Multiple Control Laws Research Articles

Deadbeat Flux Vector Control as a One Single Control Law Operating in the Linear, Overmodulation, and Six-Step Regions With Time-Optimal Torque Control

This article proposes an enhanced version of the Deadbeat Flux Vector Controller (DBFC) as a one single control law which can operate in the entire torque-speed plane. The operation at any feasible modulation index can be accomplished by adequate determination of the flux trajectories at the different operating regions (e.g., PWM, overmodulation (I and II), and six-step). Continuous and seamless transition between the four operating regions is guaranteed, where the modulation index changes linearly with speed between PWM and six-step (without abrupt change in torque or acoustic problems). With the proposed strategy, undesirable torque dynamics, stability problems, and increased computational efforts associated with using multiple control laws are avoided. The transient performance of DBFC at the maximum voltage limit is analyzed in detail in the flux plane. A time-optimal torque control algorithm is developed to achieve the fastest possible torque dynamics and to considerably reduce the settling time, without the use of a voltage margin. The torque can be controlled with high accuracy and high robustness to machine parameter variations. With DBFC, no trade-off between good steady-state six-step behavior and good transient performance is needed due to the decoupling of switching and calculation frequencies. The proposed DBFC controller offers valuable features, and it is simple to implement. Simulation and experimental results are provided to validate the proposed control algorithm, which is implemented on an automotive microcontroller with a high-power/high-performance automotive traction machine (IPMSM).

Performance-Driven Post-Processing of Control Loop Execution Schedules

The increasing demand for mapping diverse embedded features onto shared electronic control units has brought about novel ways to co-design control tasks and their schedules. These techniques replace traditional implementations of control with new methods, such as pattern-based scheduling of control tasks and adaptive sharing of bandwidth among control loops through orchestration of their execution patterns. In the current practice of control design, once the static execution schedule is prepared for control tasks, no further control-related optimization is attempted for improving the control performance. We introduce, for the first time, an algorithmic mechanism that re-engineers a recurrent control task by enforcing switching between multiple control laws, which are designed for compensating the non-uniform gaps between successive executions of the control task. We establish that such post-processing of control task schedules may potentially help in improving the combined control performance of the co-scheduled control loops that are executing on a shared platform.

Cluster‐based network model for drag reduction mechanisms of an actuated turbulent boundary layer

AbstractWe introduce a novel data‐driven reduced‐order modeling approach, a Cluster‐Based Network Model (CBNM). Starting point is a set of time‐resolved snapshots associated with one or multiple control laws. These snapshots are coarse‐grained into dozens of centroids using k‐means++ clustering. The dynamics is modelled in a network between these centroids comprising the transition probability and corresponding transit time. The transition parameters depend on the control law. CBNM is successfully applied to an actuated turbulent boundary layer flow. The results show that CBNM is an attractive alternative to POD models as the model is human interpretable and dynamically robust by construction.

Stability Analysis of Event-Triggered Anytime Control With Multiple Control Laws

To deal with time-varying processor availability and lossy communication channels in embedded and networked control systems, one can employ an event-triggered sequence-based anytime control (E-SAC) algorithm. The main idea of E-SAC is, when computing resources and measurements are available, to compute a sequence of tentative control inputs and store them in a buffer for potential future use. State-dependent random-time drift (SRD) approach is often used to analyze and establish stability properties of such E-SAC algorithms. However, using SRD, the analysis quickly becomes combinatoric and hence difficult to extend to more sophisticated E-SAC. In this technical note, we develop a general model and a new stability analysis for E-SAC based on Markov jump systems. Using the new stability analysis, stochastic stability conditions of existing E-SAC are also recovered. In addition, the proposed technique systematically extends to a more sophisticated E-SAC scheme for which, until now, no analytical expression had been obtained.

Consensus of second‐order multi‐agents with actuator saturation and asynchronous time‐delays

This study presents the consensus of a saturated second-order multi-agent system with non-switching dynamics that can be represented by a directed graph. The system is affected by data processing (input delay) and communication time-delays that are assumed to be asynchronous. The agents have saturation non-linearities, each of them is approximated into separate linear and non-linear elements. Non-linear elements are represented by describing functions. Describing functions and stability of linear elements are used to estimate the existence of limit cycles in the system with multiple control laws. Stability analysis of the linear element is performed using Lyapunov–Krasovskii functions and frequency domain analysis. A comparison of pros and cons of both the analyses with respect to time-delay ranges, applicability and computation complexity is presented. Simulation and corresponding hardware implementation results are demonstrated to support theoretical results.

Development of a Real-time Onboard and Ground Station Software System for a UAV Helicopter

We report in this paper the development of a real-time software system for an unmanned aerial vehicle (UAV) helicopter, which consists of an embedded computer onboard and a ground station served by a laptop. The software system for the onboard computer performs multiple tasks including data acquisition and measurement, servo driving, automatic flight control implementation, communications and data logging. The system for the ground station gives a flexible graphical interface monitoring the real-time status of the UAV helicopter. We present the frameworks and structures of the onboard and ground station systems. The onboard system employs a framework of multiple task threads with each thread being assigned to perform a specific task. Management and time scheduling for task threads together with the detailed implementation of automatic flight control laws are the main focuses of the onboard software system. A behavior-based architecture is designed to address task scheduling and event disposal for automatic control. A hierarchical and componential structure is developed to integrate multiple control laws and perform various helicopter behaviors. The ground station software system employs a two-layer framework, i.e., data transferring in background and data visualization in foreground.A variety of views are developed to display in-flight data received from the UAV helicopter in different forms including a 3D monitoring panel, which displays real-time data in 3D on the ground station.