Dynamic Inversion Research Articles

Exploring the impact of surfactant types and formulation variables on the EACN of crude and model oils

Characterizing the hydrophobicity of oils remains a significant challenge for the academic and industrial scientific communities, striving to optimize the formulation of Surfactant/Oil/Water (SOW) systems. Various descriptors, including the required Hydrophilic-Lipophilic Balance (required HLB) and the Equivalent Alkane Carbon Number (EACN), have been proposed to characterize oil hydrophobicity. Indeed, it is already known that the EACN of crude oils can be rapidly determined through dynamic Phase Inversion Temperature-induced (PIT) experiments. The study herein presents an alternative method to characterize the EACN of crude and model oils through dynamic Salinity-induced Phase Inversion (SPI) using two reference SOW systems, one with the ionic extended surfactant propyl heptyl propoxylated sodium sulfate (i-C3C7PO4SO4Na) and the other with the nonionic surfactant decyl tetraethylene glycol ether (C10EO4). Results reveal that the EACN of crude and model oils strongly depend not only on the chosen formulation variable but also on the nature of the surfactant. Discrepancies in EACN values for crude oils range between −0.2 and 3.3 units. These differences are justified by several factors: the segregation of the polar fraction for crude oils and its dependence with temperature, the high solubility of the nonionic surfactant in polar oils and the differing structures of both surfactants at the interface that changes the effective packing parameter of the system. When inversing a crude oil at high salinity conditions using temperature as formulation variable, a weighted average EACN value obtained with salinity from the two surfactants yields more realistic results than the EACN obtained from PIT. These findings found a direct application in the enhanced oil recovery field in which the attainment of ultra-low interfacial tension is essential to have an efficient crude oil desaturation.

Finite-Time Attitude Control of Quadrotor Unmanned Aerial Vehicle with Disturbance and Actuator Saturation

This paper introduces a nonlinear dynamic inversion control algorithm designed to address unknown disturbances and actuator saturation issues in unmanned aerial vehicle (UAV) attitude control. The algorithm is based on a combination of finite-time disturbance observer and anti-saturation auxiliary system, which ensures the rapid convergence of attitude tracking error. Firstly, based on the Newton–Euler equations, this paper establishes a model of the attitude system for quadrotor UAVs, and this paper eliminates the small-angle flight assumption. Secondly, considering the actuator saturation problem, an anti-saturation auxiliary control system is designed to shorten the time when the control volume is in the saturation interval and achieve finite-time convergence of the attitude error. And then, to improve the robustness of the controller, this paper proposes a disturbance observer based on the finite-time stability theory, which achieves a continuous smooth output of the observation results by introducing a hyperbolic tangent function in the observer, so that the observation error can be converged to zero in a finite time. Finally, it is demonstrated by Simulink simulation that the attitude error and the observation error converge quickly to zero.

Flight control design for a hypersonic waverider configuration: A non-linear model following control approach

AbstractDLR is currently investigating the potential of hypersonic flight systems in the context of different mission scenarios. One configuration type of higher interest for civil and military purposes is the hypersonic glide vehicle (HGV). Such HGVs operate over broad flight envelopes and pose complex flight dynamic characteristics. This article presents DLR’s generic hypersonic glide vehicle 2 (GHVG-2) and proposes an integrated non-linear flight control architecture that is based on the idea of the non-linear dynamic inversion and non-linear model following control methodologies. The proposed control scheme is designed to sufficiently and robustly handle the system dynamics of the over-actuated flight vehicle. The approach is first discussed, and the performance of the suggested control laws is later investigated via simulations of a high-fidelity non-linear flight dynamic model in the nominal case and under the presence of parametric uncertainties. The presented results demonstrate that the proposed NMFC approach provides benefits for the robust control of the regarded hypersonic system.

