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3rd International Conference on Intelligent Computing and Optimization, ICO 2020

作者： Drabecki, Mariusz Institute of Control and Computation Engineering Warsaw University of Technology 15/19 Nowowiejska Street Warsaw Poland

ISBN: (纸本)9783030681531

In this paper a method for ensuring network feasibility of power flow (in terms of all network constraints), when energy in power system is balanced via peer-to-peer contracts, is proposed and analyzed. The method considers subjective benefits (utility functions) of market participants. The method is based on two optimization problems originated from Optimal Power Flow standard formulations, which can be solved by system’s operator. It possibly can be used in power systems with high penetration of distributed energy resources (DERs) to give incentive to build and actively control those resources by market participants. The method was tested on 9-bus test system, under three different preference scenarios. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electric load flow

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Nonlinear predictive control based on multivariable neural Wiener models

Nonlinear predictive control based on multivariable neural W...

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Lecture Notes in Computer Science

作者： Lawryńczuk, Maciej Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 00-665 Warsaw Poland

ISBN: (纸本)9783642202810

This paper describes a nonlinear Model Predictive control (MPC) scheme in which a neural Wiener model of a multivariable process is used. The model consists of a linear dynamic part in series with a steady-state nonlinear part represented by neural networks. A linear approximation of the model is calculated on-line and used for prediction. Thanks to it, the control policy is calculated from a quadratic programming problem. Good control accuracy and computational efficiency of the discussed algorithm are shown in the control system of a chemical reactor for which the classical MPC strategy based on a linear model is unstable. © 2011 Springer-Verlag.

关键词： computational efficiency

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Fault detection and accommodation by means of neural networks. Application to the boiler unit

Fault detection and accommodation by means of neural network...

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7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Systems, SAFEPROCESS'09

作者： Patan, Krzysztof Korbicz, Jozef Institute of Control and Computation Engineering University of Zielona Gora ul. Podgorna 50 65-246 Zielona Gora Poland

ISBN: (纸本)9783902661463

The work presented in this paper deals with a fault tolerant control system designed for a boiler unit. The main core of the proposed system is the so-called on-line fault approximator built using locally recurrent neural networks. The on-line stable training of the fault approximator is developed for monitoring of the controlled system. The obtained fault estimator is then used for the fault detection as well as for the fault accommodation. Computer experiments illustrate the performance of the proposed system for a boiler unit. © 2009 IFAC.

关键词： Fault detection

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Multiple AGV fault-tolerant within an agile manufacturing warehouse

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IFAC-PapersOnLine 2019年第13期52卷 1914-1919页

作者： Witczak, Marcin Majdzik, Pawel Stetter, Ralf Lipiec, Bogdan Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Faculty of Mechanical Engineering University of Applied Sciences Ravensburg-Weingarten Weingarten Germany Steinbeis Transfer Center Automotive Systems Ravensburg Germany

The current trend towards Industry 4.0 leads to several important aspects that concern future warehouse systems. The holistic digitalization efforts behind this trend may enable sustainable and resilient processes within warehouses and may increase their agility, but require elaborate control and diagnosis systems. This paper concentrates on one prominent means for increasing the agility - the employment of multiple automated guided vehicles (AGVs). Due to the complexity of a system with multiple AGVs, model predictive control (MPC) algorithms are required for effective and efficient operation. In industrial reality, uncertainties cannot be avoided, it is therefore highly desirable that these algorithms can handle such uncertainties and minor inconsistencies. The precedent necessities led to a strategy based on a fault-tolerant control framework, which is based on max-plus algebra with a model predictive control scheme. The applicability of this strategy is validated on the example of the feedings system of an high-bay warehouse. © 2019, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Model predictive control Agile manufacturing systems Algebra Automatic guided vehicles Fault tolerance Predictive control systems Warehouses Agile manufacturing AGVs system Automated guided vehicles Diagnosis systems Fault tolerant control Fault tolerant Max plus algebra Warehouse systems

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Multi-stream Fusion in Image Sets Comparison

Multi-stream Fusion in Image Sets Comparison

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International Conference on Automation, AUTOMATION 2021

作者： Piwowarski, Pawel Kasprzak, Wlodzimierz Warsaw University of Technology Institute of Control and Computation Engineering ul. Nowowiejska 15/19 Warszawa00-665 Poland

ISBN: (纸本)9783030748920

A unique problem is considered: how to automatically determine whether two images (pictures, drawings, or photos) show the same 3D object pictured in different views. Similarity or equality of the objects seen despite the spotting, size or angle of view is one of the biggest challenges. Thus, a unique proposition of solving this task is proposed. In this complex solution image sets are compared and following question is answered: are these sets similar in the sense that they present an object of the same type? The approach uses CNN-like deep neural networks for object region masking, specific feature extraction and proper type classification, and similarity measures for data matching. Experimental validation is performed on a public car image database. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image classification

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A Multiple Actuator and Sensor Fault Estimation for Dynamic Systems 21st

A Multiple Actuator and Sensor Fault Estimation for Dynamic ...

