Fractal Impedance for Passive Controllers

There is increasing interest in control frameworks capable of moving robots from industrial cages to unstructured environments and coexisting with humans. Despite significant improvement in some specific applications (e.g., medical robotics), there is still the need for a general control framework that improves interaction robustness and motion dynamics. Passive controllers show promising results in this direction; however, they often rely on virtual energy tanks that can guarantee passivity as long as they do not run out of energy. In this paper, a fractal attractor is proposed to implement a variable impedance controller that can retain passivity without relying on energy tanks. The controller generates a fractal attractor around the desired state using an asymptotic stable potential field, making the controller robust to discretization and numerical integration errors. The results prove that it can accurately track both trajectories and end-effector forces during interaction. Therefore, these properties make the controller ideal for applications requiring robust dynamic interaction at the end-effector.Comment: Video Available at https://youtu.be/S06_hqn3Nv

Adaptive Optimal Control of Faulty Nonlinear DC Microgrids with Constant Power Loads: Dual-Extended Kalman Filter Approach

This article investigates the problem of estimating actuator fault and states and controlling the bus voltage in direct current microgrids (DC MGs) with linear and nonlinear constant power loads (CPLs). It is considered that the DC MG states are not fully measurable and the utilized sensors are not ideal and noisy. Additionally, the actuator fault occurs and it is modeled as an additive term in the power system dynamics. These issues, including nonlinearities, un-measurable states, noisy measures, and actuator fault indispensably degrade the operation of the DC MG. To solve this issue, initially, a dual-extended Kalman filter (dual-EKF) is suggested for the fault and state estimation. It decomposes the process of estimating the state and actuator fault to reduce the online computational burden. For the control purpose, a linear parameter varying (LPV) model predictive control (MPC) is suggested to regulate the current and voltage of the DC MG. It benefits the nonlinear system modeling of LPV representation and constrained-based design procedure of the MPC to result in an accurate and low online computational burden dealing with system constraints. By deploying the overall robust adaptive dual-EKF estimation-based LPV-MPC, there is no need to have any prior knowledge of all system states and actuator faults in prior. The theoretical analysis and controller design are validated by numerical simulations on a typical islanded DC MG and comparisons are done with state-of-the-art estimation and control strategies.©2022 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.fi=vertaisarvioitu|en=peerReviewed

Evolving Systems: An Outcome of Fondest Hopes and Wildest Dreams

New theory is presented for evolving systems, which are autonomously controlled subsystems that self-assemble into a new evolved system with a higher purpose. Evolving systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control that operates through one specific component to maintain stability during the evolution. In addition, this control must often overcome persistent disturbances that occur while the evolution is in progress. Theoretical results will be presented for Adaptive Key Component control for persistent disturbance rejection. An illustrative example will demonstrate the Adaptive Key Component controller on a system composed of rigid body and flexible body modes

Historical overview of the passification method and its applications to nonlinear and adaptive control problems

The present survey paper provides a historical overview of the method of passification and its applications to nonlinear and adaptive control problems from 1980 to present days

Steering control for haptic feedback and active safety functions

Steering feedback is an important element that defines driver–vehicle interaction. It strongly affects driving performance and is primarily dependent on the steering actuator\u27s control strategy. Typically, the control method is open loop, that is without any reference tracking; and its drawbacks are hardware dependent steering feedback response and attenuated driver–environment transparency. This thesis investigates a closed-loop control method for electric power assisted steering and steer-by-wire systems. The advantages of this method, compared to open loop, are better hardware impedance compensation, system independent response, explicit transparency control and direct interface to active safety functions.The closed-loop architecture, outlined in this thesis, includes a reference model, a feedback controller and a disturbance observer. The feedback controller forms the inner loop and it ensures: reference tracking, hardware impedance compensation and robustness against the coupling uncertainties. Two different causalities are studied: torque and position control. The two are objectively compared from the perspective of (uncoupled and coupled) stability, tracking performance, robustness, and transparency.The reference model forms the outer loop and defines a torque or position reference variable, depending on the causality. Different haptic feedback functions are implemented to control the following parameters: inertia, damping, Coulomb friction and transparency. Transparency control in this application is particularly novel, which is sequentially achieved. For non-transparent steering feedback, an environment model is developed such that the reference variable is a function of virtual dynamics. Consequently, the driver–steering interaction is independent from the actual environment. Whereas, for the driver–environment transparency, the environment interaction is estimated using an observer; and then the estimated signal is fed back to the reference model. Furthermore, an optimization-based transparency algorithm is proposed. This renders the closed-loop system transparent in case of environmental uncertainty, even if the initial condition is non-transparent.The steering related active safety functions can be directly realized using the closed-loop steering feedback controller. This implies, but is not limited to, an angle overlay from the vehicle motion control functions and a torque overlay from the haptic support functions.Throughout the thesis, both experimental and the theoretical findings are corroborated. This includes a real-time implementation of the torque and position control strategies. In general, it can be concluded that position control lacks performance and robustness due to high and/or varying system inertia. Though the problem is somewhat mitigated by a robust H-infinity controller, the high frequency haptic performance remains compromised. Whereas, the required objectives are simultaneously achieved using a torque controller

