Model-Based Vehicle Dynamics Control for Active Safety

The functionality of modern automotive vehicles is becoming increasingly dependent on control systems. Active safety is an area in which control systems play a pivotal role. Currently, rule-based control algorithms are widespread throughout the automotive industry. In order to improve performance and reduce development time, model-based methods may be employed. The primary contribution of this thesis is the development of a vehicle dynamics controller for rollover mitigation. A central part of this work has been the investigation of control allocation methods, which are used to transform high-level controller commands to actuator inputs in the presence of numerous constraints. Quadratic programming is used to solve a static optimization problem in each sample. An investigation of the numerical methods used to solve such problems was carried out, leading to the development of a modified active set algorithm.Vehicle dynamics control systems typically require input from a number of supporting systems, including observers and estimation algorithms. A key parameter for virtually all VDC systems is the friction coefficient. Model-based friction estimation based on the physically-derived brush model is investigated

Dynamic Inversion and Backstepping Controller Robustness Analysis for a Reusable Launch Vehicle

The Air Force has been working towards developing technology for operationally responsive space (ORS), which is the ability to launch military assets into space without the long set up time currently required. Part of the solution to ORS is to develop a reusable booster vehicle capable of sending any vehicle into orbit, then descending back to the atmosphere and landing unpowered so that it may take another vehicle into orbit with a 48 hour turnaround time. Currently classical gain tuning techniques are used to design a controller for a specific mission, which may hinder the vehicle’s ability to perform multiple missions if gains have to be re-tuned. Advanced nonlinear control methods like dynamic inversion and backstepping may eliminate the need to use classical gain tuning techniques that may increase quick turnaround time, reliability, and performance. Both methods consider the dynamics of the vehicle allowing the controller to be applied to the whole flight envelope. However, they are model-based methods that require knowledge of plant aerodynamics. The objective was to develop a backstepping outer loop and dynamic inversion inner loop controller for a reusable launch vehicle configuration and evaluate its robustness characteristics by inserting aerodynamic uncertainties into the static and control surface aerodynamic data separately and together. Both dynamic inversion and backstepping were susceptible to control surface aerodynamic uncertainties more than static aerodynamics. The benefit of using dynamic inversion and backstepping was that it was formulated so that it decouples the system of equations as long as the dynamics were modeled accurately. The control variable became a bank of decoupled integrators. However, when uncertainties were introduced into the plant model, the controller was unable to accurately model the dynamics, which re-introduced axes coupling inherent in the plant. The coupling caused performance in one axis to degrade if another axis degraded

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

Vehicle Dynamics Control for Rollover Prevention

Vehicle rollover accidents are a particularly dangerous form of road accident. Existing vehicle dynamics controllers primarily deal with yaw stability, and are of limited use for dealing with problems of roll instability. This thesis deals with the development of a new type of vehicle dynamics control system, capable of preventing rollover accidents caused by extreme maneuvering. A control strategy based on limitation of the roll angle while following a yaw rate reference is presented. Methods for rollover detection are investigated. A new computationally–efficient control allocation strategy based on convex optimization is used to map the controller commands to the individual braking forces, taking into account actuator constraints. Simulations show that the strategy is capable of preventing rollover of a commercial van during various standard test maneuvers