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21st Polish control Conference, PCC 2023

作者： Pazera, Marcin Witczak, Marcin Korbicz, Jozef Institute of Control and Computation Engineering University of Zielona Gora ul. Szafrana 2 Zielona Gora65-516 Poland

ISBN: (纸本)9783031351693

The paper deals with the problem of simultaneous actuator and sensor fault estimation for linear dynamic systems on which influence unknown exogenous disturbances. The most common approach of dealing with fault estimation approach is that either actuator or sensor fault estimation schemes are provided in the literature. This paper proposes a kind of a fusion of those approaches which results with the capability of estimation of actuator and sensor faults which might appear in the system simultaneously. The novelty relies on that the unwelcome rate of change of the fault factor is vanished which simplifies the design problem. The methodology utilized in the paper to attain the robustness is the so-called Quadratic boundedness approach. In the final part of the paper, the illustrative example with the implementation to the laboratory Multi-Tank system is provided which shows the performance of the proposed approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Actuators

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Model Predictive control of a Dynamic System with Fast and Slow Dynamics: Implementation Using PLC 20th

Model Predictive Control of a Dynamic System with Fast and S...

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20th Polish control Conference, PCC 2020

作者： Plamowski, Sebastian Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 Warsaw00-665 Poland

ISBN: (纸本)9783030509354

The article presents Model Predictive control (MPC) of a multivariable laboratory process using Programmable Logic controller (PLC). The Dynamic Matrix control (DMC) MPC algorithm is used in which a step-response model of the process is used for prediction. Two main practical issues are discussed. Firstly, it is shown how to deal with DMC control of a dynamical systems in which some variables react quickly and some slowly. In order to deal with fast and slow dynamics, a decomposed control structure based on the DMC algorithm is used. Secondly, the decomposed DMC control structure is implemented using the PLC controller, taking into account the PLC resources. Results of real laboratory experiments are present to show effectiveness of the discussed method. © 2020, Springer Nature Switzerland AG.

关键词： Model predictive control

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Towards integrated tracking fault-tolerant control for Takagi-Sugeno systems 63

Towards integrated tracking fault-tolerant control for Takag...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Witczak, Marcin Pazera, Marcin Institute of Control and Computation Engineering University of Zielona Gora ul. Szafrana 2 Zielona Gora65-516 Poland

ISBN: (纸本)9798350316339

This paper addresses the challenge of combining fault estimation and fault-tolerant control for constrained non-linear systems subject to bounded external disturbances. To handle the nonlinearities, the fuzzy Takagi-Sugeno (TS) methodology is utilised. As a consequence, gains of the estimator and controller are calculated for all the vertices of the polytopic set. Specifically, the intertwined nature of control and estimation leads to mutual influence, necessitating a novel integration approach to avoid deteriorating the overall system performance. A new strategy is introduced, grounded on a critical existence condition that is both necessary and sufficient. The suggested method operates through output feedback and unfolds in two distinct phases: the off-line phase involves a straightforward optimization task utilizing the set of Linear Matrix Inequalities (LMIs), while the on-line phase tackles a deterministic model predictive control issue. © 2024 IEEE.

关键词： Predictive control systems

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Two nonlinear predictive control algorithms based on structured neural models

Two nonlinear predictive control algorithms based on structu...

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作者： Lawrynczuk, Maciej Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 00-665 Warsaw Poland

ISBN: (纸本)9783902661333

This paper describes two nonlinear Model Predictive control (MPC) algorithms with neural models of a special structure and their applications to a bioreactor. The model calculates the many-step ahead prediction without the necessity of being used recursively, the prediction error is not propagated. The first algorithm solves on-line a nonlinear optimisation problem. In order to reduce the computational burden, in the second algorithm the structured neural model is used on-line to determine the local linearisation and the nonlinear free trajectory. It is more computationally efficient and reliable, because only a quadratic optimisation problem has to be solved. Although being suboptimal, the second algorithm gives closed-loop control performance similar to that obtained in the first algorithm. Copyright © 2007 IFAC.

关键词： Quadratic programming

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Identification of Linear Models of a Tandem-Wing Quadplane Drone: Preliminary Results 1

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20th Polish control Conference, PCC 2020

作者： Okulski, Michal Lawryńczuk, Maciej Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 Warsaw00-665 Poland

ISBN: (数字)9783030509361

ISBN: (纸本)9783030509354

A tandem-wing quadplane drone has been built to study control strategies and develop high-performance onboard controllers. In hover flight, the quadplane behaves like a classic quadcopter. Highly non-linear dynamics of the orientation stabilization need a state-of-the-art Model Predictive controller (MPC). To develop such a controller, an accurate model of the drone needs to be identified – ideally, a linear model. This paper present preliminary results of identifying two linear models: a State-Space Model derived from Newton dynamic principles and a novel Recurrent Neural Network based linear model. © 2020, Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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