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Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
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Year 2024
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A hierarchical observer for a non-linear uncertain CSTR model of biochemical processes
PublicationThe problem of estimation of unmeasured state variables and unknown reaction kinetic functions for selected biochemical processes modelled as a continuous stirred tank reactor is addressed in this paper. In particular, a new hierarchical (sequential) state observer is derived to generate stable and robust estimates of the state variables and kinetic functions. The developed hierarchical observer uses an adjusted asymptotic observer...
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A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor
PublicationThis paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure....
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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An optimized dissolved oxygen concentration control in SBR with the use of adaptive and predictive control schemes
PublicationThis paper addresses the problem of optimizing control of the aeration process in a water resource recovery facility (WRRF) using sequencing batch reactor (SBR), one that affects the efficiency of wastewater treatment by stimulating metabolic reactions of microorganisms through dissolved oxygen (DO) level control, and accounts for the predominant part of operating costs. Two independent approaches to DO control algorithm design...
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Minimization of a ship's magnetic signature under external field conditions using a multi-dipole model
PublicationThe paper addresses the innovative issue of minimizing the ship's magnetic signature under any external field conditions, i.e., for arbitrary values of ambient field modulus and magnetic inclination. Varying values of the external field, depending on the current geographical location, affect only the induced part of ship's magnetization. A practical problem in minimizing the ship signature is separating permanent magnetization...
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Neural network model of ship magnetic signature for different measurement depths
PublicationThis paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...
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Optimising Sequencing Batch Reactor Operation Cycle Planning Using Evolutionary Algorithm
PublicationThe objective of this research was to optimise the operation cycle of the Sequencing Batch Reactor (SBR). Appropriate time balances of aerobic to anaerobic phases, as well as a set dissolved oxygen level are the key to ensuring the quality of effluent from the wastewater treatment process. The proposal to solve this optimisation problem was based on multi-objective optimisation using an evolutionary multi-objective optimisation...
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Optimizing Control of Wastewater Treatment Plant With Reinforcement Learning: Technical Evaluation of Twin-Delayed Deep Deterministic Policy Gradient Agent
PublicationControl of the wastewater treatment processes presents significant challenges due to the fluctuating nature of inflow and wastewater composition, alongside the system’s non-linear dynamics. Traditional control methods struggle to adapt to these variations, leading to an economically suboptimal operation of the process and a violation of norms imposed on the quality of wastewater discharged to the catchment area. This study proposes...
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PLC-based Implementation of Stochastic Optimization Method in the Form of Evolutionary Strategies for PID, LQR, and MPC Control
PublicationProgrammable logic controllers (PLCs) are usually equipped with only basic direct control algorithms like proportional-integral-derivative (PID). Modules included in engineering software running on a personal computer (PC) are usually used to tune controllers. In this article, an alternative approach is considered, i.e. the development of a stochastic optimizer based on the (μ,λ) evolution strategy (ES) in a PLC. For this purpose,...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Quantifying inconsistencies in the Hamburg Sign Language Notation System
PublicationThe advent of machine learning (ML) has significantly advanced the recognition and translation of sign languages, bridging communication gaps for hearing-impaired communities. At the heart of these technologies is data labeling, crucial for training ML algorithms on a huge amount of consistently labeled data to achieve models that generalize well. The adoption of language-agnostic annotations is essential to connect different sign...
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Robust asymptotic super twisting sliding mode observer for non-linear uncertain biochemical systems
PublicationThe problem of state estimation (reconstruction of the state vector) for a given class of biochemical systems under uncertain system dynamics has been addressed in this paper. In detail, the bioreactor at a water resource recovery facility represents the considered biochemical systems. The biochemical processes taking place in the bioreactor have been modelled using an activated sludge model. Based on this model, an appropriate...
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The influence of the geographic positioning system error on the quality of ship magnetic signature reproduction based on measurements in sea conditions
PublicationIn previous studies, the authors performed the magnetic signature reconstruction of the marine ship Zodiak as part of the measurement campaign focused on recording magnetic data and the relative position of a ship during its passage over a magnetometer immersed on the testing ground. A high degree of representation of the magnetic signature was obtained. However, the recorded measurement data revealed new patterns of the multidipole model...
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Wykorzystanie rachunku niecałkowitego rzędu w sterowaniu suwnicą 3D
PublicationSuwnica 3D jest obiektem stosowanym w różnych gałęziach przemysłu. Z punktu widzenia sterowania, jest to system dynamiczny, nieliniowy i wielowymiarowy. W artykule zaprojektowano dwa układy regulacji: z klasycznym regulatorem PID oraz z regulatorem PID ułamkowego rzędu. Przedstawiono analizę porównawczą zaprojektowanych układów regulacji.
