoor environments for future works. Throughout the formation control implementations, the controllers successfully satisfy the objective of formation maintenance for non-adaptive and adaptive cases. Simulations and experimental results are presented considering various scenarios, and positive results obtained for the effectiveness of our algorithm