Bringing optimal feedback controller design to practice

Although optimal feedback controller design based on H∞ or H2 criteria [1] has already proven its potential in academia, it has yet to find wide acceptance in industry. One explanation is the lack of software support for practitioners without expertise in optimal control. Matlab’s robust control toolbox [2] contains the core tools for H ∞ and H 2 control, but (i) it doesn’t allow for an easy and intuitive control problem formulation; (ii) it doesn’t support multi-objective controller designs; (iii) it doesn’t allow for unstable [3] or improper weights. To overcome these drawbacks we are developing a Matlab toolbox that combines an intuitive control problem formulation with efficient and numerically stable algorithms that overcome the drawbacks mentioned above.status: publishe

An LTI control toolbox - simplifying optimal feedback controller design

This paper presents a novel LTI control toolbox, aiming at transparent optimal feedback controller design. It provides a compact and intuitive syntax to model the control configuration and to formulate performance specifications based on an H_infinity criterion. Its core contains state-of-the-art solvers which are able to handle unstable weights. Moreover, improper weighting functions can be handled and state measurements are exploited to reduce the controller order. On account of these aspects, the synthesized controllers require no post-processing. A comparison with Matlab’s robust control toolbox shows a clear improvement regarding the expression of controller specifications and the computation time.status: publishe

Robust marker-tracking system for vision-based autonomous landing of VTOL UAVs

This article presents the development of a visionbased VTOL UAV docking system for outdoor applications. A new marker type is constructed, along with a robust detection algorithm based on the Hough transform, which forms the basis of the positioning system. For verification purposes, a binary classifier based on support vector machines is trained. Test data show great robustness against varying lighting, partial occlusion and unsharpness. The practical usefulness is demonstrated by creating a single tracking module, based upon the PX4FLOW camera. Equipping a quadrotor with the new positioning sensor allows it to perform a precision landing.status: publishe

LCToolbox – A MATLAB toolbox for robust control design

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LCToolbox: Facilitating optimal linear feedback controller design

Plenary lecturestatus: publishe

Development and implementation of a reconfigurable assembly cell

As product diversity increases and new designs succeed one another more rapidly than ever before, the value of recon- figurable manufacturing systems (RMSs) cannot be denied. Though the idea of RMSs exists already for a very long time [1], few of such systems have actually been developed. This abstract addresses the development and deployment of such a system, paying special attention to the key aspects of RMSs: modularity, scalability and integrability. The de- veloped RMS, presented in Figure 1, consists of two AGVs collecting orders at the movable work stations. A modular ceiling camera system posts position measurements on the network, allowing the AGVs to plan their path and dock near the right work station. On top of this, a central coordinator gathers tasks and dispatches them to the appropriate agent. The next sections briefly describe the different subsystems.status: publishe

A toolbox for robust control design: an illustrative case study

This paper presents LCToolbox, an open-source MATLAB software package facilitating robust linear feedback controller design. Its key feature is the automation of time-consuming pre- and postprocessing steps that are inextricable from modern control design techniques. In particular, the toolbox focuses on H-infinity loop shaping for linear time-invariant (LTI) and linear parameter-varying (LPV) systems. Since these methods require an accurate model to realize their full potential, the toolbox also supports the user to estimate LTI and LPV models using state-of-the-art system identification methods. Simulation tools are available in order to evaluate identified models and control performance. As such, this toolbox aims at supporting the user throughout the complete design process. The tailored data structures, functionalities and simulation tools are illustrated by means of a running case study considering trajectory tracking of a mobile platform with a kinematic model.status: Published onlin

Low-cost Carry-home Mobile Platforms for Project-based Evaluation of Control Theory

This paper presents mobile platforms that were recently designed in support of an introductory control course. Through dedicated assignments, the students are guided to implement and validate all parts of the course on a setup, ranging from basic time-domain system identification, over root locus analysis and loop shaping PID design, to state feedback, state estimation and Kalman filtering. The platforms are flexible, allowing for numerous extensions and variations; cheap, allowing for a large pool of setups from which the students can borrow platforms to take home; and of sufficient quality, allowing the students to get maximal insight in the course material. The setups are easy to set up and administer using the supporting material provided by the authors.status: publishe

Flexible Multi-Agent System for Distributed Coordination, Transportation & Localisation

© 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. This demonstration presents Flexonomy, a flexible autonomous system for distributed coordination, transportation and localisation in a lab-scale factory floor. It illustrates the use of multi-agent systems in manufacturing and leverages new Industry 4.0 design principles to cope with manufacturing requirements in factories of the future: rapidly changing customer needs, market volatility and shortened product life cycles. Three main contributions are identified: (i) distributed auction-based coordination allows local decision making and task allocation, (ii) distributed model predictive control-based transportation enables free space collision avoidance of automated guided vehicles (AGVs), and (iii) distributed vision-based localisation provides scalable and dynamic position information of key resources on the factory floor.status: publishe

Distributed Coordination, Transportation & Localisation in Industry 4.0

© 2018 IEEE. Factories of the future must be agile to adapt to rapidly changing customer needs, market volatility and shortened product life cycles. This requires flexibility in hardware and software at distinct levels of the factory and manufacturing process: multipurpose machines with fast change-overs, easy to use reconfigurable software and distributed decision-making are key. This paper leverages the new Industry 4.0 design principles to cope with these new manufacturing requirements: (i) distributed auction-based coordination allows local decision-making and task allocation, (ii) distributed model predictive control-based transportation enables free space collision avoidance of automated guided vehicles (AGVs), and (iii) distributed vision-based localisation provides scalable and dynamic position information of key resources on the factory floor. Furthermore, these contributions are brought together in a lab-scale reconfigurable manufacturing system to showcase modularity and distributed decision-making at several levels of a manufacturing process' logistics.status: publishe