Intelligent Control Systems for Industry 4.0 – Centre for Intelligent Systems

In a Nutshell

State Research Grant

The project is supported by the Estonian Research Grant nr. PRG658.

Research with Impact

The project aim is to research advanced control systems with novel industrial applications.

Long term

The project is running for four years from January 2020 to December 2024.

One of the main challenges of the future control systems will be data-driven control design for rapidly changing environments that will be able to increase efficiency and reduce energy consumption, emissions and pollution. Data-driven control algorithms lying on the border between control theory, machine learning and data science have the largest impact on the future of humanity.

CENTRE FOR INTELLIGENT
SYSTEMS | TALTECH

Efficient and safe control algorithms

We design safe and efficient control systems that are endowed with machine intelligence

Digital twins for training and SCADA applications

We do this by recreating accurate digital twin models of the controlled entities and processes

Improving heating, ventilation, and A/C systems

With knowledge of accurate process models we can improve heating, ventilation and A/C and make it much more energy efficient

Improving SCADA systems with Data Science

Control process operators can also benefit from using advanced SCADA systems built with Data Science and Digital Twins—including those in Extended Reality

Ensuring less wasteful production with demand side management

On the consumer end, we are able to accomplish a resource consumption equilibrium by applying data driven demand side management

A Smart City is a Green City — less emissions, cleaner air

A Smart City is a Green City—with intelligent control we can reduce energy waste and harmful emissions and enjoy a cleaner air

Improving control algorithms leads to better energy efficiency and a greener environment

Intelligent control as part of Industry 4.0 will thus lead to better energy efficiency and a greener environment

Project Goals

The aim of the project is to develop an industrial software framework for control engineers and researchers consisting of a set of methods for automated analysis, modelling and design of the most efficient control system from data representing the controlled process. The developed methodology will significantly simplify implementation of advanced control techniques in the industry, increase their efficiency and enable industrial control systems to acquire knowledge and learn from constantly growing data sets.

