Pilot-induced Oscillations Research Articles

Model Reference Control for Reducing Pilot-Induced Oscillation Tendencies

Lags between pilot inputs and aircraft responses may lead to a pilot–vehicle system entering into a pilot-induced oscillation. A model reference control element can compensate for these lags, avoiding pilot-induced oscillations and improving tracking performance. Neural network compensation drives the combined controller–plant system to exhibit a closed-loop response similar to that of an idealized system, immune to the factors that trigger pilot-induced oscillations. Actuator rate limiting has been a historically ubiquitous cause of pilot-induced oscillations; meanwhile, aeroelastic effects pose a threat to future lightweight, flexible aircraft designs. Model reference control can reduce pilot-induced oscillation tendencies caused by either of these factors. This paper presents the methods used to train the model reference controller, including conditions for system stability under model reference control. It then showcases results from a pair of simulation experiments applying the control design to compensate for rate limiting and aeroelasticity, respectively. Results demonstrate that the model reference control scheme reduces pilot-induced oscillation tendencies and improves closed-loop tracking performance.

Development of means for suppressing the negative effects of interaction between the pilot and reentry and other high-speed vehicles

Several novel active and passive means for the suppression of pilot-induced oscillations are considered in the paper. The potential of the proposed means in eliminating Category I, II, and III pilot-induced oscillations was studied in ground-based simulation for two controlled element dynamics corresponding to an aerospace vehicle and a second-generation supersonic transport. The experiments demonstrated that the highest effectiveness in suppressing pilot-induced oscillations and improving task performance is provided by integrating both proposed active suppressors with one of the passive prefilters.

Adaptive Flying Assistance Controller Design to Suppress Nonlinear Pilot-Induced Oscillations

Nonlinear pilot-induced oscillations (PIOs) pose a threat to the safety of piloted aircraft in flight. This study aimed to address this safety concern. A novel method for designing an assistance controller based on incremental model predictive control is proposed to aid pilots in suppressing categories 2 and 3 PIOs. In the assistance controller design, the characteristics of the full pilot–aircraft system are considered through a predictive model that integrates the dynamics of the pilot, actuator, and aircraft. This ensures that the assistance controller coordinates with both the pilot and aircraft. Additionally, an adaptive logic for the pilot–controller authority assignment is proposed to automatically adjust the role of the assistance controller. This adaptive logic adopts a model predictive technique to determine whether the pilot’s independent control will cause actuator saturation over the receding prediction horizon. By doing so, the assistance controller is restricted to work only when the actuator saturation constraints are activated. The pilot model-based simulations and the human-in-the-loop experiments demonstrated that the proposed assistance controller can effectively assist pilots in dealing with factors causing nonlinear PIOs while maintaining a harmonious cooperative relationship with the pilot.

Pilot Induced Oscillations of the Small Unmanned Aerial Vehicles

Abstract The unintentional inputs of the UAV operators in certain conditions might lead to the unwanted, pilot induced oscillations (PiO) of the aircraft. The PiOs might cause severe damages of the UAV, or as the worth, might lead to the loss of the aircraft. The PiOs of the manned aircraft are in the focus of attention for many decades. However, the PiOs of the UAVs became an important issue worth to investigate only in the past few years. Thus, scientific results and proven statements gained in this field might enrich both the on-going UAV operator training programs and UAV autopilot design based mostly on traditional synthesis methods and procedures.

Parameters design for feel system of aircraft active inceptor controller

To provide the pilot with feedback on flight states, aircraft active inceptor controllers deliver appropriate tactile feedback through the feel system. Current research on the feel system often relies on conventional models, with limited analysis of its unique characteristics. Investigating the dynamic properties of the feel system and their impact on flying quality can inform the parameters design of the feel system. In this paper, we designed various feel system parameters with different natural frequencies and damping ratios and selected three typical aircraft dynamic models. A human-vehicle closed-loop system model is established, including the pilot model, feel system model, and aircraft dynamic model. Combining different flying quality criteria, including bandwidth criterion, Neal-Smith criterion, and Open-Loop Onset-Point (OLOP) criterion, the flying qualities of Type I and Type II pilot-induced oscillations (PIO) are evaluated separately. The influence of aircraft configuration, feel system natural frequency and damping ratio on flying quality is explored. Finally, design recommendations for the feel system are proposed, aiming to reduce the adverse aircraft pilot coupling and improve flying quality.

