A new educational software tool for robust control design using the QFT method

ABSTRACT We present a new educational software tool for robust control design based on the Quantitative Feedback Design (QFT) method. This is a graphical design methodology for systems with large parametric uncertainty, which has been successfully applied to many complex practical problems. The software tool is implemented in Matlab and may be used to introduce students to robust control methods via small and medium-size design applications. The software is a library of programmable M-files with open access to users and is intended as a test-bed for developing new techniques in this area and for automating parts of the design procedure, such as loop-shaping. A simple design problem is used to illustrate the main features of the software

Runtime translation of OCL-like statements on Simulink models : Expanding domains and optimising queries

Open-source model management frameworks such as OCL and ATL tend to focus on manipulating models built atop the Eclipse Modelling Framework (EMF), a de facto standard for domain specific modelling. MATLAB Simulink is a widely used proprietary modelling framework for dynamic systems that is built atop an entirely different technical stack to EMF. To leverage the facilities of open-source model management frameworks with Simulink models, these can be transformed into an EMF-compatible representation. Downsides of this approach include the synchronisation of the native Simulink model and its EMF representation as they evolve; the completeness of the EMF representation, and the transformation cost which can be crippling for large Simulink models. We propose an alternative approach to bridge Simulink models with open-source model management frameworks that uses an “on-the-fly” translation of model management constructs into MATLAB statements. Our approach does not require an EMF representation and can mitigate the cost of the upfront transformation on large models. To evaluate both approaches we measure the performance of a model validation process with Epsilon (a model management framework) on a sample of large Simulink models available on GitHub. Our previous results suggest that, with our approach, the total validation time can be reduced by up to 80%. In this paper, we expand our approach to support the management of Simulink requirements and dictionaries, and we improve the approach to perform queries on collections of model elements more efficiently. We demonstrate the use of the Simulink requirements and dictionaries with a case study and we evaluate the optimisations on collection queries with an experiment that compares the performance of a set of queries on models with different sizes. Our results suggest an improvement by up to 99% on some queries

Tilt control design for high-speed trains: a study on multi-objective tuning approaches

This paper presents work on a hybrid fuzzy control scheme to improve the performance of tilting trains using a nulling-based tilt strategy. Two multi-objective genetic algorithm tuning methods (MOGA and NSGAII) were employed to optimise both the fuzzy output membership functions and the controller parameters. The objective functions incorporated the tilt response and roll gyroscope signals for the deterministic (curved track) profile, and lateral acceleration for the stochastic (straight track) profile. Simulation results discuss the effectiveness of using the presented techniques for tuning the fuzzy control scheme via multiple objectives. The proposed scheme is compared with the conventional nulling-tilt approach and a manually tuned fuzzy controlle

LQG control of a high redundancy actuator

A high redundancy actuator, comprising a relatively large number of actuation elements, is being developed for safety critical applications. Some classical control results have previously been reported and this paper will focus on evaluation of the LQG control design. Three different design approaches will be presented and compared under different types of typical faults in the sub-actuation elements. Overall a LQG design using a physically motivated reduced order model appears to be the best approach