Design of U-PPC-Type II for nonlinear systems

In this study, a new U-PPC-Type II (U-model Pole Placement Control Type II) control system design procedure is proposed based on the U-model principle. The objective of a U-PPC-Type II design is to determine a linear controller Gc from a specified closed loop linear transfer function Gcls . The study also compares the new design procedure with a U-PPC-Type I based design procedure. For demonstration of the effectiveness of the proposed new procedure, U-PPC-Type II is designed for both a linear dynamic model and a Hammerstein (nonlinear dynamic) model. The simulation results are presented with discussions and graphical illustrations

A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

U-model enhanced dynamic control of a heavy oil pyrolysis/cracking furnace

This paper proposes a case study in the control of a heavy oil pyrolysis/cracking furnace with a newly extended U-Model based Pole Placement Controller (U-PPC). The major work of the paper includes: 1. establishing a control oriented nonlinear dynamic model with Naphtha cracking and thermal dynamics, 2. analysing a U-model (i.e. control oriented prototype) representation of various popular process model sets, 3. designing the new U-PPC to enhance the control performance in pole placement and stabilisation, 4) taking computational bench tests to demonstrate the control system design and performance with a user-friendly step by step procedure

Morphing airfoils analysis using dynamic meshing

© 2018, Emerald Publishing Limited. Purpose: The purpose of this paper is to use dynamic meshing to perform CFD analyses of a NACA 0012 airfoil fitted with a morphing trailing edge (TE) flap when it undergoes static and time-dependent morphing. The steady CFD predictions of the original and morphing airfoils are validated against published data. The study also investigates an airfoil with a hinged TE flap for aerodynamic performance comparison. The study further extends to an unsteady CFD analysis of a dynamically morphing TE flap for proof-of-concept and also to realise its potential for future applications. Design/methodology/approach: An existing parametrization method was modified and implemented in a user-defined function (UDF) to perform dynamic meshing which is essential for morphing airfoil unsteady simulations. The results from the deformed mesh were verified to ensure the validity of the adopted mesh deformation method. ANSYS Fluent software was used to perform steady and unsteady analysis and the results were compared with computational predictions. Findings: Steady computational results are in good agreement with those from OpenFOAM for a non-morphing airfoil and for a morphed airfoil with a maximum TE deflection equal to 5 per cent of the chord. The results obtained by ANSYS Fluent show that an average of 6.5 per cent increase in lift-to-drag ratio is achieved, compared with a hinged flap airfoil with the same TE deflection. By using dynamic meshing, unsteady transient simulations reveal that the local flow field is influenced by the morphing motion. Originality/value: An airfoil parametrisation method was modified to introduce time-dependent morphing and used to drive dynamic meshing through an in-house-developed UDF. The morphed airfoil’s superior aerodynamic performance was demonstrated in comparison with traditional hinged TE flap. A methodology was developed to perform unsteady transient analysis of a morphing airfoil at high angles of attack beyond stall and to compare with published data. Unsteady predictions have shown signs of rich flow features, paving the way for further research into the effects of a dynamic flap on the flow physics

Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification

The target echo signals obtained by Synthetic Aperture Radar (SAR) and Ground Moving Target Indicator (GMTI platforms are mainly composed of two parts, the micro-Doppler signal and the target body part signal. The wheeled vehicle and the track vehicle are classified according to the different character of their micro-Doppler signal. In order to overcome the mode mixing problem in Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) is employed to decompose the original signal into a number of Intrinsic Mode Functions (IMF). The correlation analysis is then carried out to select IMFs which have a relatively high correlation with the micro-Doppler signal. Thereafter, four discriminative features are extracted and Support Vector Machine (SVM) classifier is applied for classification. The experimental results show that the features extracted after EEMD decomposition are effective, with up 90% success rate for classification using one feature. In addition, these four features are complementary in different target velocity and azimuth angles

