Adaptive fuzzy proportional-integral-derivative control for micro aerial vehicle

With multiple industries employing Micro Aerial Vehicles (MA V) to accomplish various tasks comprising agricultural spraying, package delivery and disaster monitoring, the MA V system has attracted researchers towards resolving its stability issue as emerged from external disturbances. Disruptions caused by both wind and payload change disturbances have prevailed as natural mishaps which degrade performance of the quadrotor MA V system at the horizontal and vertical positions in the aspects of overshoot (OS), rise time (Tr), settling time (Ts)and steady-state error (ess)· Such adversities then cause increased error between the system's desired and actual positions, with a longer rise time and settling time towards reaching its steady-state condition. Adopting the rotary wing quad-rotor MAV system with 'X' configuration as the groundwork, the current study has especially set to explore a new approach for the system's robust positional control in the concurrent presence of wind and payload change disturbances. Earlier literatures have simultaneously suggested the adoptions of linear, nonlinear and hybrid approaches towards handing stability challenge of the quad-rotor MA V. Notably, most hybrid approaches are unable to account for current changes in the system's environment, whilst incapable of concomitantly handle multiple disturbances. An instance being the Fuzzy-PID (FPID) method which merely adjusts the Proportional-Integral-Derivative (PID) gains ensuing discovered positional error from emergence of system's overshoot. Acknowledging such incompetency, this research further proposed Adaptive Fuzzy-PlD (AFPID) controller as the contemporary hybrid approach that includes adaptability function for overcoming nonlinearity of the quad-rotor MA V system, while maintaining the system's robust performance facing current environmental changes from simultaneous wind and payload change disturbances. With the proposed adaptive fuzzy control being adopted to adjust the PID gains in accordance to surrounding changes, undertaken improvement is hereby targeted to eliminate the effect of wind and payload change disturbances amidst stabilizing the employed system. In return, encountered error on both the quad-rotor MA V's horizontal and vertical positions is expected to decline despite concurrent bombardment of multiple external disturbances, following a decrease to the system's overshoot (OS), rise time (Tr), settling time (Ts)and steady-state error (ess). In simulation, performance of the proposed AFPID controller on the horizontal, y position as studied under circumstances of different incoming wind velocities and water flow rates with respect to OS, Tr, Ts and e55 is placed in comparison to the performance of the PID and FPID methods. Improvement is observed in the system's ess for the AFPID controller on the horizontal, y position amid disruption of combined disturbances, with respective reductions of0.93 x 10-3 % and 1.35 X 10-3 % over the performances of PID and FPID controllers. Obtained results then confirm corresponding decline of 27.5% and 21.70% in OS for the AFPID controller over the PID and FPID controllers. A decline of 13 7.50 s and 13.40 s in Ts is further recorded for the AFPID controller as compared to the respective PID and FPID controllers. Accumulated findings, thus, validate AFPID as an effective controller for minimized positional error, smaller overshoot (OS) and steady-state error (esJ, as well as shorter settling time (Ts) and rise time (Tr) as compared to the earlier PID and FPID controllers when faced with uncertain situations of wind and payload change disturbances

Suspended Load Path Tracking Control Using a Tilt-rotor UAV Based on Zonotopic State Estimation

This work addresses the problem of path tracking control of a suspended load using a tilt-rotor UAV. The main challenge in controlling this kind of system arises from the dynamic behavior imposed by the load, which is usually coupled to the UAV by means of a rope, adding unactuated degrees of freedom to the whole system. Furthermore, to perform the load transportation it is often needed the knowledge of the load position to accomplish the task. Since available sensors are commonly embedded in the mobile platform, information on the load position may not be directly available. To solve this problem in this work, initially, the kinematics of the multi-body mechanical system are formulated from the load's perspective, from which a detailed dynamic model is derived using the Euler-Lagrange approach, yielding a highly coupled, nonlinear state-space representation of the system, affine in the inputs, with the load's position and orientation directly represented by state variables. A zonotopic state estimator is proposed to solve the problem of estimating the load position and orientation, which is formulated based on sensors located at the aircraft, with different sampling times, and unknown-but-bounded measurement noise. To solve the path tracking problem, a discrete-time mixed $\mathcal{H}_2/\mathcal{H}_\infty$ controller with pole-placement constraints is designed with guaranteed time-response properties and robust to unmodeled dynamics, parametric uncertainties, and external disturbances. Results from numerical experiments, performed in a platform based on the Gazebo simulator and on a Computer Aided Design (CAD) model of the system, are presented to corroborate the performance of the zonotopic state estimator along with the designed controller