Decoupled incremental nonlinear dynamic inversion control for aircraft autonomous landing with ground-effect

Due to motion coupling and increased model dependence, the use of nonlinear controllers in real-time applications for aircraft is extremely constrained. This explains why proportional, derivative, and integral (PID) controls are frequently used in practice. However, fast changes in the commanded path and the requirement for high accuracy and tracking performance limit use of PID in landing. This paper presents a design of a decoupled incremental nonlinear dynamic inversion (INDI) controller for performing autonomous landing of a fixed-wing aircraft. The investigation is carried out using the ground effect model and is compared without it. A carrot chasing guidance algorithm is implemented for waypoint navigation to generate the command for the proposed controller's outer loop. The navigational state estimate issue has been resolved using the Cubature Kalman Filter (CKF) approach. Two decoupled CKF algorithms named complementary Cubature Kalman Filter (CCKF) and Integrated Cubature Kalman Filter (I-CKF) are proposed to estimate aircraft navigational states comprised of attitudes, navigational position in terms of latitude, longitude altitudes, and North-East-down velocities. The mathematical model for flare and approach trajectory is designed and commanded to follow the same by the proposed INDI controller. The effectiveness of INDI have been evaluated in a simulation environment by landing the aircraft in the same runway position at arbitrary wind conditions. The performance of the proposed INDI controller is juxtaposed with a conventional proportional integrator and derivative (PID) based landing controller. The simulation findings demonstrate that the INDI has a competitive edge over traditional PID approaches due to its robust performance, less dependence on model dynamics, and fast command tracking capability required during the flare phase.

Fixed-time convergence ZNN model for solving rectangular dynamic full-rank matrices inversion

The Moore–Penrose inverse of dynamic matrices has found widespread application and has garnered significant attention. The zeroing neural network (ZNN) has proven to be an effective solution for computing the Moore–Penrose inverse in dynamic matrices. This paper proposes a novel unified fixed-time ZNN (UFTZNN) model designed to achieve fixed-time convergence and solve both left and right inverse problems using a single model. Theoretical analysis of the convergence and robustness of the UFTZNN model is rigorously presented. Numerical simulations comparing the UFTZNN with existing ZNN models confirm its superiority in addressing left and right inverse problems, convergence time, and robustness. The UFTZNN model is applied to the inverse kinematic tracking problem of a six-degree-of-freedom manipulator-based photoelectric tracking system to demonstrate its potential applications and effectiveness.

Dynamic inversion and correction of ammonia pressure within the range 6611–6614 cm−1

Laser absorption spectroscopy is widely applied in gas concentration detection while the measurement accuracy would be affected by fluctuations in the environmental pressure (pressure fluctuations inside the gas cell under vacuum conditions). In this paper, a dynamic inversion and correction method of gas pressure without pressure sensors was proposed. Ammonia within the range of 6611–6614 cm−1 was selected as the research object. In contrast to previous reports, this method does not investigate the effect of pressure on gas concentration detection from a single point of view, or obtain pressure values from pressure sensors. Instead, the real-time temperature was measured to determine the broadening coefficient, which was then utilized along with full width at half-maximum (FWHM) of the spectral lines to calculate the real-time pressure value before correction. The directly acquired pressure has an error, and based on the error analysis, the pressure is corrected to get the corrected real-time pressure value. Finally, the effect of systematic error was eliminated by correcting the concentration using the corrected real-time pressure value and the measured real-time temperature. Experimental results show that the average residual of the corrected real-time pressure compared to the measured true values was 0.1993 torr with a standard deviation of 0.7387 torr. The correlation coefficient R2 between the inverted pressure value and the measured true value was 0.999, with a maximum fitting error of 1.19 %, error fluctuations within 2 %, and pressure uncertainty ranging from 0.545 % to 0.913 %. Furthermore, the ammonia concentration was corrected, and the maximum error compared to the standard ammonia concentration injected in the experiment was 1.025 % (with an effective optical path length of the detection gas cell of 15 cm). This work demonstrated the effectiveness of the proposed method in accurately inverting dynamic real-time pressure values and improving the accuracy of gas concentration measurement.

