Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy

A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs) equipped with synthetic jet actuators (SJAs) is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty

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

Rotor failure compensation in a biplane quadrotor based on virtual deflection

A biplane quadrotor is a hybrid type of UAV that has wide applications such as payload pickup and delivery, surveillance, etc. This simulation study mainly focuses on handling the total rotor failure, and for that, we propose a control architecture that does not only handle rotor failure but is also able to navigate the biplane quadrotor to a safe place for landing. In this structure, after the detection of total rotor failure, the biplane quadrotor will imitate reallocating control signals and then perform the transition maneuver and switch to the fixed-wing mode; control signals are also reallocated. A synthetic jet actuator (SJA) is used as the redundancy that generates the desired virtual deflection to control the pitch angle, while other states are taken care of by the three rotors. The SJA has parametric nonlinearity, and to handle it, an inverse adaptive compensation scheme is applied and a closed-loop stability analysis is performed based on the Lyapunov method for the pitch subsystem. The effectiveness of the proposed control structure is validated using numerical simulation carried out in the MATLAB Simulink.Web of Science67art. no. 17

A Sliding Mode LCO Regulation Strategy for Dual-Parallel Underactuated UAV Systems Using Synthetic Jet Actuators

A sliding mode control- (SMC-) based limit cycle oscillation (LCO) regulation method is presented, which achieves asymptotic LCO suppression for UAVs using synthetic jet actuators (SJAs). With a focus on applications involving small UAVs with limited onboard computational resources, the controller is designed with a simplistic structure, requiring no adaptive laws, function approximators, or complex calculations in the control loop. The control law is rigorously proven to achieve asymptotic regulation of both pitching and plunging displacements for a class of systems in a dual-parallel underactuated form, where a single scalar control signal simultaneously affects two states. Since dual-parallel underactuated systems cannot be expressed in a strict feedback or cascade form, standard backstepping-based control techniques cannot be applied. This difficulty is mitigated through careful algebraic manipulation in the regulation error system development, along with innovative design of the sliding surface. A detailed model of the UAV LCO dynamics is utilized, and a rigorous analysis is provided to prove asymptotic regulation of the pitching and plunging displacements. Numerical simulation results are provided to demonstrate the performance of the control law

A Sliding Mode LCO Regulation Strategy for Dual-Parallel Underactuated UAV Systems Using Synthetic Jet Actuators

A sliding mode control- (SMC-) based limit cycle oscillation (LCO) regulation method is presented, which achieves asymptotic LCO suppression for UAVs using synthetic jet actuators (SJAs). With a focus on applications involving small UAVs with limited onboard computational resources, the controller is designed with a simplistic structure, requiring no adaptive laws, function approximators, or complex calculations in the control loop. The control law is rigorously proven to achieve asymptotic regulation of both pitching and plunging displacements for a class of systems in a dual-parallel underactuated form, where a single scalar control signal simultaneously affects two states. Since dual-parallel underactuated systems cannot be expressed in a strict feedback or cascade form, standard backstepping-based control techniques cannot be applied. This difficulty is mitigated through careful algebraic manipulation in the regulation error system development, along with innovative design of the sliding surface. A detailed model of the UAV LCO dynamics is utilized, and a rigorous analysis is provided to prove asymptotic regulation of the pitching and plunging displacements. Numerical simulation results are provided to demonstrate the performance of the control law

Adaptive and Neural Network-Based Aircraft Tracking Control with Synthetic Jet Actuators

Wing-embedded synthetic jet actuators (SJA) can be used to achieve maneuvering control in aircraft by delivering controllable airflow perturbations near the wing surface. Trajectory tracking control design for aircraft equipped with SJA is particularly challenging, since the controlling actuator itself has an uncertain dynamic model. These challenges necessitate advanced nonlinear control design methods to achieve desirable performance for SJA-based aircraft (e.g., micro air vehicles (MAVs)). In this research, adaptive and neural-network based control methods are investigated, which are specifically designed to compensate for the SJA dynamic model uncertainty and unpredictable operating conditions characters tic of real-world MAV applications. The control design methods discussed in this thesis are rigorously developed to achieve a prescribed level of trajectory tracking control performance, and numerical simulation results are presented to demonstrate the performance of the controllers in the presence of adversarial operating conditions

Robust Nonlinear Estimation and Control Applications using Synthetic Jet Actuators