Adaptive active inceptor design under shared control architecture for nonlinear pilot-induced oscillations

This paper presents a Shared Control Architecture (SCA) between a human pilot and a smart inceptor for nonlinear Pilot Induced Oscillations (PIOs), e.g., category II or III PIOs. One innovation of this paper is that an intelligent shared control architecture is developed based on the intelligent active inceptor technique, i.e., Smart Adaptive Flight Effective Cue (SAFE-Cue). A deep reinforcement learning approach namely Deep Deterministic Policy Gradient (DDPG) method is chosen to design a gain adaptation mechanism for the SAFE-Cue module. By doing this, the gains of the SAFE-Cue will be intelligently tuned once nonlinear PIOs triggered; meanwhile, the human pilot will receive a force cue from the SAFE-Cue, and will consequently adapting his/her control policy. The second innovation of this paper is that the reward function of the DDPG based gain adaptation approach is constructed according to flying qualities. Under the premise of considering failure situation, task completion qualities and pilot workload are also taken into account. Finally, the proposed approach is validated using numerical simulation experiments with two types of scenarios: lower actuator rate limits and airframe damages. The Inceptor Peak Power-Phase (IPPP) metric is adopted to analyze the human-vehicle system simulation results. Results and analysis show that the DDPG based sharing control approach can well address nonlinear PIO problems consisting of Categories II and III PIO events.

Suppression of Pilot-Induced Oscillations of Various Categories Using Augmentation Means

Suppression of Pilot-Induced Oscillations of Various Categories Using Augmentation Means

Suggestions for Criteria to Evaluate Lateral-Directional Nonlinear Pilot-Induced Oscillations Due to Fly-by-Wire Civil Aircraft Landing Configuration Switch

Using a nonlinear pilot-induced oscillation prediction method based on digital virtual flight simulation calculations, digital experiments on predicting lateral-directional nonlinear pilot-induced oscillations due to landing configuration switching of fly-by-wire civil aircraft with different closed-loop dynamic characteristics are carried out. It is proposed that the lateral-directional pilot-induced oscillations due to the landing configuration switch can be evaluated using the changes in dynamic characteristic parameters before and after the configuration switch. The quantitative boundaries of the dynamic characteristic parameters of an example aircraft are determined, and a criterion suggestion is formed to predict the lateral-directional nonlinear pilot-induced oscillations due to landing configuration switching. This study provides a reference for the optimal design of the lateral-directional flight control law of fly-by-wire aircraft during the approach stage and provides suggestions for the formulation of evaluation criteria for other nonlinear pilot-induced oscillation phenomena.

Overview of System Identification Tool Advancements at Systems Technology, Incorporated

For nearly two decades, Systems Technology, Inc. has been investigating novel system identification methods and practical applications. Two such methods will be highlighted herein: 1) the use of wavelet-based scalograms to explore the nature of dynamic systems in both the time and frequency domains simultaneously; and 2) a method to estimate frequency, damping, and mode shapes for lightly damped aeroelastic modes exhibited across a variety of air vehicles. From past work, two scalogram-based metrics have evolved, which are the power frequency and inceptor peak power phase, that will be one focus of this paper. The power frequency provides a metric that considers not only the dominant frequencies of the signal of interest, such as the command input from a pilot, but also the power at those frequencies. For the inceptor peak power phase, scalograms are used to identify the peak input power of a pilot’s inceptor command signal that when compared against a pitch or roll rate phase angle at the peak frequency produces a new method to detect the onset of pilot-induced oscillations. This paper will further describe system identification tools that extract modal information of aeroelastic vibrations observed in flight. Because it is often difficult to obtain input excitation data, particularly in real time, Systems Technology, Inc. developed a modal identification software toolbox that provides an innovative approach based on curve-fitting frequency domain decomposition, which relies only on output sensor data to identify the aeroelastic modes. Flight-test data are used to demonstrate the effectiveness and efficacy of the system identification approaches.