U-Model and U-Control methodology for nonlinear dynamic systems

This study presents the fundamental concepts and technical details of a U-model-based control (U-control for short) system design framework, including U-model realisation from classic model sets, control system design procedures, and simulated showcase examples. Consequently, the framework provides readers with clear understandings and practical skills for further research expansion and applications. In contrast to the classic model-based design and model-free design methodologies, this model-independent design takes two parallel formations: (1) it designs an invariant virtual controller with a specified closed-loop transfer function in a feedback control loop and (2) it determines the real controller output by resolving the inverse of the plant U-model. It should be noted that (1) this U-control provides a universal control system design platform for many existing linear/nonlinear and polynomial/state-space models and (2) it complements many existing design approaches. Simulation studies are used as examples to demonstrate the analytically developed formulations and guideline for potential applications

Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control

This paper develops a novel U-model enhanced double sliding mode controller (UDSMC) for a quadrotor based on multiple-input and multiple-output extended-state-observer (MIMO-ESO). UDSMC is designed using Lyapunov synthesis and Hurwitz stability to not only cancel the complex dynamics and nonlinearity, but also stabilize the uncertainty and external disturbance of the underlying quadrotors. MIMO-ESO is designed to estimate the unmeasurable velocities which can reduce the impact of sensor measurement errors in practice. The difficulties associated with quadrotor velocity's measurement disturbances and uncertain aerodynamics are successfully addressed in this control design. Rigorous theoretical analysis has been carried out to determine whether the proposed control system can achieve stable trajectory tracking performance, and a comparative real-time experimental study has also been carried out to verify the better effectiveness of the proposed control system than the built-in PID control system

Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique

A robust standard gradient descent (SGD) algorithm for ARX models using the Aitken acceleration method is developed. Considering that the SGD algorithm has slow convergence rates and is sensitive to the step size, a robust and accelerative SGD (RA-SGD) algorithm is derived. This algorithm is based on the Aitken acceleration method, and its convergence rate is improved from linear convergence to at least quadratic convergence in general. Furthermore, the RA-SGD algorithm is always convergent with no limitation of the step size. Both the convergence analysis and the simulation examples demonstrate that the presented algorithm is effective

U-model-based two-degree-of-freedom internal model control of nonlinear dynamic systems

This paper proposes a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) structure with strength in nonlinear dynamic inversion, and separation of tracking design and robustness design. This approach can effectively accommodate modeling error and disturbance while removing those widely used linearization techniques for nonlinear plants/processes. To assure the expansion and applications, it analyses the key properties associated with the UTDF-IMC. For initial benchmark testing, computational experiments are conducted using MATLAB/Simulink for two mismatched linear and nonlinear plants. Further tests consider an industrial system, in which the IMC of a Permanent Magnet Synchronous Motor (PMSM) is simulated to demonstrate the effectiveness of the design procedure for potential industrial applications

Embedding human expert cognition and real-time trajectory planning in autonomous UAS

This thesis presents a new approach to compute and optimize feasible three dimensional (3D) flight trajectories using aspects of Human Decision Making (HDM) strategies, for fixed wing Unmanned Aircraft (UA) operating in low altitude environments in the presence of real time planning deadlines. The underlying trajectory generation strategy involves the application of Manoeuvre Automaton (MA) theory to create sets of candidate flight manoeuvres which implicitly incorporate platform dynamic constraints. Feasible trajectories are formed through the concatenation of predefined flight manoeuvres in an optimized manner. During typical UAS operations, multiple objectives may exist, therefore the use of multi-objective optimization can potentially allow for convergence to a solution which better reflects overall mission requirements and HDM preferences. A GUI interface was developed to allow for knowledge capture from a human expert during simulated mission scenarios. The expert decision data captured is converted into value functions and corresponding criteria weightings using UTilite Additive (UTA) theory. The inclusion of preferences elicited from HDM decision data within an Automated Decision System (ADS) allows for the generation of trajectories which more closely represent the candidate HDM’s decision strategies. A novel Computationally Adaptive Trajectory Decision optimization System (CATDS) has been developed and implemented in simulation to dynamically manage, calculate and schedule system execution parameters to ensure that the trajectory solution search can generate a feasible solution, if one exists, within a given length of time. The inclusion of the CATDS potentially increases overall mission efficiency and may allow for the implementation of the system on different UAS platforms with varying onboard computational capabilities. These approaches have been demonstrated in simulation using a fixed wing UAS operating in low altitude environments with obstacles present