Project Lead

Eduard Petlenkov

Professor
Head of Centre

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Developed software

FOMCON Toolbox for MATLAB

FOMCONpy toolbox for Python

GPTIPS2F Toolbox for MATLAB

Publications

A. Remenyi, S. Alsaleh, and A. Tepljakov, “Assessing Interaction Mechanics in Extended Reality for Control Engineering Applications,” in 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2024, pp. 1–7. [DOI] [Bib]
K. Nosrati, J. Belikov, A. Tepljakov, and E. Petlenkov, “Extended Fractional Singular Kalman Filter,” Applied Mathematics and Computation, vol. 448, pp. 127950, 2023. [DOI] [Bib]
V. Skiparev, K. Nosrati, J. Belikov, A. Tepljakov, and E. Petlenkov, “An Enhanced NN-based Load Frequency Control Design of MGs: A Fractional order Modeling Method,” in 2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG). IEEE, 2023. [DOI] [Bib]
K. Nosrati, A. Tepljakov, E. Petlenkov, V. Skiparev, J. Belikov, and Y. Levron, “Constrained Intelligent Frequency Control in an AC Microgrid: An Online Reinforcement Learning Based PID Tuning Approach,” in 2023 IEEE Power & Energy Society General Meeting (PESGM), 2023, pp. 1–5. [Bib]
A. Onile, J. Belikov, Y. Levron, and E. Petlenkov, “Energy efficient behavior modeling for demand side recommender system in solar microgrid applications using multi-agent reinforcement learning model,” Sustainable Cities and Society, vol. 90, pp. 104392, 2023. [DOI] [Bib]
K. Nosrati, J. Belikov, A. Tepljakov, and E. Petlenkov, “Optimal Robust Filter of Uncertain Fractional Order Systems: A Penalized Deterministic Approach,” IEEE Control Systems Letters, vol. 7, pp. 1075–1080, 2023. [DOI] [Bib]
V. Skiparev, K. Nosrati, A. Tepljakov, E. Petlenkov, Y. Levron, J. Belikov, and J. Guerrero, “Virtual Inertia Control of Isolated Microgrids Using an NN-Based VFOPID Controller,” IEEE Transactions on Sustainable Energy, pp. 1–11, 2023. [DOI] [Bib]
M. Ghorbani, M. Tavakoli-Kakhki, A. Tepljakov, E. Petlenkov, A. Farnam, and G. Crevecoeur, “Robust Stability Analysis of Interval Fractional-Order Plants With Interval Time Delay and General Form of Fractional-Order Controllers,” IEEE Control Systems Letters, vol. 6, pp. 1268–1273, 2022. [DOI] [Bib]
V. Vansovits, E. Petlenkov, A. Tepljakov, K. Vassiljeva, and J. Belikov, “Bridging the Gap in Technology Transfer for Advanced Process Control with Industrial Applications,” Sensors, vol. 22, no. 11, pp. 4149, 2022. [DOI] [Bib]
S. Alsaleh, A. Tepljakov, M. Tamre, V. Kuts, and E. Petlenkov, “Digital Twin Simulations Based Reinforcement Learning for Navigation and Control of a Wheel-on-Leg Mobile Robot,” in Volume 2B: Advanced Manufacturing. American Society of Mechanical Engineers, 2022. [DOI] [Bib]
A. Ferrantelli, J. Belikov, E. Petlenkov, M. Thalfeldt, and J. Kurnitski, “Evaluating the Energy Readiness of National Building Stocks Through Benchmarking,” IEEE Access, vol. 10, pp. 45430–45443, 2022. [DOI] [Bib]
M. Ghorbani, M. Tavakoli-Kakhki, A. Tepljakov, and E. Petlenkov, “Robust stability analysis of smith predictor based interval fractional-order control systems: A case study in level control process,” IEEE/CAA Journal of Automatica Sinica, pp. 1–11, 2022. [DOI] [Bib]
M. Ghorbani, A. Tepljakov, and E. Petlenkov, “Stabilizing region of fractional-order proportional integral derivative controllers for interval fractional-order plants,” Transactions of the Institute of Measurement and Control, pp. 014233122211178, 2022. [DOI] [Bib]
S. Alsaleh, A. Tepljakov, A. Kose, J. Belikov, and E. Petlenkov, “ReImagine Lab: Bridging the Gap Between Hands-On, Virtual and Remote Control Engineering Laboratories Using Digital Twins and Extended Reality,” IEEE Access, vol. 10, pp. 89924–89943, 2022. [DOI] [Bib]
M. Meas, R. Machlev, A. Kose, A. Tepljakov, L. Loo, Y. Levron, E. Petlenkov, and J. Belikov, “Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI),” Sensors, vol. 22, no. 17, pp. 6338, 2022. [DOI] [Bib]