Designing a Robust Predictive Controller to Prevent Rate-Limiter-Based Pilot-Induced Oscillations in the Frequency Domain

Designing a Robust Predictive Controller to Prevent Rate-Limiter-Based Pilot-Induced Oscillations in the Frequency Domain

Adaptive flight control system for flight safety improvement in reentry and other high-velocity vehicles

An adaptive controller and a nonlinear rate limiter are presented in order to improve the flight safety of manually controlled reentry vehicles and supersonic transport (SST) aircraft. The adaptive controller is based on the principle of dynamic inversion. The calculation of the controller parameters corresponding to the aerodynamic coefficients of the vehicle was carried out by a proposed online identification procedure. The effectiveness of the adaptive controller was tested through a set of experiments performed using a ground-based simulator. The obtained results were used to estimate the probability of an accident due to pilot error for the basic Space Shuttle flight control system and for its improved version with the adaptive controller. It was found that using the adaptive controller causes high required rates of elevon deflection. Because of the actuator's rate limiting, this is a source of pilot-induced oscillations. To counteract these oscillations in the pilot-vehicle closed loop system, an adaptive nonlinear rate limiter is introduced. The effectiveness of using the adaptive prefilter for improving the flight safety and flying qualities of the Space Shuttle reentry vehicle and an SST was demonstrated in experiments involving a ground-based simulator.

Visual and Control Augmentation Techniques for Pilot Assistance During Helicopter Shipboard Recovery

Shipboard launch and recovery of helicopters continue to pose operational challenges even to experienced pilots. The present research seeks to develop novel visual and control augmentation techniques and determine their impact on human factors for shipboard recovery operations. The paper first outlines the development and integration of a helicopter–ship dynamic interface model into a wide field of view, fixed-base rotorcraft simulation environment. The paper then describes the development of novel visual and control augmentation techniques for pilot assistance during shipboard recovery. Visual augmentation includes two-dimensional primary flight information and three-dimensional conformal shipboard landing symbology presented on a low-cost, off-the-shelf, see-through head-mounted display system to facilitate "eyes-out" piloting. Control augmentation includes robust nonlinear control laws producing translational rate command position hold, and acceleration command velocity hold response types with good predicted handling qualities. Finally, the paper reports experimental results of simulated visual shipboard approaches conducted with four experimental test pilots for low- and high-intensity ship motions. The results indicate improved piloting performance, mitigation of pilot-induced oscillations, lower workload, improved handling, and improved perceived safety for fleet pilots for the proposed visual and control augmentation techniques.

Modeling Fuzzy and Adaptive Human Behavior for Aircraft with Dynamic-Pitch-Control Envelope Cue

As one of the key issues in aviation safety, loss-of-control in the form of adverse aircraft-pilot couplings is attracting attention increasingly. Dynamic-pitch-control envelope shows to be a promising means to evaluate the loss-of-control related to pilot-induced oscillations. To mitigate this issue, this paper develops a human pilot model with the dynamic-pitch-control envelope cue. A key feature of the model is the capability to afford the characteristics of the pilot’s behavior through analyzing the cue of envelope boundaries in different areas. The fuzziness and adaption of the human are introduced into the model to describe the behavior of the human pilot. Fuzzy control logic is designed to reflect the fuzziness of the human’s response to the envelope cue. Time-varying parameters are adjusted to embody the adaptive characteristics of the human pilot to different regional envelope cues. Furthermore, three metrics methods, including error metric, envelope boundaries metric, and scalogram-based pilot-induced oscillation (PIO) metric, are proposed to design the dynamic-pitch-control envelope cues. The assessment results obtained by pilot–aircraft system simulation are compared with the pilot-in-the-loop flight experiment in-ground simulator to validate the effectiveness of the model. Simulation and experimental results show that the proposed human pilot model and envelope cue method can be applied to mitigate the loss-of-control events caused by the pilot–aircraft system oscillations.

