Professor Mike Grimble

Publications

Speed tracking of an electric vehicle using a restricted structure NGMV control algorithm

Cebeci Cagatay, Grimble Michael

2022 European Control Conference, ECC 2022 European Control Conference, pp. 790-795 (2022)

https://doi.org/10.23919/ECC55457.2022.9838220

Multiple degrees of freedom active motion control of a hydraulically actuated crane

Balan Marius, Majecki Pawel, Grimble Michael, Blackwell Paul

OCEANS 2021 OCEANS 2021: San Diego - Porto Oceans Conference Record (IEEE) Vol 2021-September, pp. 1-6 (2022)

https://doi.org/10.23919/OCEANS44145.2021.9705747

Restricted structure polynomial systems approach to LPV generalized predictive control

Grimble M, Alotaibi S, Majecki P

7th IFAC Conference on Nonlinear Model Predictive Control (2021)

Nonlinear optimal generalized predictive functional control of piecewise affine systems

Alotaibi Sultan, Grimble M, Cavanini L

29th Mediterranean Conference on Control and Automation (2021)

Linear parameter-varying model predictive control of AUV for docking scenarios

Uchihori Hiroshi, Cavanini Luca, Tasaki Mitsuhiko, Majecki Pawel, Yashiro Yusuke, Grimble Michael, Yamamoto Ikuo, van der Molen Gerrit M, Morinaga Akihiro, Eguchi Kazuki

Applied Sciences Vol 11 (2021)

https://doi.org/10.3390/app11104368

Observer based restricted structure generalized predictive control for quasi-LPV nonlinear systems

Grimble Mike J, Majecki Pawel

IFAC-PapersOnLine Vol 53, pp. 4264-4271 (2020)

https://doi.org/10.1016/j.ifacol.2020.12.2480

More publications

Research Interests

• Theory and Application of Nonlinear and Robust Control Design Methods for Multivariable Systems.
• The theory and design of Novel adaptive control and estimation methods.
• Benchmarking and performance assessment of control systems and related condition monitoring problems.
• Design of applications in the automotive, aerospace, metal processing, marine process and manufacturing industries.

Professional Activities

Benefits and problems arising from the use of advanced control methods in industrial applications

Invited speaker

5/6/2013

More professional activities

Projects

International Workshop on Hybrid and Predict Control for Nonlinear Industrial Applications

Yue, Hong (Principal Investigator) Grimble, Michael (Co-investigator)

The International Workshop on Hybrid and Predictive Control for Nonlinear Industrial Applications was held on 28th-30th April 2009 in Glasgow. This workshop was organised by the Industrial Control Centre in the University of Strathclyde. The aim of running this workshop is to expand a sequence of nonlinear control workshops that were held at the University of Strathclyde into a more international event and one which provides an opportunity for research students to both learn and contribute. The most recent developments in nonlinear predictive control, control of hybrid systems and distributed control systems are well covered during the 3-day workshop. Problems in the implementation of advanced control and signal processing methods are considered and their use in embedded systems for applications such as wind turbine control and networked systems control are also discussed. The level of the presentations suits research students in the broad area of nonlinear control and applications. There are demonstrations of hardware and software tools for both real time control and for control systems design from National Instrument and Quanser Inc.

01-Jan-2008 - 14-Jan-2009

Medical Devices Doctoral Training Centre Renewal / RS4559

Connolly, Patricia (Principal Investigator) Bowers, Roy (Co-investigator) Buis, Arjan (Co-investigator) Conway, Bernard A (Co-investigator) Gourlay, Terry (Co-investigator) Grant, Mary (Co-investigator) Grimble, Michael (Co-investigator) Higham, Desmond (Co-investigator) Lakany, Heba (Co-investigator) McGarry, Anthony (Co-investigator) Meidan, Victor (Co-investigator) Orr, Philip (Co-investigator) Pratt, Judith (Co-investigator) Riches, Phil (Co-investigator) Rosochowski, Andrzej (Co-investigator) Rowe, Philip (Co-investigator) Wheel, Marcus (Co-investigator) Yan, Xiu (Co-investigator)

