Engineering topics

Yildiz, Yildiray

Publications and source records attributed to Yildiz, Yildiray.

6 records

NASA NTRS2013

Motion-Based Piloted Simulation Evaluation of a Control Allocation Technique to Recover from Pilot Induced Oscillations

This paper describes the maturation of a control allocation technique designed to assist pilots in the recovery from pilot induced oscillations (PIOs). The Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) is designed to enable next generation high efficiency aircraft designs. Energy efficient next generation aircraft require feedback control strategies that will enable lowering the actuator rate limit requirements for optimal airframe design. One of the common issues flying with actuator rate limits is PIOs caused by the phase lag between the pilot inputs and control surface response. CAPIO utilizes real-time optimization for control allocation to eliminate phase lag in the system caused by control surface rate limiting. System impacts of the control allocator were assessed through a piloted simulation evaluation of a non-linear aircraft simulation in the NASA Ames Vertical Motion Simulator. Results indicate that CAPIO helps reduce oscillatory behavior, including the severity and duration of PIOs, introduced by control surface rate limiting.

pilot induced oscillation↗

NASA NTRS2013

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Game Theory↗

NASA NTRS2012

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Yildiz, Yildiray↗

NASA NTRS2011

Implementation of CAPIO for Composite Adaptive Control of Cross-Coupled Unstable Aircraft

This paper presents an implementation of a recently developed control allocation algorithm CAPIO (a Control Allocation technique to recover from Pilot Induced Oscillations) for composite adaptive control of an inertially cross coupled unstable aircraft. When actuators are rate-saturated due to either an aggressive pilot command, high gain of the flight control system or some anomaly in the system, the effective delay in the control loop may increase due to the phase shifting between the desired and the achieved system states. This effective time delay may deteriorate the performance or even destabilize the system in some cases, depending on the severity of rate saturation. CAPIO reduces the effective time delay by minimizing the phase shift between the commanded and the actual attitude accelerations. We present simulation results for an unstable aircraft with cross-coupling controlled with a composite adaptive controller in the presence of rate saturation. The simulations demonstrate the potential of CAPIO serving as an effective rate saturation compensator in adverse conditions.

Yildiz, Yildiray↗

NASA NTRS2010

A Control Allocation Technique to Recover From Pilot-Induced Oscillations (CAPIO) Due to Actuator Rate Limiting

This paper proposes a control allocation technique that can help pilots recover from pilot induced oscillations (PIO). When actuators are rate-saturated due to aggressive pilot commands, high gain flight control systems or some anomaly in the system, the effective delay in the control loop may increase depending on the nature of the cause. This effective delay increase manifests itself as a phase shift between the commanded and actual system signals and can instigate PIOs. The proposed control allocator reduces the effective time delay by minimizing the phase shift between the commanded and the actual attitude accelerations. Simulation results are reported, which demonstrate phase shift minimization and recovery from PIOs. Conversion of the objective function to be minimized and constraints to a form that is suitable for implementation is given.

Yildiz, Yildiray↗

NASA NTRS2010

Stability Properties and Cross Coupling Performance of the Control Allocation Scheme CAPIO

This paper presents a stability analysis and an application of a recently developed Control Allocator for recovery from Pilot Induced Oscillations (CAPIO). When actuators are rate-saturated due to either aggressive pilot commands, high gain ight control systems or some anomaly in the system, the effective delay in the control loop may increase. This effective delay increase manifests itself as a phase shift between the commanded and actual system signals and can instigate Pilot induced Oscillations (PIO). CAPIO reduces the e ective time delay by minimizing the phase shift between the commanded and the actual attitude accelerations. We present a stability analysis of CAPIO for a scalar system. In addition, we present simulation results for aircraft with cross-coupling which demonstrates the potential of CAPIO serving as an effective PIO handler in adverse conditions.

Yildiz, Yildiray↗