On UAV Robust Nonlinear Control in Presence of Parametric Uncertainties

We examine a new robust nonlinear flight control technology that employs an array of synthetic-jet micro-actuators embedded in UAV wing design in order to completely eliminate moving parts (such as ailerons) thus greatly enhancing maneuverability required for small fixed-wing air vehicles operating, e.g., in tight urban environments. Estimated fast response times are critical in mitigating gust effects while greatly improving flight stability and control. The new controller design is particularly advantageous for high levels of uncertainty and nonlinearity present both in the unsteady flowpath environment and in the embedded actuator’s response. The current work focuses on a benchmark case of flutter control of 2- DOF elastically-mounted airfoil entering limit-cycle oscillations (LCO) due to impinging upstream flow disturbance. Preliminary parametric studies conducted for various SJA excitation amplitudes and frequencies examine the thresholds of the actuator’s control authority to produce a desirable impact

Quadrotor Swarm Arena (QuaSAr) Development of a Swarm Control Testbed

Swarm control systems are increasingly popular in the robotics industry and academia due to their many potential applications. The goal of the Quadrotor Swarm Arena (QuaSAr) project is to construct a quadrotor swarm control testbed to provide researchers with the tools needed to experimentally investigate this emerging science. This testbed is equipped with a motion capture system, test control station, and numerous quadrotor UAVs. MATLAB-Simulink is utilized for control law development, data processing, and test control. This configuration allows researchers to test developing control law in a \u27plug and play\u27 manner as control development and test control are all completed using the same tools. Thus, the QuaSAr testbed an increasingly valuable tool to a wide set of researchers. Currently, the testbed is undergoing final testing and initial operation. Improved single-agent control methods are continuously being developed and initial swarm control research is underway. The combination of the completed and future work has promising implications for the continued success of the QuaSAr project

QUASAR: An Experimental Test Bed for Autonomous Multi-Agent Control

The QUAdrotor Swarm ARena (QUASAR) is an experimental test bed for autonomous multi-agent unmanned aerial vehicle (UAV) control systems. The development of QUASAR is motivated by the desire to experimentally test and validate new hardware-in-the-loop multi-agent control methods. A key focus of the project is on investigating the performance comparisons between linear and nonlinear multi-agent control methods under realistic operating conditions. Preliminary numerical simulations using MATLAB/Simulink indicate that nonlinear control methods more effectively compensate for unpredictable disturbances and dynamic model uncertainty. However, the results also suggest that standard linear control methods offer the benefit of ease of implementation. In addition to the control design trade-offs, preliminary experimental results have demonstrated the practical trade-offs that exist in using different inter-agent wireless communication protocols (e.g., radio versus Wi-Fi). Ongoing research efforts include experimentally testing new hardware-in-the-loop multi-agent UAV control methods that effectively compensate for disturbances and uncertain dynamics (e.g., unmodelled wind gusts). It is expected that this research project will provide increased potential for multi-agent UAV implementation in military and civilian applications, which achieve reliable performance under the unpredictable and potentially adversarial operating conditions encountered in real-world operating conditions

Adaptive Nonlinear Regulation Control of Thermoacoustic Oscillations in Rijke-Type Systems

Adaptive nonlinear control of self-excited oscillations in Rijke-type thermoacoustic systems is considered. To demonstrate the methodology, a well-accepted thermoacoustic dynamic model is introduced, which includes arrays of sensors and monopole-like actuators. To facilitate the derivation of the adaptive control law, the dynamic model is recast as a set of nonlinear ordinary differential equations, which are amenable to control design. The control-oriented nonlinear model includes unknown, unmeasurable, nonvanishing disturbances in addition to parametric uncertainty in both the thermoacoustic dynamic model and the actuator dynamic model. To compensate for the unmodeled disturbances in the dynamic model, a robust nonlinear feedback term is included in the control law. One of the primary challenges in the control design is the presence of input-multiplicative parametric uncertainty in the dynamic model for the control actuator. This challenge is mitigated through innovative algebraic manipulation in the regulation error system derivation along with a Lyapunov-based adaptive control law. To address practical implementation considerations, where sensor measurements of the complete state are not available for feedback, a detailed analysis is provided to demonstrate that system observability can be ensured through judicious placement of pressure (and/or velocity) sensors. Based on this observability condition, a sliding-mode observer design is presented, which is shown to estimate the unmeasurable states using only the available sensor measurements. A detailed Lyapunov-based stability analysis is provided to prove that the proposed closed-loop active thermoacoustic control system achieves asymptotic (zero steady-state error) regulation of multiple thermoacoustic modes in the presence of the aforementioned model uncertainty. Numerical Monte Carlo-type simulation results are also provided, which demonstrate the performance of the proposed closed-loop control system under various sets of operating conditions

Observer-Based Sliding Mode Control of Rijke-Type Combustion Instability

Observer-based sliding mode control of combustion instability in a Rijke-type thermoacoustic system is considered. A commonly used thermoacoustic model with sensors and monopole-like actuators is linearized and formulated in a statespace form. It is assumed that the velocity or pressure sensor locations are chosen to assure the observability of the system. An observer-based sliding mode controller is then implemented to tune the actuators so that the system is asymptotically stable. The effectiveness of the controller is illustrated through a simulation example involving two modes and one sensor. The successful demonstration indicates that the observer-based feedback controller can be applied to a real combustion system with multiple modes