Year 2023
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A comprehensive approach to SBR modelling for monitoring and control system design
PublicationThe aim of this research is to provide a comprehensive description of the Sequencing Batch Reactor (SBR) modelling for monitoring, control, and plant operational optimisation validation. The paper provides a detailed modelling of the SBR, its components and constituent processes. For this purpose, the mass balance principle and continuity equations were provided with a reactive term implemented using Activated Sludge Model (ASM)....
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A new approach to designing control of dissolved oxygen and aeration system in sequencing batch reactor by applied backstepping control algorithm
PublicationThe Wastewater Treatment Plant (WWTP) is a very complex system, due to its nonlinearity, time-variance, and multiple time scales in its dynamics among others. The most important control parameter in a WWTP is the Dissolved Oxygen (DO) concentration. The tracking problem of the DO concentration is one of the most fundamental issues in biological wastewater treatment. Proper DO concentration control is necessary to achieve adequate...
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Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
PublicationWastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it is difficult to design an efficient, optimal control system. The problem regarding biochemical reactions inside Sequential Batch Reactor...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Automated anonymization of sensitive data on production unit
PublicationThe article presents an approach to data anonymization with the use of generally available tools. The focus is put on the practical aspects of using open-source tools in conjunction with programming libraries provided by suppliers of industrial control systems. This universal approach shows the possibilities of using various operating systems as a platform for process data anonymization. An additional advantage of the described...
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DYNAMIC POSITIONING CAPABILITY ASSESSMENT BASED ON OPTIMAL THRUST ALLOCATION
PublicationThe article presents an efficient method of optimal thrust allocation over the actuators in a dynamically positioned ship, according to the DNV-ST-0111 standard, Level 1. The optimisation task is approximated to a convex problem with linear constraints and mathematically formulated as quadratic programming. The case study is being used to illustrate the use of the proposed approach in assessing the DP capability of a rescue ship....
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Employment of a Nonlinear Adaptive Control System for Improved Control of Dissolved Oxygen in Sequencing Batch Reactor
PublicationA proper control in a complex system, such as Wastewater Treatment Plant (WWTP) with each year is becoming increasingly important. High quality control can minimize an environmental impact as well as reduce operational costs of the WWTP. One of the core issues is providing adequate dissolved oxygen (DO) concetration for microorganisms used in a treatment process. An aeration process of the wastewater realised by an system consisting...
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Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set
PublicationThis paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time...
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
PublicationThis paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of the art and highlights the challenges and opportunities in this topic. By incorporating the best practices identified in this review, we established guidelines for the development of CMB detection...
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Fault detection and diagnostics of complex dynamic systems using Gaussian Process Models - nuclear power plant case study
PublicationThe article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working...
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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Magnetic signature reproduction of ferromagnetic ships at arbitrary geographical position, direction and depth using a multi-dipole model
PublicationThe reproduction of magnetic signatures is an important issue concerning the safety of ship traffic, as well as the identification and classification of vessels. Moreover, military applications of magnetic signatures and their reproduction refer to the activation or protection against activation of magnetic naval mines. Previous works on this subject focused on recording and replicating the signatures under the same conditions...
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Respiration rate estimation using non-linear observers in application to wastewater treatment plant
PublicationA problem of respiration rate estimation using two new non-linear observers for a wastewater treatment plant is addressed in this paper. In particular, a non-linear adaptive Luenberger-like observer and a super twisting sliding mode observer have been derived to produce stable and bounded estimates of the respiration rate. During the synthesis of the particular observer, an appropriate mathematical utility model was used. The observability...
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Stochastic optimisation algorithm for optimisation of controller parameters for control of dissolved oxygen in wastewater treatment plant
PublicationWastewater treatment plants (WWTPs) are very important facilities for mankind. They enable the removal and neutralisation of man-made pollutants. Therefore, it is important for wastewater treatment plants to operate as efficiently as possible so that the level of pollutants in the treated wastewater meets specific requirements. This paper concerns the design of a hierarchical nonlinear adaptive control system for dissolved oxygen...
Year 2022
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Advanced Control With PLC—Code Generator for aMPC Controller Implementation and Cooperation With External Computational Server for Dealing With Multidimensionality, Constraints and LMI Based Robustness
PublicationThe manufacturers of Programmable Logic Controllers (PLC) usually equip their products with extremely simple control algorithms, such as PID and on-off regulators. However, modern PLCs have much more efficient processors and extensive memory, which enables implementing more sophisticated controllers. The paper discusses issues related to the implementation of matrix operations, time limitations for code execution within one PLC...