Generalized predictive control of the aircraft system with actuator saturation to prevent Pilot-induced Oscillations

Amplitude and rate saturations are one of the problems of flight control systems which puts the closed-loop system stability at risk. These nonlinear elements are mainly responsible for the type II pilot induces oscillations (PIOs). In this paper, a robust unconstrained generalized predictive controller (GPC) with a self-tuning regulator (STR) structure is designed in the frequency domain to prevent the type II PIOs. Furthermore, the sensitivity function is used for tuning the GPC parameters and investigating the stability and robustness of the system against the uncertainties of the controller parameters. To get better results, a constrained GPC is further designed considering the rate, amplitude, and both saturations. Rate and amplitude saturations are considered as input constraints in the design stage. Finally, the performances of the proposed controllers are compared to that of a PID controller.

Human Pilot Interaction with Fast Adapting Flight Control System

Interaction between the adaptive behavior of a human pilot and an adaptive flight control system (FCS) usually leads to undesirable adverse effects such as pilot-induced oscillations (PIO). This paper presents an analysis of this interaction in the case of a fast adapting FCS. The analysis shows that, although a pilot will have some nonlinear behavior at the moment when a failure occurs, the fast adapting FCS allows to keep the physical workload low and the pilot behavior remains the same as before the failure. This effectively mitigates the adverse effects seen in the literature.

Application of Nonlinear Correction Method for Attitude Control and Landing Oscillations Prevention

The purpose of this work is to demonstrate the application of the nonlinear correction method to prevent attitude oscillations of flying vehicles. This paper investigates the complications of manual control tasks in aeronautics caused by employing the integral component in the control loop. If the actuators of aircraft controlling surfaces reach their rate limits, the aircraft oscillations can appear for both manually and automatically piloted cases. In this paper, the oscillations alleviation problem is solved using the nonlinear correction method. A general methodology for pilot-induced oscillations prevention is described briefly by the example of an aircraft pitch control system. The obtained pilot model parameters are used for altitude control system examination. The nonlinear systems analysis is carried out by calculating the generalized sensitivity function for the control and disturbance input signal. In the second part, the application of the nonlinear correction method to prevent aircraft and satellite oscillations caused by integrator windup. A comparative analysis of the nonlinear correction and the customary anti-windup feedback is carried out. The results obtained demonstrate that a sequential nonlinear corrective device can be efficiently used to suppress pilot-induced and integrator windup oscillations.

Предотвращение колебаний, вызванных летчиком при посадке воздушного судна

The paper focuses on a manned aircraft landing control system. It is known that actuator level and rate limitations can cause pilot-induced oscillations. This phenomenon occurs during intensive pilot control in a closed-loop system under certain initiating conditions associated with both the influence of the external environment and changes in the system dynamics. Oscillations appear unintentionally and unexpectedly for the pilot, which jeopardizes flight safety. The study shows the possibility of preventing aircraft oscillations using the method of nonlinear correction of systems by sequential introduction of a pseudo-linear correcting device into the control loop, the phase-frequency characteristic of the device not depending on the amplitude of the input signal. The airplane-pilot closed-loop system for various parameters of the input signal is analyzed by calculating the generalized function of sensitivity and the excitation index. The results of the study are presented in the form of angle and the pitch rate time processes, and landing trajectories.

