Implementation of a C Library of Kalman Filters for Application on Embedded Systems

Having knowledge about the states of a system is an important component in most control systems. However, an exact measurement of the states cannot always be provided because it is either not technically possible or only possible with a significant effort. Therefore, state estimation plays an important role in control applications. The well-known and widely used Kalman filter is often employed for this purpose. This paper describes the implementation of nonlinear Kalman filter algorithms, the extended and the unscented Kalman filter with square-rooting, in the programming language C, that are suitable for the use on embedded systems. The implementations deal with single or double precision data types depending on the application. The newly implemented filters are demonstrated in the context of semi-active vehicle damper control and the estimation of the tire–road friction coefficient as application examples, providing real-time capability. Their per-formances were evaluated in tests on an electronic control unit and a rapid-prototyping platform

A QP Solver Implementation for Embedded Systems Applied to Control Allocation

Quadratic programming problems (QPs) frequently appear in control engineering. For use on embedded platforms, a QP solver implementation is required in the programming language C. A new solver for quadratic optimization problems, EmbQP, is described, which was implemented in well readable C code. The algorithm is based on the dual method of Goldfarb and Idnani and solves strictly convex QPs with a positive definite objective function matrix and linear equality and inequality constraints. The algorithm is outlined and some details for an efficient implementation in C are shown, with regard to the requirements of embedded systems. The newly implemented QP solver is demonstrated in the context of control allocation of an over-actuated vehicle as application example. Its performance is assessed in a simulation experiment

Advanced Controller Development Based on eFMI with Applications to Automotive Vertical Dynamics Control

High-level modeling languages facilitate system modeling and the development of control systems. This is mainly achieved by the automated handling of differential algebraic equations which describe the dynamics of the modeled systems across different physical domains. A wide selection of model libraries provides additional support to the modeling process. Nevertheless, deployment on embedded targets poses a challenge and usually requires manual modification and reimplementation of the control system. The novel proposed eFMI Standard (Functional Mock-up Interface for embedded systems) introduces a workflow and an automated toolchain to simplify the deployment of model-based control systems on embedded targets. This contribution describes the application and verification of the eFMI workflow using a vertical dynamics control problem with an automotive application as an example. The workflow is exemplified by a control system design process which is supported by the a-causal, multi-physical, high-level modeling language Modelica. In this process, the eFMI toolchain is applied to a model-based controller for semi-active dampers and demonstrated using an eFMI-based nonlinear prediction model within a nonlinear Kalman filter. The generated code was successfully tested in different validation steps on the dedicated embedded system. Additionally, tests with a low-volume production electronic control unit (ECU) in a series-produced car demonstrated the correct execution of the controller code under real-world conditions. The novelty of our approach is that it automatically derives an embedded software solution from a high-level multi-physical model with standardized eFMI methodology and tooling. We present one of the first full application scenarios (covering all aspects ranging from multi-physical modeling up to embedded target deployment) of the new eFMI tooling

Recent Research on Automotive Control at DLR Institute of System Dynamics and Control - An Overview

Safety, comfort, and responsible use of natural resources are motivating the work regarding road vehicles in the automotive research group at the DLR (German Aerospace Center) Institute of System Dynamics and Control. The present article presents an overview of the research activities of this group, including recent results on energy management, vehicle dynamics, and intelligence. Most of this research has been experimentally validated in the ROboMObil, a modular robotic electric vehicle with a highly integrated mechatronic chassis, developed by DLR. These activities are in particular taking advantage of the opportunities offered by digitalization, automation, and electrification in order to decrease the conflict between mobility demands and its harmful collateral effects