2,214 research outputs found
Dual Design PID Controller for Robotic Manipulator Application
This research introduces a dual design proportionalâintegralâderivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by ChienâHronesâReswick (CHR)Â technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption
Composite Disturbance Filtering: A Novel State Estimation Scheme for Systems With Multi-Source, Heterogeneous, and Isomeric Disturbances
State estimation has long been a fundamental problem in signal processing and
control areas. The main challenge is to design filters with ability to reject
or attenuate various disturbances. With the arrival of big data era, the
disturbances of complicated systems are physically multi-source, mathematically
heterogenous, affecting the system dynamics via isomeric (additive,
multiplicative and recessive) channels, and deeply coupled with each other. In
traditional filtering schemes, the multi-source heterogenous disturbances are
usually simplified as a lumped one so that the "single" disturbance can be
either rejected or attenuated. Since the pioneering work in 2012, a novel state
estimation methodology called {\it composite disturbance filtering} (CDF) has
been proposed, which deals with the multi-source, heterogenous, and isomeric
disturbances based on their specific characteristics. With the CDF, enhanced
anti-disturbance capability can be achieved via refined quantification,
effective separation, and simultaneous rejection and attenuation of the
disturbances. In this paper, an overview of the CDF scheme is provided, which
includes the basic principle, general design procedure, application scenarios
(e.g. alignment, localization and navigation), and future research directions.
In summary, it is expected that the CDF offers an effective tool for state
estimation, especially in the presence of multi-source heterogeneous
disturbances
Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics
It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM âSchwingungen in rotierenden Maschinenâ. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name âEuropean Conference on Rotordynamicsâ. This new international profile has also been
emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This ďŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ďŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiďŹed Proportional ConďŹict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiďŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiďŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiďŹcation.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiďŹcation, and hybrid techniques mixing deep learning with belief functions as well
SET2022 : 19th International Conference on Sustainable Energy Technologies 16th to 18th August 2022, Turkey : Sustainable Energy Technologies 2022 Conference Proceedings. Volume 4
Papers submitted and presented at SET2022 - the 19th International Conference on Sustainable Energy Technologies in Istanbul, Turkey in August 202
Security and Privacy for Modern Wireless Communication Systems
The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in nodeâedgeâcloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks
Sliding Mode Control and Vision-Based Line Tracking for Quadrotors
This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition.This thesis describes the design of Sliding Mode Control applied to quadrotor UAV flight. This is a nonlinear control technique in which a discontinuous control signal is applied to drive the so-called sliding variable to zero, which defines the sliding surface. The sliding variable should be designed in such a way that approaching the sliding surface is beneficial to tracking the reference signals. The advantages of Sliding Mode Control are that the need for simplifying the underlying dynamical model through linearization is avoided, it is robust and adaptive, and works even if the system to be controlled is highly nonlinear or has model uncertainties. Sliding Mode Control has one major issue associated with it, namely the chattering phenomena in the control inputs, which is undesirable. This can be tackled by approximating the discontinuous sign function in the control input with a approximated continuous function, or by applying techniques such as adaptive fuzzy gain scheduling. As with other control methods, Sliding Mode Control requires tuning of the control parameters to obtain an optimal performance. In this work, genetic algorithms were investigated as a way to tune the controller parameters. The findings of this thesis were combined with the design of a line tracking algorithm in order to enter the MathWorks Minidrone Competition
Automatic Control and Routing of Marine Vessels
Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of shipsâ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels
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