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An analysis of observability and detectability for different sets of measured outputs - CSTR case study
PublicationA problem of proving the observability/detectability at a given measured output for non-linear biochemical systems has been addressed in this paper. A theory of indistinguishable state trajectories has been used to prove the properties of the observability or detectability of this system. It is related to taking system dynamics into consideration depending on initial conditions and the impact of inputs taking into account a given...
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An analytical four-layer horizontal electric current dipole model for analysing underwater electric potential in shallow seawater
PublicationThe paper presents a new analytical four‑layer (air–water–bottom–non‑conductive layer) horizontal electric dipole model which allows an accurate approximation of ship’s Underwater Electric Potential (UEP) from a sufficient depth in shallow coastal marine waters. The numerical methods, usually Finite Element Method (FEM) or Boundary Elements Method (BEM), are typically used to estimate the electric field and the distribution of...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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An observability and detectability analysis for non-linear uncertain CSTR model of biochemical processes
PublicationThe problem of proving observability/detectability properties for selected non-linear uncertain model of biochemical processes has been addressed in this paper. In particular, the analysis of observability/detectability in the face of parametric and unstructured uncertainty in system dynamics transformed into unknown inputs, and unknown initial conditions has been performed. Various sets of system measured outputs were taken into...
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Comparable analysis of PID controller settings in order to ensure reliable operation of active foil bearings
PublicationIn comparison to the traditional solutions, active bearings offer great operating flexibility, ensure better operating conditions over a wider range of rotational speeds and are safe to use. In order to ensure optimum bearing performance a bearing control system is used that adapts different geometries during device operation. The selection of optimal controller parameters requires the use of modern optimization methods that make...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Design of three control algorithms for an averaging tank with variable filing
PublicationAn averaging tank with variable filling is a nonlinear multidimensional system and can thus be considered a complex control sys-tem. General control objectives of such object include ensuring stability, zero steady state error and achieving simultaneously shortest possible settling time and minimal overshoot. The main purpose of this research work was the modelling and synthesis of three control systems for an averaging tank. In...
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Dynamic Positioning Capability Assessment for Ship Design Purposes
PublicationThe article focuses on solving a problem of optimal thrust distribution over the actuators in a ship Dynamic Positioning, according to DNV-ST-0111 standard, Level 1. The classic Quadratic Programming approach is combined with the numerical solusion used to handle the propeller with the rudder constraints in the optimization task and the influence between thrusters and skeg. It is presented as an efficient method of minimizing the...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Estimation of the angular position of a two-wheeled balancing robot using a real IMU with selected filters
PublicationA low-cost measurement system using filtering of measurements for two-wheeled balancing robot stabilisation purposes has been addressed in this paper. In particular, a measurement system based on gyroscope, accelerometer, and encoder has been considered. The measurements have been corrected for deterministic disturbances and then filtered with Kalman, α-β type, and complementary filters. A quantitative assessment of selected filters...
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublicationIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set
PublicationThis paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their...
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Optimal state feedback controller for balancing cube
PublicationIn this paper, a nonlinear balancing cube system is considered, the concept for which is based on an inverted pendulum. The main purpose of this work was the modelling and construction of a balancing cube with the synthesis of the control system. The control objectives included swing-up and stabilization of the cube on its vertex at an unstable equilibrium. Execution of the intended purpose required, first, deriving a cognitive...
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Optymalizacja procesów biologicznych w oczyszczalni ścieków typu SBR
PublicationObiektem zainteresowania jest biologiczna, sekwencyjna oczyszczalnia ścieków (Sequ-encing Batch Reactor – SBR). Jest to złożony system sterowania z powodu nieliniowej dyna-miki, niepewności, wielu skal czasu, wielowymiarowości i braku wystarczającej liczby pomia-rów. Warunkiem koniecznym zachodzenia większości procesów biologicznych jest dostar-czenie bakteriom oczyszczającym ścieki, odpowiedniej ilości tlenu, za pomocą instalacji...
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Projekt układu sterowania ciągiem wektorowanym rakiety
PublicationArtykuł opisuje problem syntezy układu sterowania ciągiem wektorowanym rakiety w strategii pionowego startu i pionowego lądowania. Celem badań było symulacyjne określenie możliwości wykorzystania regulatora liniowo-kwadratowego w układzie sterowania orientacją rakiety podczas lotu. W pracy oprócz badań symulacyjnych zweryfikowano również algorytm sterowania z wykorzystaniem autorskiego stanowiska z rakietą prototypową wyposażoną...
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Prototype and design of six axis robotic manipulator
PublicationThe paper presents a design of six axis manipulator. The design consists of specially designed solutions for housing, planetary gearboxes and electronics. The manipulator is controlled by a supervisory control system. The use of a series of measuring elements allows to track the current position of each axis and use this to create a cascade control loop with velocity and acceleration feed-forward. The implemented control algorithm...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublicationThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...