Boosted Incremental Nonlinear Dynamic Inversion for Flexible Airplane Gust Load Alleviation

Active gust load alleviation is an important technology for reducing loads on future commercial airplanes so that the structure can be designed to be lighter in order to save fuel. For the intense reduction of gust loads, a highly reactive control system of sensors, control algorithms, and actuators is required, which is not yet available. In this paper, a control algorithm based on incremental nonlinear dynamic inversion is extended so that actuators respond faster. The control algorithm is applied to a future medium-range aircraft with distributed trailing-edge flaps. It is assumed that the vertical acceleration of the center of gravity and the displacement, velocity, and acceleration of the first wing bending mode are available as feedback variables. To allow comparability with other actuator and sensor setups, the authors abstract the actuator dynamics and sensor filter as control system time delay. The feedback gains are adjusted automatically to the control system time delay. In simulation, the authors investigate the influence of the control system time delay on the peak gust loads. They show that gust loads can indeed be intensely reduced with sufficiently small control system time delay in simulation.

Fault-Tolerant Control for Aircraft with Structural Damage Using Sparse Online Gaussian Process Regression

This paper presents the design of data-driven fault-tolerant control using sparse online Gaussian process regression (SOGPR) to stabilize an aircraft with left-wing damage. The structural damage causes changes in mass, moment of inertia, center of gravity, and aerodynamic coefficients. These parameter variations deteriorate the performance of model-based nonlinear control methods. Hence, Gaussian process-based nonlinear dynamic inversion (GP-NDI) is proposed to compensate for uncertainties in situations of structural damage. Unlike parametric adaptive control approaches, Gaussian process regression is a non-parametric method that does not need prior information about uncertainties. And the proposed method implements SOGPR to reduce computational time and memory by incrementally updating the mean and variance. To compensate for the error in the estimated uncertainty, a robust control input is designed. In addition, a weighted delete score is used to improve the transient response. Numerical simulation results are compared with model reference adaptive control (MRAC) and nonlinear disturbance observer (NDO) to analyze a stabilizing and tracking performance in a structural damage situation.

Rotary inverted pendulum control using neuro-adaptive robust generalized dynamic inversion

The objective of this research is to design a robust control system for trajectory tracking of the under-actuated Rotary Inverted Pendulum (RIP). The focus is on achieving semi-global asymptotic stability in the absence of knowledge about the RIP geometric and inertia parameters. The control design commences by formulating differential servo constraint dynamics (VCD) that encapsulates the control objectives for the RIP. The baseline generalized dynamic inversion (GDI) control law is derived by inverting the VCD for the control voltage input using the Moore–Penrose generalized inverse. To enhance robustness against modeling uncertainties and exogenous disturbances, a sliding mode control (SMC) element is integrated within the GDI control system, resulting in the robust GDI (RGDI) control system. Furthermore, an adaptive estimator that is based on Radial Basis Function Neural Networks (RBF-NN) is adopted to eliminate the dependency of the RGDI control system on the RIP mathematical model. The weighting matrices of the RBF-NN are updated with the aid of a Lyapunov control function. The proposed control system offers robust solution and guarantees semi-global asymptotic stability to the unstable equilibria of the RIP dynamics in the absence of a mathematical model. The proposed control system’s performance is evaluated through computer simulations and experimental tests on a real RIP system. Comparative analyses with traditional SMC and linear quadratic control methodologies are conducted to show the effectiveness of the proposed approach.

Dynamical Nonlinear Inversion of the Surface Photovoltage at Si(100).

A surface photovoltage (SPV) is observed whenever a doped semiconductor with non-negligible band bending is illuminated by light and charge carriers are excited across the band gap. The sign of the SPV depends on the nature of the doping, the amplitude of the SPV increases with the fluence of the light illumination up to a saturation value, which is determined by the doping concentration. We have investigated Si(100) samples with well-characterized doping levels over a wide range of illumination fluences. Surprisingly, the sign of the SPV upon illumination with 532nm photons reverses for some p-doping concentrations at high fluences. This is a new effect associated with a crossover between electronic excitations in the bulk and at the surface of the semiconductor.