Limit cycle oscillations (LCO), also known as utter, cause significant challenges in flight control of small unmanned aerial vehicles (SUAVs), and could potentially lead to structural damage and catastrophic failures. LCO can be described as vibrational motions in the rocking, pitching and plunging displacements of an aircraft wing. To address this, the use of synthetic jet actuators (SJAs) in UAV flight control systems is becoming popular as a practical alternative and to mechanical deflection surfaces. Synthetic jet actuators are promising tools for LCO suppression systems in small UAVs due to their small size, ease of operation, and low cost. Uncertainties inherent in the dynamics of the synthetic jet actuators present significant challenges in the synthetic jet actuator-based control design. Specifically, the input-output characteristic (voltage-virtual deflection angle relationship) of the synthetic jet actuators is nonlinear and contains parametric uncertainty. Further control design challenges exist in situations where multiple actuators lose effectiveness. This dissertation focuses on the suppression of limit cycle oscillations on small unmanned air vehicles using synthetic jet actuators. A brief description on how wind gust affects aircraft tracking control is presented. It shows an extension to a paper by adding the wind gust model to the system while also varying the uncertain synthetic jet actuator parameters using a Monte Carlo method. Next, a robust nonlinear control method is presented, which achieves simultaneous aircraft tracking control and limit cycle oscillation suppression using these synthetic jet actuators and a robust controller. Following that, a nonlinear LCO regulation method is presented, which uses a bank of dynamic filters to eliminate the need for pitching and plunging LCO rate measurements. Finally, an alternative method of LCO regulation control is presented, which utilizes a sliding mode observer in lieu of a bank of filters to estimate the pitching and plunging LCO rates

Recent Progress in Some Aircraft Technologies

The book describes the recent progress in some engine technologies and active flow control and morphing technologies and in topics related to aeroacoustics and aircraft controllers. Both the researchers and students should find the material useful in their work

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

Robust and Adaptive Nonlinear Control of Limit Cycle Oscillations in UAVs Using Synthetic Jet Actuators

Limit cycle oscillations (LCO), also known as utter, cause significant challenges in fight control of unmanned aerial vehicles (UAVs), and could potentially lead to structural damage and catastrophic failures. LCO can be described as vibrational motions in the pitching and plunging displacements of an aircraft wing. Even in low Reynolds number (low-Re) fight regimes, LCO can exceed the limiting boundary for safe UAV fight. Further, as practical considerations motivate the design of smaller, lighter weight UAVs, there is a growing need for UAV systems that do not require heavy mechanical actuators (e.g., ailerons). To address this, the use of synthetic jet actuators (SJAs) in UAV fight control systems is becoming popular as a practical alternative to mechanical deflection surfaces. SJAs are promising tools for LCO suppression systems in small UAVs due to their small size, ease of operation, and low cost. Uncertainties inherent in the dynamics of SJAs present significant challenges in SJA-based control design. Specifically, the input-output characteristic of SJAs is nonlinear and contains parametric uncertainty. Further control design challenges exist in situations where multiple actuators lose effectiveness. In the event of loss of effectiveness in multiple actuators, control challenges arise due to the fact that the resulting system contains fewer actuators than degrees of freedom (DOF) to be controlled (i.e., an underactuated system). Still further difficulties exist in control design for dual parallel underatuated systems, where standard backstepping-based control approaches cannot be applied. In this thesis, three nonlinear SJA-based control methods are presented, which are capable of complete (i.e., asymptotic) suppression of LCO in UAV systems containing uncertainty. An adaptive control method is presented first, which is shown to achieve asymptotic regulation of LCO for UAVs in the presence of model uncertainty and unmodelled external disturbances. Motivated by the desire to reduce the computational complexity of the closed-loop system, a structurally simplistic robust (single feedback loop) control design is presented next, which is shown to achieve asymptotic LCO regulation without the need for adaptive parameter estimation. Finally, to address the control challenges encountered in the event of actuator faults, a robust control method is presented, which achieves simultaneous suppression of the pitching and plunging displacements using only a single scalar control input. The control design presented for this underactuated scenario is also proven to completely compensate for the inherent SJA nonlinearity. Rigorous Lyapunov-based stability analyses are provided to prove the theoretical results, and numerical simulation results are provided to complement the theoretical development