B. Alagoz, O. Simsek, D. Ari, A. Tepljakov, E. Petlenkov, and H. Alimohammadi, “An Evolutionary Field Theorem: Evolutionary Field Optimization in Training of Power-Weighted Multiplicative Neurons for Nitrogen Oxides-Sensitive Electronic Nose Applications,” Sensors, vol. 22, no. 10, pp. 3836, 2022. [DOI] [Bib]
A. Aksjonov, V. Ricciardi, K. Augsburg, V. Vodovozov, and E. Petlenkov, “Hardware-in-the-Loop Test of an Open-Loop Fuzzy Control Method for Decoupled Electrohydraulic Antilock Braking System,” IEEE Transactions on Fuzzy Systems, vol. 29, no. 5, pp. 965–975, 2021. [DOI] [Bib]
V. Vodovozov, Z. Raud, and E. Petlenkov, “Review on Braking Energy Management in Electric Vehicles,” Energies, vol. 14, no. 15, pp. 4477, 2021. [DOI] [Bib]
A. Onile, R. Machlev, E. Petlenkov, Y. Levron, and J. Belikov, “Uses of the digital twins concept for energy services, intelligent recommendation systems, and demand side management: A review,” Energy Reports, vol. 7, pp. 997–1015, 2021. [DOI] [Bib]
A. Tepljakov, B. Alagoz, C. Yeroglu, E. Gonzalez, H. Hosseinnia, E. Petlenkov, A. Ates, and M. Cech, “Towards Industrialization of FOPID Controllers: A Survey on Milestones of Fractional-Order Control and Pathways for Future Developments,” IEEE Access, vol. 9, pp. 21016–21042, 2021. [PDF] [DOI] [Bib]
A. Tepljakov, “Interactive Whiteboards in Extended Reality for Advanced Control System Design,” in 2021 44th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2021, pp. 283–287. [PDF] [DOI] [Bib]
M. Tarasevich, A. Tepljakov, E. Petlenkov, and V. Vansovits, “Genetic Programming based Identification of an Industrial Process,” in 2021 44th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2021. [DOI] [Bib]
S. Alsaleh, A. Tepljakov, M. Tamre, and E. Petlenkov, “Towards Artificial Intelligence Driven Immersive Environments in Virtual Reality for Industrial Applications,” in 2021 44th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2021, pp. 340–345. [DOI] [Bib]
J. Chen, B. Zhuang, A. Tepljakov, and E. Petlenkov, “Stabilization and uncertainty analysis of a time‐fractional reaction diffusion equation cascaded with a time‐fractional hyperbolic partial differential equation,” Asian Journal of Control, 2021. [DOI] [Bib]
O. Ademola, M. Leier, and E. Petlenkov, “Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme,” Sensors, vol. 21, no. 22, pp. 7529, 2021. [DOI] [Bib]
V. Vodovozov, E. Petlenkov, A. Aksjonov, and Z. Raud, “Neural Network Control of Green Energy Vehicles with Blended Braking Systems,” Renewable Energy and Power Quality Journal, vol. 19, pp. 344–349, 2021. [DOI] [Bib]
A. Köse, A. Tepljakov, and E. Petlenkov, “Intelligent Virtual Environments with Assessment of User Experiences,” in International Conference on Artificial Intelligence and Soft Computing (ICAISC 2021). Springer International Publishing, 2021, pp. 463–474. [DOI] [Bib]
J. Chen, A. Tepljakov, E. Petlenkov, Y. Chen, and B. Zhuang, “Boundary Mittag-Leffler stabilization of coupled time fractional order reaction-advection-diffusion systems with non-constant coefficients,” Systems & Control Letters, vol. 149, pp. 104875, 2021. [DOI] [Bib]
M. Sinimaa, M. Spichakova, J. Belikov, and E. Petlenkov, “Feature Engineering of Weather Data for Short-Term Energy Consumption Forecast,” in 2021 IEEE Madrid PowerTech. IEEE, 2021. [DOI] [Bib]
V. Vodovozov, A. Aksjonov, E. Petlenkov, and Z. Raud, “Neural Network-Based Model Reference Control of Braking Electric Vehicles,” Energies, vol. 14, no. 9, pp. 2373, 2021. [DOI] [Bib]
V. Skiparev, R. Machlev, N. Chowdhury, Y. Levron, E. Petlenkov, and J. Belikov, “Virtual Inertia Control Methods in Islanded Microgrids,” Energies, vol. 14, no. 6, pp. 1562, 2021. [DOI] [Bib]
A. Onile, J. Belikov, E. Petlenkov, and Y. Levron, “A Comparative Study on Graph-based Ranking Algorithms for Consumer-oriented Demand Side Management,” in 2021 IEEE Madrid PowerTech. IEEE, 2021. [DOI] [Bib]
