Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies, using pre-existing plant trajectory data is of great interest in industrial applications. Fuzzy controllers have been used in industry for decades as interpretable and efficient system controllers. In this study, we introduce a fuzzy genetic programming (GP) approach called fuzzy GP reinforcement learning (FGPRL) that can select the relevant state features, determine the size of the required fuzzy rule set, and automatically adjust all the controller parameters simultaneously. Each GP individual's fitness is computed using model-based batch reinforcement learning (RL), which first trains a model using available system samples and subsequently performs Monte Carlo rollouts to predict each policy candidate's performance. We compare FGPRL to an extended version of a related method called fuzzy particle swarm reinforcement learning (FPSRL), which uses swarm intelligence to tune the fuzzy policy parameters. Experiments using an industrial benchmark show that FGPRL is able to autonomously learn interpretable fuzzy policies with high control performance.Comment: Accepted at Genetic and Evolutionary Computation Conference 2018 (GECCO '18

Exploiting road traffic data for very short term load forecasting in smart grids

If accurate short term prediction of electricity consumption is available, the Smart Grid infrastructure can rapidly and reliably react to changing conditions. The economic importance of accurate predictions justifies research for more complex forecasting algorithms. This paper proposes road traffic data as a new input dimension that can help improve very short term load forecasting. We explore the dependencies between power demand and road traffic data and evaluate the predictive power of the added dimension compared with other common features, such as historical load and temperature profiles

Environmental Management Information Systems (EMIS) for Sustainable Development: A Conceptual Overview

Environmental management information systems (EMIS) is defined as \u27organizational-technical systems for systematically obtaining, processing, and making available relevant environmental information available in companies\u27. Such systems evolved out of a growing need to manage environmental information in response to internal and external pressures such as regulations, consumers, stockholders, and changes in the business environments. While over the past decade EMIS have proliferated in the corporate landscape, these systems have received little attention within the information systems research community as whole. The objective of this paper is to serve as a tutorial providing a conceptual overview of EMIS, highlighting organizational and technical issues, as well as research opportunities. In this paper we suggest that there are significant and relatively untapped research synergies existing between information systems and environmental management for sustainable development at the organizational and technical levels

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Validation and Verification of Aircraft Control Software for Control Improvement

Validation and Verification are important processes used to ensure software safety and reliability. The Cooper-Harper Aircraft Handling Qualities Rating is one of the techniques developed and used by NASA researchers to verify and validate control systems for aircrafts. Using the Validation and Verification result of controller software to improve controller\u27s performance will be one of the main objectives of this process. Real user feedback will be used to tune PI controller in order for it to perform better. The Cooper-Harper Aircraft Handling Qualities Rating can be used to justify the performance of the improved system

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154105/1/kampfner1997.pd

Systemic Innovation in a Distributed Network Paradox or Pinnacle?

Previous research has suggested that there is a dichotomy of organisational practices: companies involved in autonomous or modularised innovations, it is argued, benefit from decentralised approaches where coordination primarily takes place through the marketplace, whereas the benefits of systemic innovation are said to be appropriated best by centralised organisations. However, case studies of subcontractors to the Danish wind turbine industry suggest that the ability to meet heterogeneous demands plays an important role for the success of different forms of organisational practices in relation to innovation. The modularised versus systemic architecture approach therefore appears to be a too sweeping dichotomy for describing what can better be perceived as an array of different practices for balancing innovation contribution with the ability of individual firms to appropriate innovation benefits – and a heterogeneous market perception is a core element in building and sustaining this ability.Organisational Forms, Innovation System, Knowledge Complementarities, Value Appropriation