Modeling XV-15 tilt-rotor aircraft dynamics by frequency and time-domain identification techniques

Models of the open-loop hover dynamics of the XV-15 Tilt-Rotor Aircraft are extracted from flight data using two approaches: frequency domain and time-domain identification. Both approaches are reviewed and the identification results are presented and compared in detail. The extracted models are compared favorably, with the differences associated mostly with the inherent weighing of each technique. Step responses are used to show that the predictive capability of the models from both techniques is excellent. Based on the results of this study, the relative strengths and weaknesses of the frequency and time-domain techniques are summarized and a proposal for a coordinated parameter identification approach is presented

UAV as a Reliable Wingman: A Flight Demonstration

In this brief, we present the results from a flight experiment demonstrating two significant advances in software enabled control: optimization-based control using real-time trajectory generation and logical programming environments for formal analysis of control software. Our demonstration platform consisted of a human-piloted F-15 jet flying together with an autonomous T-33 jet. We describe the behavior of the system in two scenarios. In the first, nominal state communications were present and the autonomous aircraft maintained formation as the human pilot flew maneuvers. In the second, we imposed the loss of high-rate communications and demonstrated an autonomous safe “lost wingman” procedure to increase separation and reacquire contact. The flight demonstration included both a nominal formation flight component and an execution of the lost wingman scenario

A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles

Vehicle to Vehicle (V2V) communication has a great potential to improve reaction accuracy of different driver assistance systems in critical driving situations. Cooperative Adaptive Cruise Control (CACC), which is an automated application, provides drivers with extra benefits such as traffic throughput maximization and collision avoidance. CACC systems must be designed in a way that are sufficiently robust against all special maneuvers such as cutting-into the CACC platoons by interfering vehicles or hard braking by leading cars. To address this problem, a Neural- Network (NN)-based cut-in detection and trajectory prediction scheme is proposed in the first part of this paper. Next, a probabilistic framework is developed in which the cut-in probability is calculated based on the output of the mentioned cut-in prediction block. Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed which incorporates this cut-in probability to enhance its reaction against the detected dangerous cut-in maneuver. The overall system is implemented and its performance is evaluated using realistic driving scenarios from Safety Pilot Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I

Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental settin

Robust control for independently rotating wheelsets on a railway vehicle using practical sensors

This paper presents the development of H-infinity control strategy for the active steering of railway vehicles with independently rotating wheelsets. The primary objective of the active steering is to stabilize the wheelset and to provide a guidance control. Some fundamental problems for active steering are addressed in the study. The developed controller is able to maintain stability and good performance when parameter variations occur, in particular at the wheel-rail interface. The control is also robust against structured uncertainties that are not included in the model such as actuator dynamics. Furthermore the control design is formulated to use only practical sensors of inertial and speed measurements, as some basic measurements required for active steering such as wheel-rail lateral displacement cannot be easily and economically measured in practice

A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models

In this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.This work has been conducted within the ENABLE-S3 project that has received funding from the ECSEL Joint Undertaking under Grant Agreement No 692455. This work was developed at Tecnalia Research & Innovation facilities supporting this research