Control as an Enabler for Electrified Mobility

This article outlines the importance of electrified mobility (e-mobility) in modern transport. One key goal of this review is to illustrate the role that control has played, and must continue to play, as e-mobility grows. The coordination of power in multiple modes (mechanical, electrical, and thermal) requires sophisticated controller algorithms. This review advocates for model-based approaches to control since there may not be readily available physical systems from which to gather data and do data-based control. A second goal of the article is to present methods for modeling these powertrain systems that are modular, scalable, flexible, and computationally efficient. A graph-based approach satisfies many of the desired criteria. The third goal is to review control approaches for these classes of systems and detail a hierarchical approach that makes trades across different domains of power. Optimization-based approaches are well suited to achieving the regulation and tracking goals, along with the minimization of costs and the satisfaction of constraints. Multiple examples, within this article and the references therein, support the presentation throughout. This field of e-mobility is rapidly growing, and control engineers are uniquely positioned to have an impact and lead many of the critical developments. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Composite adaptive posicast controller for the wing rock phenomenon in a delta-wing aircraft

The nonlinear dynamic phenomenon like wing rock is one of the important issues in the high performance aircraft autopilot design. This phenomenon occurs in the form of constant amplitude oscillations in the roll dynamics, during the flight at high angles of attack (AOAs) and endangers carrying out the mission of an aircraft. In this paper, a composite adaptive posicast controller is designed for the wing rock phenomenon in a delta-wing aircraft with known input delay. The existence of the input delay besides the parametric uncertainties of the system dynamics adds to the complexity of the problem and can cause undesirable troubles in regulation and tracking performance or instability in the control system. Consequently, there is a need for a controller that can provide the stability and desirable regulation and tracking for the system. The proposed control method uses the system state forecasting and the composite model reference adaptive controller in an integrated control structure based on linear quadratic regulator (LQR). Combining the tracking error and the prediction error to form the adaptive laws in the composite model reference adaptive controller improves the characteristics of the system response and provides a better performance compared to the model reference adaptive controller in which the adaptive laws are formed only with the tracking error. Simulation results show the efficiency of the composite adaptive posicast controller in counteracting the system uncertainties in the presence of considerably large input delay cases.