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

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

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

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

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

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

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

Nonlinear Estimation and Control Methods for Mechanical and Aerospace Systems under Actuator Uncertainty

Air flow velocity field control is of crucial importance in aerospace applications to prevent the potentially destabilizing effects of phenomena such as cavity ow oscillations, flow separation, flow-induced limit cycle oscillations (LCO) (flutter), vorticity, and acoustic instabilities. Flow control is also important in aircraft applications to reduce drag in aircraft wings for improved flight performance. Although passive flow control approaches are often utilized due to their simplicity, active flow control (AFC) methods can achieve improved flight performance over a wider range of time-varying operating conditions by automatically adjusting their level of control actuation in response to real-time sensor measurements. Although several methods for AFC have been presented in recent literature, there remain numerous challenges to be overcome in closed-loop nonlinear AFC design. Additional challenges arise in control design for practical systems with limited onboard sensor measurements and uncertain actuator dynamics. In this thesis, robust nonlinear control methods are developed, which are rigorously proven to achieve reliable control of fluid flow systems under uncertain, time-varying operating conditions and actuator model uncertainty. Further, to address the practical control design challenges resulting from sensor limitations, this thesis research will investigate and develop new methods of sliding mode estimation, which are shown to achieve finite-time state estimation for systems with limited onboard sensing capabilities. The specific contributions presented in this thesis include: 1) the application of proper orthogonal decomposition (POD)-based model order reduction techniques to develop simplified, control-oriented mathematical models of actuated fluid flow dynamic systems; 2) the rigorous development of nonlinear closed-loop active flow control techniques to achieve asymptotic regulation of fluid flow velocity fields; 3) the design of novel sliding mode estimation and control methods to regulate fluid flow velocity fields in the presence of actuator uncertainty; 4) the design of a nonlinear control method that achieves simultaneous fluid flow velocity control and LCO suppression in a flexible airfoil; and 5) the analysis of a discontinuous hierarchical sliding mode estimation method using a differential inclusions-based technique

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