Discretize-Then-Optimize Modeling for Dynamic Force Inversion Based on Runge–Kutta Explicit Time Integration

Discretize-Then-Optimize Modeling for Dynamic Force Inversion Based on Runge–Kutta Explicit Time Integration

Precision Advancements in Aerial Gliding Vehicles: Modeling to FCS Validation

The growing utilization of unmanned aerial vehicles (UAVs) in military operations has necessitated the development of a suitable weaponry for these kind of platforms. One of the trending categories of such armaments is the aerial gliding vehicle (AGV). AGVs have no propulsion system, consequently, a critical need for a robust flight control system (FCS) tailored to this kind of aerial systems is raised. This research focuses on designing a nonlinear model based controller, starting with the construction of a precise model through practical experiments and the establishment of a dedicated testing and flight simulation environment. Recognizing the limitations of traditional nonlinear dynamic inversion (NDI) due to its dependence on the vehicle model, the modified incremental nonlinear dynamic inversion (MI-NDI) is developed to operate in the presence of wind, model mismatches, and external disturbances. In this research, an extensive testing is conducted in a hardware-in-the-loop (HIL) simulation environment which validates the MI-NDI controller’s superior performance, even in challenging conditions. The research outcomes mark a significant advancement in enhancing autopilot precision for advanced aerial weaponry and unmanned vehicles.

Hexa-Propeller Airship for Environmental Surveillance and Monitoring in Amazon Rainforest

This paper proposes a new kind of airship actuator configuration for surveillance and environmental monitoring missions. We present the design and application of a six-propeller electrical airship (Noamini) with independent tilting propellers, allowing improved and flexible maneuverability. The vehicle has different combinations of differential propulsion and can be used in a two-, four- or six-motor configuration. We developed a high-fidelity airship simulator for the Noamini airship, which was used to test and validate a control/guidance approach. Incremental Nonlinear Dynamic Inversion (INDI) is used for the velocity/attitude control to follow a high-level L1 guidance reference in a simulated waypoint-tracking mission with wind and turbulence. The proposed framework will be soon implemented in the onboard control system of the Noamini, an autonomous airship for environmental monitoring and surveillance applications.

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study.

This article introduces a cutting-edge H∞ model-based control method for uncertain Multi Input Multi Output (MIMO) systems, specifically focusing on UAVs, through a flexible mixed-optimization framework using the Method of Inequality (MOI). The proposed approach adaptively addresses crucial challenges such as unmodeled dynamics, noise interference, and parameter variations. Central to the design is a two-step controller development process. The first step involves Nonlinear Dynamic Inversion (NDI) and system decoupling for simplification, while the second step integrates H∞ control with MOI for optimal response tuning. This strategy is distinguished by its adaptability and focus on balancing robust stability and performance, effectively managing the intricate cross-coupling dynamics in UAV systems. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB/Simulink environment. Results demonstrated the efficiency of the proposed robust control approach as evidenced by reduced steady-state error, diminished overshoot, and faster system response times, thus significantly outperforming traditional control methods.

Research on cascade control method for turboshaft engine with variable rotor speed

Abstract In order to realize high-quality control for turboshaft engine with variable rotor speed, a cascade control method based on the acceleration estimator of gas turbine speed (N gdot ) through Complementary filtering – incremental nonlinear dynamic inversion (CF-INDI)with Newton’s prediction is proposed. Firstly, an adaptive torsional suppression method based on the Recursive Least Square (RLS) algorithm and combined with the control index of power turbine speed is proposed and designed to solve the torsional instability of control system in turboshaft engine with variable rotor speed. Then, an online N gdot estimated method based on CF-INDI with Newton’s prediction is developed, and the complementary filtering method is applied to compensate for the inaccuracy of the state variable model available at a single working point, and Newton prediction is used to alleviate the problem of lagging acceleration estimate, which is accessible to realize the cascade control for turboshaft engine based on N gdot . The simulation results show that the RLS adaptive torsional filter can effectively suppress the low-order torsional components with frequencies of 1.2 Hz and 2.0 Hz mixing in power turbine speed, and the torsional suppression effect is remarkable. In addition, under different flight conditions, CF-INDI with Newton prediction is faster and more accurate than INDI N gdot estimate, and smoother than central difference method, which proves the feasibility of INDI N gdot estimator. Meanwhile, after the application of CF-INDI with Newton prediction N gdot estimator in cascade control, the anti-interference capacity of power turbine speed is stronger, and the dynamic control effect is superior, which has satisfactory robustness performance.

Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation

Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the problem of stabilizing a tail-sitter when hovering. For this purpose, the first controller is an existing strategy for tail-sitter control obtained from the literature, the second is an application of Nonlinear Dynamic Inversion (NDI), and the last one is its incremental version, INDI. These controllers were implemented and tuned in a simulation in order to stabilize a model of the tail-sitter, complemented by estimation methods that allow the feedback of the necessary variables. These estimators and controllers were then implemented in a microcontroller and validated in a Hardware-in-the-Loop (HITL) scenario with simple maneuvers in vertical flight. Lastly, the developed control solutions were used to stabilize the aircraft in experimental flight while being monitored by a motion capture system. The experimental results allow the validation of the model of the X-Vert and provide a comparison of the performance of the different control solutions, where the INDI presents itself as a robust control strategy with accurate tracking capabilities and less actuator demand.

Light-induced switching between singlet and triplet superconducting states

While the search for topological triplet-pairing superconductivity has remained a challenge, recent developments in optically stabilizing metastable superconducting states suggest a new route to realizing this elusive phase. Here, we devise a testable theory of competing superconducting orders that permits ultrafast switching to an opposite-parity superconducting phase in centrosymmetric crystals with strong spin-orbit coupling. Using both microscopic and phenomenological models, we show that dynamical inversion symmetry breaking with a tailored light pulse can induce odd-parity (spin triplet) order parameter oscillations in a conventional even-parity (spin singlet) superconductor, which when driven strongly can send the system to a competing minimum in its free energy landscape. Our results provide new guiding principles for engineering unconventional electronic phases using light, suggesting a fundamentally non-equilibrium route toward realizing topological superconductivity.

Event-Based Guidance and Incremental Control with Application to Fixed-wing Unmanned Aerial Vehicle Perched Landing Maneuvers

Considering the nonlinearity and unknown dynamics of fixed-wing unmanned aerial vehicles in perched landing maneuvers, an event-based online guidance and incremental control scheme is proposed. The guidance trajectory for perched landing must be dynamically feasible therefore an event-based trapezoidal collocation point optimization method is proposed. Introduction of the triggering mechanism for the rational use of computing resources to improve PL accuracy. Furthermore, a filter-based incremental nonlinear dynamic inverse (F-INDI) control with state transformation is proposed to achieve robust trajectory tracking under high angle of attack (AOA). The F-INDI uses low-pass filters to obtain incremental dynamics of the system, which simplifies the design process. The state transformation strategy is to convert the flight-path angle, AOA and velocity into two composite dynamics, which avoids the sign reversal problem of control gain under high AOA. The stability analysis shows that the original states can be controlled only by controlling the composite state. Simulation results show that the proposed scheme achieves high perched landing accuracy and a reliable trajectory tracking control.

A New Chirality Invertible Photoswitch: Light-Driven Axially Chiral Hydrazone Enabling Dynamic Handedness Inversion of Self-Organized Helical Superstructure

A New Chirality Invertible Photoswitch: Light-Driven Axially Chiral Hydrazone Enabling Dynamic Handedness Inversion of Self-Organized Helical Superstructure

Dynamic characteristics analysis and robust transition control of tail-sitter VTOL UAVs

The strong nonlinear dynamics of tail-sitter vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) have consistently constrained their applications. Particularly, the widely-varying flight speed and attitude during the transition flights pose substantial challenges for the controller design. In order to gain a clear understanding of the nonlinear transition flights, the long- and short- period dynamic characteristics of tail-sitter UAVs are investigated for the first time. The results reveal that the short-period mode exhibits either sluggish response or excessive overshoot in different transition stages, primarily due to the widely-varying damping ratio and natural angular frequency. Even worse, the long-period mode can diverge due to positive poles. To address these issues, a systematic controller is proposed. First, the transition trajectory is optimized and the optimal control inputs are employed in a feedforward manner to trim the nominal forces and moments. On this basis, a discrete-time linear quadratic regulation (LQR) controller with a predefined decay rate is developed to position the desired poles, and a novel angular acceleration estimation method is introduced to compensate for unmodeled dynamics. Simulations under different uncertainties indicate that the proposed control method performs better in both transition trajectory tracking and uncertainty suppression, compared to the PID and incremental nonlinear dynamic inversion (INDI) controllers.