Impact of algorithm design in implementing real-time active control systems

This paper presents an investigation into the impact of algorithm design for real-time active control systems. An active vibration control (AVC) algorithm for flexible beam systems is employed to demonstrate the critical design impact for real-time control applications. The AVC algorithm is analyzed, designed in various forms and implemented to explore the impact. Finally, a comparative real-time computing performance of the algorithms is presented and discussed to demonstrate the merits of different design mechanisms through a set of experiments

Real-Time Anticipatory Suspension Control for Single Event Disturbances

Most commercial vehicles currently on the market are still equipped with a passive suspension system, while some luxury brands may already use an adaptive suspension. Active suspension systems on the other hand are rarely found, however, they offer great opportunities to close the gap of the well-known trade-off between ride comfort and handling. Besides that, they can also be used to mitigate single event disturbances, an objective of the USA army as announced in a solicitation which initiated and motivated this research. In addition to that, several studies were found stating the impact and danger of potholes and their impact on the vehicle and passenger. Reviewing the literature, several control strategies for controlling active suspension systems were found. However, most of these approaches used feedback control and did not try to mitigate single event disturbances. Since literature also suggested making use of look ahead preview, research at the Performance Engineering Research Lab at Virginia Tech was started in 2015 combining look ahead preview and an adaptive system to generate optimal force profiles. This introductory research succeeded and proved the used approach to be very promising. However, the used adaptive system was not designed to operate in real-time and did not show any correlation between different road profiles. Therefore, the main objective of this research project is to evaluate and analyze each of the adaptive systems by searching for correlations in their solutions. The results then should be used in order to design a control law which emulates the adaptive system and can be used in a real-time environment. First, an overall research methodology was derived. According to this a software application was developed which extracts ideal force profiles from single event disturbance signals in order to miti- gate their impact to the vehicle. The application uses a quarter car model with a partially loaded active suspension system, a set of predefined road profiles, a road profile preprocessor, and an adaptive algorithm. The preprocessing includes geometric filtering using a Tandem-Cam Model and the adaptive processor used an iterative version of the Filtered-X Last-Mean-Square algorithm. During evaluation and analysis of several generated data sets, high correlations in the generated and adjusted adaptive systems were discovered. From these an empirical and theoretical universal filter model was derived, which was then used to design an open-loop control law named Optimal Force Control. The original control law and an adjusted version designed for a real-time environment were tested for all predefined road profiles over all considered vehicle velocities and prove to perform much better than the offline solution using the adaptive system. In summary, a control law named Optimal Force Control was designed which can be used and implemented in a vehicle to extract an analytical and ideal force profile given a road profile input. Implementing an active suspension system with tracking controller, this approach can be used in order to mitigate single event disturbance signals by reducing the vertical vehicle acceleration

Intelligent Learning Algorithms for Active Vibration Control

YesThis correspondence presents an investigation into the comparative performance of an active vibration control (AVC) system using a number of intelligent learning algorithms. Recursive least square (RLS), evolutionary genetic algorithms (GAs), general regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS) algorithms are proposed to develop the mechanisms of an AVC system. The controller is designed on the basis of optimal vibration suppression using a plant model. A simulation platform of a flexible beam system in transverse vibration using a finite difference method is considered to demonstrate the capabilities of the AVC system using RLS, GAs, GRNN, and ANFIS. The simulation model of the AVC system is implemented, tested, and its performance is assessed for the system identification models using the proposed algorithms. Finally, a comparative performance of the algorithms in implementing the model of the AVC system is presented and discussed through a set of experiments

An Adaptive Design Methodology for Reduction of Product Development Risk

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an essential step in the development of any system, especially for Embedded System. This paper introduces a novel adaptive design methodology, which incorporates step-wise prototyping and verification. With each adaptive step product-realization level is enhanced while decreasing the level of product uncertainty, thereby reducing the overall costs. The back-bone of this frame-work is the development of Domain Specific Operational (DOP) Model and the associated Verification Instrumentation for Test and Evaluation, developed based on the DOP model. Together they generate functionally valid test-sequence for carrying out prototype evaluation. With the help of a case study 'Multimode Detection Subsystem' the application of this method is sketched. The design methodologies can be compared by defining and computing a generic performance criterion like Average design-cycle Risk. For the case study, by computing Average design-cycle Risk, it is shown that the adaptive method reduces the product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure

Network emulation focusing on QoS-Oriented satellite communication

This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication

AltURI: a thin middleware for simulated robot vision applications

Fast software performance is often the focus when developing real-time vision-based control applications for robot simulators. In this paper we have developed a thin, high performance middleware for USARSim and other simulators designed for real-time vision-based control applications. It includes a fast image server providing images in OpenCV, Matlab or web formats and a simple command/sensor processor. The interface has been tested in USARSim with an Unmanned Aerial Vehicle using two control applications; landing using a reinforcement learning algorithm and altitude control using elementary motion detection. The middleware has been found to be fast enough to control the flying robot as well as very easy to set up and use