A. Tepljakov and B. Alagoz, “Software Implementation of FOPID Controllers with Tuning Capability for Fractional FOPDT Plants,” in 2021 44th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2021, pp. 199–203. [DOI] [Bib]
G. Magdy, A. Bakeer, M. Nour, and E. Petlenkov, “A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids,” Energies, vol. 13, no. 21, pp. 5641, 2020. [DOI] [Bib]
H. Alimohammadi, B. Alagoz, A. Tepljakov, K. Vassiljeva, and E. Petlenkov, “A NARX Model Reference Adaptive Control Scheme: Improved Disturbance Rejection Fractional-Order PID Control of an Experimental Magnetic Levitation System,” Algorithms, vol. 13, no. 8, pp. 201, 2020. [DOI] [Bib]
M. Tarasevich, A. Tepljakov, E. Petlenkov, and V. Vansovits, “Modeling and Identification of an Industrial Hot Water Boiler,” 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), 2020. [DOI] [Bib]
V. Skiparev, J. Belikov, and E. Petlenkov, “Reinforcement Learning based Approach for Virtual Inertia Control in Microgrids with Renewable Energy Sources,” 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 2020. [DOI] [Bib]
B. Alagoz, A. Tepljakov, E. Petlenkov, and C. Yeroglu, “Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations,” Algorithms, vol. 13, no. 2, pp. 38, 2020. [DOI] [Bib]
T. Onyedi, A. Tepljakov, and E. Petlenkov, “FOMCONpy: Fractional-order Modelling and Control Library for Python,” 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), 2020. [DOI] [Bib]
S. Jersov and A. Tepljakov, “Digital Twins in Extended Reality for Control System Applications,” in 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. [DOI] [Bib]
A. Kose, A. Tepljakov, and E. Petlenkov, “Real Time Data Communication for Intelligent Extended Reality Applications,” 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2020. [DOI] [Bib]
V. Vodovozov, Z. Raud, A. Aksjonov, and E. Petlenkov, “Modelling of a Versatile Vehicle Braking System with a Fuzzy PID Torque Controller,” 2020 17th Biennial Baltic Electronics Conference (BEC), 2020. [DOI] [Bib]
J. Chen, A. Tepljakov, E. Petlenkov, Y. Chen, and B. Zhuang, “State and output feedback boundary control of time fractional PDE-fractional ODE cascades with space‐dependent diffusivity,” IET Control Theory & Applications, vol. 14, no. 20, pp. 3589–3600, 2020. [DOI] [Bib]
V. Vodovozov, E. Petlenkov, A. Aksjonov, and Z. Raud, “Fuzzy Gradient Control of Electric Vehicles at Blended Braking with Volatile Driving Conditions,” in Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2020. [DOI] [Bib]
A. Aksjonov, V. Vodovozov, K. Augsburg, and E. Petlenkov, “Blended Antilock Braking System Control Method for All-Wheel Drive Electric Sport Utility Vehicle,” in ELECTRIMACS 2019. Springer International Publishing, 2020, pp. 229–241. [DOI] [Bib]
J. Chen, A. Tepljakov, E. Petlenkov, and B. Zhuang, “Boundary state and output feedbacks for underactuated systems of coupled time-fractional PDEs with different space-dependent diffusivity,” International Journal of Systems Science, vol. 51, no. 15, pp. 2922–2942, 2020. [DOI] [Bib]
J. Chen, A. Tepljakov, E. Petlenkov, Y. Chen, and B. Zhuang, “Observation and stabilisation of coupled time‐fractional reaction-advection-diffusion systems with spatially‐varying coefficients,” IET Control Theory & Applications, vol. 14, no. 19, pp. 3128–3138, 2020. [DOI] [Bib]
J. Chen, A. Tepljakov, E. Petlenkov, and B. Zhuang, “Bilateral Output Feedback Control of Fractional PDEs with Space-Dependent Coefficients,” in IFAC World Congress 2020. Elsevier BV, 2020, pp. 3743–3748. [DOI] [Bib]
A. Maalberg, M. Kuntzsch, and E. Petlenkov, “Simulation of RF Noise Propagation to Relativistic Electron Beam Properties in a Linear Accelerator,” in IFAC-PapersOnLine. Elsevier BV, vol. 53, no. 2, 2020, pp. 348–354. [DOI] [Bib]
V. Vodovozov, Z. Raud, A. Aksjonov, and E. Petlenkov, “Fuzzy Logic Control of Electric Vehicles in Changing Braking Conditions,” in 2020 XI International Conference on Electrical Power Drive Systems (ICEPDS). IEEE, 2020. [DOI] [Bib]

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