Autonomous landing of fixed-wing aircraft on mobile platforms

E n esta tesis se propone un nuevo sistema que permite la operación de aeronaves autónomas sin tren de aterrizaje. El trabajo está motivado por el interés industrial en aeronaves con la capacidad de volar a gran altitud, con más capacidad de carga útil y capaces de aterrizar con viento cruzado. El enfoque seguido en este trabajo consiste en eliminar el sistema de aterrizaje de una aeronave de ala fija empleando una plataforma móvil de aterrizaje en tierra. La aeronave y la plataforma deben sincronizar su movimiento antes del aterrizaje, lo que se logra mediante la estimación del estado relativo entre ambas y el control cooperativo del movimiento. El objetivo principal de esta Tesis es el desarrollo de una solución práctica para el aterrizaje autónomo de una aeronave de ala fija en una plataforma móvil. En la tesis se combinan nuevos métodos con experimentos prácticos para los cuales se ha desarrollado un sistema de pruebas específico. Se desarrollan dos variantes diferentes del sistema de aterrizaje. El primero presta atención especial a la seguridad, es robusto ante retrasos en la comunicación entre vehículos y cumple procedimientos habituales de aterrizaje, al tiempo que reduce la complejidad del sistema. En el segundo se utilizan trayectorias optimizadas del vehículo y sincronización bilateral de posición para maximizar el rendimiento del aterrizaje en términos de requerimientos de longitud necesaria de pista, pero la estabilidad es dependiente del retraso de tiempo, con lo cual es necesario desarrollar un controlador estabilizador ampliado, basado en pasividad, que permite resolver este problema. Ambas estrategias imponen requisitos funcionales a los controladores de cada uno de los vehículos, lo que implica la capacidad de controlar el movimiento longitudinal sin afectar el control lateral o vertical, y viceversa. El control de vuelo basado en energía se utiliza para proporcionar dicha funcionalidad a la aeronave. Los sistemas de aterrizaje desarrollados se han analizado en simulación estableciéndose los límites de rendimiento mediante múltiples repeticiones aleatorias. Se llegó a la conclusión de que el controlador basado en seguridad proporciona un rendimiento de aterrizaje satisfactorio al tiempo que suministra una mayor seguridad operativa y un menor esfuerzo de implementación y certificación. El controlador basado en el rendimiento es prometedor para aplicaciones con una longitud de pista limitada. Se descubrió que los beneficios del controlador basado en el rendimiento son menos pronunciados para una dinámica de vehículos terrestres más lenta. Teniendo en cuenta la dinámica lenta de la configuración del demostrador, se eligió el enfoque basado en la seguridad para los primeros experimentos de aterrizaje. El sistema de aterrizaje se validó en diversas pruebas de aterrizaje exitosas, que, a juicio del autor, son las primeras en el mundo realizadas con aeronaves reales. En última instancia, el concepto propuesto ofrece importantes beneficios y constituye una estrategia prometedora para futuras soluciones de aterrizaje de aeronaves.In this thesis a new landing system is proposed, which allows for the operation of autonomous aircraft without landing gear. The work was motivated by the industrial need for more capable high altitude aircraft systems, which typically suffer from low payload capacity and high crosswind landing sensitivity. The approach followed in this work consists in removing the landing gear system from the aircraft and introducing a mobile ground-based landing platform. The vehicles must synchronize their motion prior to landing, which is achieved through relative state estimation and cooperative motion control. The development of a practical solution for the autonomous landing of an aircraft on a moving platform thus constitutes the main goal of this thesis. Therefore, theoretical investigations are combined with real experiments for which a special setup is developed and implemented. Two different landing system variants are developed — the safety-based landing system is robust to inter-vehicle communication delays and adheres to established landing procedures, while reducing system complexity. The performance-based landing system uses optimized vehicle trajectories and bilateral position synchronization to maximize landing performance in terms of used runway, but suffers from time delay-dependent stability. An extended passivity-based stabilizing controller was implemented to cope with this issue. Both strategies impose functional requirements on the individual vehicle controllers, which imply independent controllability of the translational degrees of freedom. Energy-based flight control is utilized to provide such functionality for the aircraft. The developed landing systems are analyzed in simulation and performance bounds are determined by means of repeated random sampling. The safety-based controller was found to provide satisfactory landing performance while providing higher operational safety, and lower implementation and certification effort. The performance-based controller is promising for applications with limited runway length. The performance benefits were found to be less pronounced for slower ground vehicle dynamics. Given the slow dynamics of the demonstrator setup, the safety-based approach was chosen for first landing experiments. The landing system was validated in a number of successful landing trials, which to the author’s best knowledge was the first time such technology was demonstrated on the given scale, worldwide. Ultimately, the proposed concept offers decisive benefits and constitutes a promising strategy for future aircraft landing solutions