A survey of human pilot models for study of Pilot-Induced Oscillation (PIO) in longitudinal aircraft motion

AbstractPilot-Induced Oscillation (PIO), although an old issue, still poses a significant threat to aviation safety. The introduction of new systems in modern aircraft modifies the human–machine interaction and makes it necessary for research to revisit the subject from time to time. Given the need of aircraft manufacturers to constantly perform PIO tests, this study analysed the feasibility of using three different computational pilot models (Tustin, Crossover and Precision) to simulate PIO conditions. Three aircraft models with different levels of propensity to PIO (original, low propensity and high propensity) were tested, as well as two pilot gain conditions (normal and high). Data were collected for a purely longitudinal synthetic task through simulations conducted in MATLAB®. PIO conditions were detect using a tuned PIO detection algorithm (ROVER). Data were analysed in terms of both whether the pilot models triggered a PIO condition and for how long the condition was sustained. The results indicated that the three pilot models only provoked PIO conditions when high gain inputs were applied. Additionally, Crossover was the only pilot model to trigger a PIO for the three aircraft models. There were also significant differences between the pilot models in the total PIO time, as the Tustin model typically sustained the oscillatory condition for longer.

Method of predicting nonlinear pilot-induced oscillations due to flight control degradation based on digital virtual flight

Because few methods of predicting nonlinear pilot-induced oscillations are available, it is difficult to analyze the sensitive characteristics of such oscillations in the stage of aircraft scheme design. The pilot has the ability to self-adapt, and the control behavior may change before and after flight control degradation. To identify flight control degradation faults and adaptively adjust a pilot's manipulation behavior, three new modules, including pilot perception, flight control degradation judgment and adaptive adjustment, are established to construct a time-varying pilot model. Combined with a digital flight task model, a digital virtual flight simulation model of flight control degradation is built. An identification algorithm based on fuzzy logic is adopted to quantitatively evaluate the pilot-induced oscillation characteristics according to the numerical simulation results. Then, a nonlinear pilot-induced oscillation prediction method based on digital virtual flight is established. A pitch attitude tracking task is selected to predict the longitudinal, nonlinear pilot-induced oscillations. The results show that the prediction results of the simulations are basically consistent with those of a human-in-the-loop flight test with a ground simulator, which verifies the correctness of the proposed method. Through a sensitivity study of the stick force gradient after degradation, the influence of this parameter and the recommended value are determined. This method can be used to predict the nonlinear pilot-induced oscillation characteristics of fly-by-wire aircraft in the conceptual design stage and provide a theoretical reference for the optimal design of flight control systems.

Modeling multi-loop intelligent pilot control behavior for aircraft-pilot couplings analysis

Aircraft-pilot couplings (APCs) are one of the key factors that affect the flight safety of the modern aircraft. Among the several types of APCs, the nonlinear pilot induced oscillations caused by aircraft flight control system anomalies are extremely severe. In this paper, a multi-loop intelligent pilot model is presented for the analysis of the nonlinear pilot induced oscillations investigations. The multi-loop control tasks are introduced to define a typical multi-loop pilot modeling problem. The model is capable of describing the pilot's behavior during a multi-loop control task and analyzing the nonlinear pilot-induced oscillations when the flight control system is changed in different forms. Fuzzy control logic is designed to reflect the human pilot's behavior of making judgments. To be specific, the human pilot can change his/her control behavior adaptively when the aircraft flight control system falls into anomalies. Six cases of the abnormal flight control system are considered, and the control effects of the human pilot model are analyzed. The experimental results demonstrate that the human pilot can adjust the control strategy in different cases, which reflects the human pilot's adaptation to the changes of aircraft dynamics characteristics. Furthermore, it indicates that the human pilot model can obtain good control performance in tracking the command signal and can complete the task well facing the failures of the control system. Besides, the validity of the human pilot model is assessed by the scalogram-based PIO metric. The proposed pilot model can be applied in evaluating the aircraft loss-of-control events in the form of adverse aircraft-pilot couplings.