Robust Nonlinear Tracking Control for Unmanned Aircraft in the Presence of Wake Vortex

The flight trajectory of unmanned aerial vehicles (UAVs) can be significantly affected by external disturbances such as turbulence, upstream wake vortices, or wind gusts. These effects present challenges for UAV flight safety. Hence, addressing these challenges is of critical importance for the integration of unmanned aerial systems (UAS) into the National Airspace System (NAS), especially in terminal zones. This work presents a robust nonlinear control method that has been designed to achieve roll/yaw regulation in the presence of unmodeled external disturbances and system nonlinearities. The data from NASA-conducted airport experimental measurements as well as high-fidelity Large Eddy Simulations of the wake vortex are used in the study. Side-by-side simulation comparisons between the robust nonlinear control law and both linear H∞ role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; font-size: 13.2px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(34, 34, 34); font-family: Arial, Arial, Helvetica, sans-serif; position: relative; \u3eH∞�∞ and PID control laws are provided for completeness. These simulations are focused on applications involving small UAV affected by the wake vortex disturbance in the vicinity of the ground (which models the take-off or landing phase) as well as in the out-of-ground zone. The results demonstrate the capability of the proposed nonlinear controller to asymptotically reject wake vortex disturbance in the presence of the nonlinearities in the system (i.e., parametric variations, unmodeled, time-varying disturbances). Further, the nonlinear controller is designed with a computationally efficient structure without the need for the complex calculations or function approximators in the control loop. Such a structure is motivated by UAV applications where onboard computational resources are limited

Reduced-order Dynamic Modeling and Robust Nonlinear Control of Fluid Flow Velocity Fields

A robust nonlinear control method is developed for fluid flow velocity tracking, which formally addresses the inherent challenges in practical implementation of closed-loop active flow control systems. A key challenge being addressed here is flow control design to compensate for model parameter variations that can arise from actuator perturbations. The control design is based on a detailed reduced-order model of the actuated flow dynamics, which is rigorously derived to incorporate the inherent time-varying uncertainty in the both the model parameters and the actuator dynamics. To the best of the authors’ knowledge, this is the first robust nonlinear closed-loop active flow control result to prove exponential tracking control of a reduced-order actuated flow dynamic model, which formally incorporates input-multiplicative time-varying parametric uncertainty and nonlinear coupling between the state and control signal. A rigorous Lyapunov-based stability analysis is utilized to prove semiglobal exponential tracking of a desired flow field velocity profile over a given spatial domain. A detailed comparative numerical study is provided, which demonstrates the performance improvement that is achieved using the proposed robust nonlinear flow control method to compensate for model uncertainty and uncertain actuator dynamics

Adaptive Modified RISE-based Quadrotor Trajectory Tracking with Actuator Uncertainty Compensation

This paper presents an adaptive robust nonlinear control method, which achieves reliable trajectory tracking control for a quadrotor unmanned aerial vehicle in the presence of gyroscopic effects, rotor dynamics, and external disturbances. Through novel mathematical manipulation in the error system development, the quadrotor dynamics are expressed in a control-oriented form, which explicitly incorporates the uncertainty in the gyroscopic term and control actuation term. An adaptive robust nonlinear control law is then designed to stabilize both the position and attitude loops of the quadrotor system. A rigorous Lyapunov-based analysis is utilized to prove asymptotic trajectory tracking, where the region of convergence can be made arbitrarily large through judicious control gain selection. Moreover, the stability analysis formally addresses gyroscopic effects and actuator uncertainty. To illustrate the performance of the control law, comparative numerical simulation results are provided, which demonstrate the improved closed-loop performance achieved under varying levels of parametric uncertainty and disturbance magnitudes

On Safety Assessment of Novel Approach to Robust UAV Flight Control in Gusty Environments

In a follow-up to our previous study, the current work examines the gust-induced “cone of uncertainty” in a small unmanned aerial vehicle’s (UAV) flight trajectory addressed in the context of safety assessments of UAV operations. Such analysis is a critical facet of the integration of unmanned aerial systems (UAS) into the National Airspace System (NAS), particularly in terminal airspace. The paper describes a predictive, robust feedback-loop flight control model that is applicable to various classes of UAVs and unsteady flight-path scenarios. The control design presented in this paper extends previous research results by demonstrating asymptotic (zero steady-state error) altitude regulation control in the presence of unmodeled vertical wind gust disturbances. To address the practical considerations involved in small UAV applications with limited computational resources, the proposed control method is designed with a computationally simplistic structure, without the requirement of complex calculations or function approximators in the control loop. Proof of the theoretical result is summarized, and detailed numerical simulation results are provided, which demonstrate the capability of the proposed nonlinear control method to asymptotically reject wind gust disturbances and parameter variations in the state space model. Simulation comparisons with a standard linear control method are provided for completeness

Finite-Time State Estimation for an Inverted Pendulum under Input-Multiplicative Uncertainty

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous analysis of the finite-time state estimator under input-multiplicative parametric uncertainty in addition to a comparative numerical study that quantifies the performance improvement that is achieved by formally incorporating the proposed compensator for input-multiplicative parametric uncertainty in the observer. In summary, our results show performance improvements when applied to both SMC- and LQR-based control systems, with results that include a reduction in the root-mean square error of up to 39% in translational regulation control and a reduction of up to 29% in pendulum angular control