Data-driven system identification and model predictive control of a multirotor with an unknown suspended payload

Thesis (MEng)--Stellenbosch University, 2022.ENGLISH ABSTRACT: This thesis considers the problem of stabilised control for a multirotor with an unknown suspended payload. The swinging payload negatively affects the multirotor flight dynamics by inducing oscillations in the system. An adaptive control architecture is proposed to damp these oscillations and produce stable flight with different unknown payloads. The architecture includes a data-driven system identification method that assumes no prior knowledge of the payload dynamics. This method is demonstrated in simulation and with practical flight data. Model Predictive Control (MPC) is applied for swing damping control and is verified with Hardware-in-the-Loop (HITL) simulations. A parameter estimator and Linear Quadratic Regulator (LQR) is used as a baseline control architecture. The LQR uses a predetermined model of the system, which is completed with estimates of the payload mass and cable length. The newly proposed architecture uses Dynamic Mode Decomposition with Control (DMDc) to estimate a linear state-space model and approximate the dynamics without using a predetermined model. The architecture was also tested with a Hankel Alternative View Of Koopman (HAVOK) algorithm which was extended in this work to account for control. An MPC uses the data-driven model to control the multirotor and damp the payload oscillations. A Simulink™ simulator was designed and verified with practical data. Within simulations both the baseline and proposed architectures produced near swing-free control with different payload masses and cable lengths. Even with a dynamic payload producing irregular oscillations, both methods achieved stabilised control. Both architectures also showed effective disturbance rejection. Despite the baseline method using an accurate predetermined model, the proposed method produced equal performances without prior knowledge of the dynamics. The baseline performance degraded significantly with a changed multirotor mass because this parameter was not considered as an unknown. In contrast, the proposed method consistently produced good performances. The accuracy of the DMDc models was verified with practical flight data. The proposed control architecture was also demonstrated in HITL simulations. The hardware executed the MPC at the desired frequency, producing near swing-free control within a Gazebo simulator. Overall, it was shown that the proposed control architecture is practically feasible. Without knowledge of the payload dynamics, a data-driven model can be used with MPC for effective swing damping control with a multirotor.AFRIKAANSE OPSOMMING: Hierdie tesis hanteer die probleem van gestabiliseerde beheer vir ’n multirotor hommeltuig met ’n onbekende hangende loonvrag. Die swaaiende loonvrag be¨ınvloed die vlugdin amika deur ossillasies in die stelsel te veroorsaak. ’n Aanpasbare beheerargitektuur word voorgestel om hierdie ossillasies te demp vir stabiele vlugte met verskillende onbekende loonvragte. Die argitektuur maak gebruik van ’n datagedrewe stelsel-identifikasiemetode wat geen voorafkennis van die loonvragdinamika gebruik nie. Hierdie metode word in simulasies en met praktiese vlugdata gedemonstreer. Model Voorspellende Beheer (MVB) word toegepas vir swaaidempingsbeheer en word geverifieer met Hardeware-in-die-Lus (HIDL) simulasies. ’n Parameter-afskatter en Lineˆere Kwadratiese Gaussiese (LKG) word in die basislyn beheerargitektuur gebruik. Die LKG gebruik ’n voorafbepaalde model van die sisteem wat voltooi word met afskattings van die loonvragmassa en kabellengte. Die nuwe voorgestelde argitektuur gebruik Dinamiese Modus Ontbinding met beheer (DMOb) om ’n lineˆere toestand-ruimte model te bereken en die dinamika af te skat sonder ’n voorafbepaalde model. Die argitektuur is ook getoets met ’n Hankel Alternatiewe Siening van Koopman (HASK)-algoritme wat in hierdie werk uitgebrei is om beheer in te sluit. ’n MVB gebruik die data-gedrewe model om die multirotor te beheer en die loonvrag se ossillasies te demp. ’n Simulink™-simululeerder is ontwerp en geverifieer met praktiese data. In simulasies het beide die basislyn en voorgestelde argitekture byna-swaaivrye beheer met verskillende loon vragmassas en kabellengtes geproduseer. Selfs met ’n dinamiese loonvrag wat onre¨elmatige ossillasies voortbring, het beide metodes gestabiliseerde beheer tot gevolg gehad. Beide ar gitekture het ook effektiewe versteuringsverwerping getoon. Al gebruik die basislynmetode ’n akkurate voorafbepaalde model, het die voorgestelde metode gelyke prestasies gelewer sonder voorafkennis van die dinamika. Die basislyn prestasie het aansienlik afgeneem vir ’n aangepaste multirotormassa omdat hierdie parameter nie as ’n onbekende beskou is nie. Daarteenoor het die voorgestelde metode deurgaans goeie prestasies gelewer. Die akkuraatheid van die DMOb modelle is geverifieer met praktiese vlugdata. Die voorgestelde beheerargitektuur is ook in HIDL-simulasies gedemonstreer. MVB is teen die verlangde frekwensie uitgevoer en het byna-swaaivrye beheer in ’n Gazebo-simululeerder gelewer. In die geheel is dit gewys dat die voorgestelde beheerargitektuur prakties uitvoerbaar is. Sonder kennis van die loonvragdinamika kan ’n data-gedrewe model met MVB gebruik word vir effektiewe swaaidempingsbeheer met ’n multirotor.Master