01-Jan-2008 - 31-Jan-2018

Nonlinear High Performance Real Time Control

Grimble, Michael (Principal Investigator) Katebi, Reza (Co-investigator)

One of the remaining unsolved problems in control design is the development of simple and practical controllers for real-time control, based on a sound theoretical basis, for systems with severe nonlinearities and constraints. Although all dynamic systems are nonlinear, classical approaches to analysis and design are almost universally based on linear time-invariant approximations to the dynamic characteristics. However, classical approaches are no longer adequate because of the increasing performance needs of modern industry, which require plants to be operated in regions where there are constraints and strong non-linear behaviour. Combined with the fact that most existing non-linear control techniques used by industry are empirically based and, as a result, difficult to tune and analyse, there is a real need for a scientifically more rigorous framework for practical non-linear multivariable control. This is a cooperative project in which the research work is divided between the Industrial Control Centre, University of Strathclyde and the Department of Aerospace Engineering, University of Glasgow. It builds upon the new nonlinear generalized minimum variance (NGMV) control design ideas developed at University of Strathclyde. The project will attack the problem of synthesising nonlinear controller design using two complementary philosophies: the traditional approach of a purely theoretical foundation tested through realistic case studies and the alternative, practical view of tailoring advanced control research to address specific engineering problems. Motivation for this second approach comes from the fact that bespoke nonlinear controllers already exist in many engineering systems and this practical experience should be harnessed in the search for complete theory. The project involves five very significant and difficult scientific challenges that should make the proposed method suitable for the most challenging real-time applications. These theoretical challenges include:
1. Development of a Nonlinear Predictive Control facility which is much faster than existing solutions for machinery controls and faster processes.
2. Include new Constraint Handling features in both the predictive and non-predictive versions.
3. Introduce measures to guarantee some minimum Robustness Margins.
4. Develop real time Labview based implementation with pre-specified low order Restricted Structure implementation.
5. Introduce a Learning and adaptation feature for applications where plant models change slowly.
The last feature may seem particularly ambitious but the NGMV family of control structures has a useful property that its structure is very suitable for learning or adaptive system. That is, any nonlinear plant subsystems affect the controller structure and solution in a very simple way.

01-Jan-2008 - 31-Jan-2010

Self organisation in the immune system

Grimble, Michael (Principal Investigator) Brewer, James (Co-investigator) Garside, Paul (Co-investigator) Giovanini, Leonardo (Co-investigator) Oppo, Gian-Luca (Co-investigator)

The in vivo visualization of dynamic processes in lymphoid tissues by two-photon microscopy opens up possibilities for a combination of modelling, testing and experimental approaches to understand the behaviour of the immune system. A key element to develop larger models of immune response is the understanding of the cell activation, proliferation and interaction mechanisms. The aim of the project is to develop a theoretical and algorithmic framework to model and simulate the behaviour of T-cells in different environments and conditions using multi/agent dynamic systems and self-organizing systems. The proposed framework will reduce the burden on the modeling and simulation of immune system. A major step forward will be achieved by drawing inspiration from behavioural science, control engineering, physical and mathematical modelling. The final multi-agent model represents a multi-discipline integration of research concepts and simultaneously a substantial improvement of the present state of the art that fails to identify the mechanisms responsible for T-cell activation and proliferation. The integration of the activities in three research units at Strathclyde guarantees the accuracy of the final model that will be tested against a variety of experimental data and put the applicants in a unique position for the achievement of the objectives not just in the UK but also at an international level.

01-Jan-2007 - 31-Jan-2008

INDUSTRIAL NON-LINEAR CONTROL AND REALTIME APPLICATIONS

Grimble, Michael (Principal Investigator) Katebi, Reza (Co-investigator) Ordys, Andrzej (Co-investigator)

01-Jan-2005 - 30-Jan-2010

Improved Inverse Simulation using Nonlinear Predictive Methods

Grimble, Michael (Principal Investigator) Ordys, Andrzej (Co-investigator)

01-Jan-2004 - 31-Jan-2008

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