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

Robust Control Methods for Nonlinear Systems with Uncertain Dynamics and Unknown Control Direction

Robust nonlinear control design strategies using sliding mode control (SMC) and integral SMC (ISMC) are developed, which are capable of achieving reliable and accurate tracking control for systems containing dynamic uncertainty, unmodeled disturbances, and actuator anomalies that result in an unknown and time-varying control direction. In order to ease readability of this dissertation, detailed explanations of the relevant mathematical tools is provided, including stability denitions, Lyapunov-based stability analysis methods, SMC and ISMC fundamentals, and other basic nonlinear control tools. The contributions of the dissertation are three novel control algorithms for three different classes of nonlinear systems: single-input multipleoutput (SIMO) systems, systems with model uncertainty and bounded disturbances, and systems with unknown control direction. Control design for SIMO systems is challenging due to the fact that such systems have fewer actuators than degrees of freedom to control (i.e., they are underactuated systems). While traditional nonlinear control methods can be utilized to design controllers for certain classes of cascaded underactuated systems, more advanced methods are required to develop controllers for parallel systems, which are not in a cascade structure. A novel control technique is proposed in this dissertation, which is shown to achieve asymptotic tracking for dual parallel systems, where a single scalar control input directly affects two subsystems. The result is achieved through an innovative sequential control design algorithm, whereby one of the subsystems is indirectly stabilized via the desired state trajectory that is commanded to the other subsystem. The SIMO system under consideration does not contain uncertainty or disturbances. In dealing with systems containing uncertainty in the dynamic model, a particularly challenging situation occurs when uncertainty exists in the input-multiplicative gain matrix. Moreover, special consideration is required in control design for systems that also include unknown bounded disturbances. To cope with these challenges, a robust continuous controller is developed using an ISMC technique, which achieves asymptotic trajectory tracking for systems with unknown bounded disturbances, while simultaneously compensating for parametric uncertainty in the input gain matrix. The ISMC design is rigorously proven to achieve asymptotic trajectory tracking for a quadrotor system and a synthetic jet actuator (SJA)-based aircraft system. In the ISMC designs, it is assumed that the signs in the uncertain input-multiplicative gain matrix (i.e., the actuator control directions) are known. A much more challenging scenario is encountered in designing controllers for classes of systems, where the uncertainty in the input gain matrix is extreme enough to result in an a priori-unknown control direction. Such a scenario can result when dealing with highly inaccurate dynamic models, unmodeled parameter variations, actuator anomalies, unknown external or internal disturbances, and/or other adversarial operating conditions. To address this challenge, a SMCbased self-recongurable control algorithm is presented, which automatically adjusts for unknown control direction via periodic switching between sliding manifolds that ultimately forces the state to a converging manifold. Rigorous mathematical analyses are presented to prove the theoretical results, and simulation results are provided to demonstrate the effectiveness of the three proposed control algorithms