Robust nonlinear trajectory controllers for a single-rotor UAV with particle swarm optimization tuning

This paper presents the utilization of robust nonlinear control schemes for a single-rotor unmanned aerial vehicle (SR-UAV) mathematical model. The nonlinear dynamics of the vehicle are modeled according to the translational and rotational motions. The general structure is based on a translation controller connected in cascade with a P-PI attitude controller. Three different control approaches (classical PID, Super Twisting, and Adaptive Sliding Mode) are compared for the translation control. The parameters of such controllers are hard to tune by using a trial-and-error procedure, so we use an automated tuning procedure based on the Particle Swarm Optimization (PSO) method. The controllers were simulated in scenarios with wind gust disturbances, and a performance comparison was made between the different controllers with and without optimized gains. The results show a significant improvement in the performance of the PSO-tuned controllers.Peer ReviewedPostprint (published version

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

Improving Leader-Follower Formation Control Performance for Quadrotors

This thesis aims to improve the leader-follower team formation flight performance of Unmanned Aerial Vehicles (UAVs) by applying nonlinear robust and optimal techniques, in particular the nonlinear H_infinity and the iterative Linear Quadratic Regulator (iLQR), to stabilisation, path tracking and leader-follower team formation control problems. Existing solutions for stabilisation, path tracking and leader-follower team formation control have addressed a linear or nonlinear control technique for a linearised system with limited disturbance consideration, or for a nonlinear system with an obstacle-free environment. To cover part of this area of research, in this thesis, some nonlinear terms were included in the quadrotors' dynamic model, and external disturbance and model parameter uncertainties were considered. Five different controllers were developed. The first and the second controllers, the nonlinear suboptimal H_infinity control technique and the Integral Backstepping (IBS) controller, were based on Lyapunov theory. The H_infinity controller was developed with consideration of external disturbance and model parameter uncertainties. These two controllers were compared for path tracking and leader-follower team formation control. The third controller was the Proportional Derivative square (PD2), which was applied for attitude control and compared with the H_infinity controller. The fourth and the fifth controllers were the Linear Quadratic Regulator (LQR) control technique and the optimal iLQR, which was developed based on the LQR control technique. These were applied for attitude, path tracking and team formation control and there results were compared. Two features regarding the choice of the control technique were addressed: stability and robustness on the one hand, which were guaranteed using the H_infinity control technique as the disturbance is inherent in its mathematical model, and the improvement in the performance optimisation on the other, which was achieved using the iLQR technique as it is based on the optimal LQR control technique. Moreover, one loop control scheme was used to control each vehicle when these controllers were implemented and a distributed control scheme was proposed for the leader-follower team formation problem. Each of the above mentioned controllers was tested and verified in simulation for different predefined paths. Then only the nonlinear H_infinity controller was tested in both simulation and real vehicles experiments

Nonlinear control and perturbation compensation in UAV quadrotor

The great interest in the field of flying robotics encouraged a lot of research work to improve its control strategies. This thesis is about modelling and design of controllers and perturbation compensators for a UAV quadrotor. Four approaches are built in this purpose. The first approach is perturbation attenuation system in a UAV quadrotor. Hierarchical Perturbation Compensator (HPC) is built to compensate for system uncertainties, non-modelled dynamics and external disturbances. It comprises three subsystems designed to provide continuous and precise estimation of perturbation. Each subsystem is designed to avoid the drawbacks of the other. This approach has superior proficiency to decrease unknown perturbation either external or internal. The second approach is a Three Loop Uncertainties Compensator (TLUC), designed to estimate unknown time- varying uncertainties and perturbations to reduce their effects and in order to preserve stability. The novelty of this approach is that the TLUC can estimate and compensate for uncertainties and disturbances in three loops made to provide tracking to residual uncertainty in order to achieve a higher level of support to the controller. Exponential reaching law sliding mode controller is proposed and applied. It is integrated based on Lyapunov stability theory to obtain fast response with lowest possible chattering. The performance is verified through analyses, simulations and experiments. The third approach is Feedback Linearization based on Sliding Mode Control (FLSMC). The purpose is to provide nonlinear control that reduces the effect of the highly coupled dynamic behavior and the hard nonlinearity in the quadrotor. The proposed controller uses a Second Order sliding mode Exact Differentiator SOED to estimate the velocity and the acceleration. The fourth approach proposes an improved Non-Singular Terminal Super-Twisting Control for the problem of position and attitude tracking of quadrotor systems. The super-twisting algorithm is an effective control used to provide high precision and less chattering. The proposed method is based on a non-singular terminal sliding surface with new exponent that solves the problem of singularity in terminal sliding mode control. Design procedure and the stability analysis using Lyapunov theory are detailed for the considered approaches. The performance is verified through analyses, simulations and experiments

Helicopter Acoustics

Exterior and interior noise problems are addressed both from the physics and engineering as well as the human factors point of view. The role of technology in closing the gap between what the customers and regulating agencies would like to have and what is available is explored. Noise regulation concepts, design, operations and testing for noise control, helicopter noise prediction, and research tools and measurements are among the topics covered

Investigations in multi-resolution modelling of the quadrotor micro air vehicle

Multi-resolution modelling differs from standard modelling in that it employs multiple abstractions of a system rather than just one. In describing the system at several degrees of resolution, it is possible to cover a broad range of system behaviours with variable precision. Typically, model resolution is chosen by the modeller, however the choice of resolution for a given objective is not always intuitive. A multi-resolution model provides the ability to select optimal resolution for a given objective. This has benefits in a number of engineering disciplines, particularly in autonomous systems engineering, where the behaviours and interactions of autonomous agents are of interest. To investigate both the potential benefits of multi-resolution modelling in an autonomous systems context and the effect of resolution on systems engineering objectives, a multi-resolution model family of the quadrotor micro air vehicle is developed. The model family is then employed in two case studies. First, non-linear dynamic inversion controllers are derived from a selection of the models in the model family, allowing the impact of resolution on a model-centric control strategy to be investigated. The second case study employs the model family in the optimisation of trajectories in a wireless power transmission. This allows both study of resolution impact in a multi-agent scenario and provides insight into the concept of laser-based wireless power transmission. In addition to the two primary case studies, models of the quadrotor are provided through derivation from first principles, system identification experiments and the results of a literature survey. A separate model of the quadrotor is employed in a state estimation experiment with low-fidelity sensors, permitting further discussion of both resolution impact and the benefits of multi-resolution modelling. The results of both the case studies and the remainder of the investigations highlight the primary benefit of multi-resolution modelling: striking the optimal balance between validity and efficiency in simulation. Resolution is demonstrated to have a non-negligible impact on the outcomes of both case studies. Finally, some insights in the design of a wireless power transmission are provided from the results of the second case study