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Tackling Actuator Saturation in Fixed Point Iteration-based Adaptive control 14

Tackling Actuator Saturation in Fixed Point Iteration-based ...

引用

ieee 14th International symposium on Applied computational intelligence and Informatics (SACI)

作者： Issat, Hazem Tar, Jozsef K. Obuda Univ Doctoral Sch Safety & Secur Sci Budapest Hungary Obuda Univ Antal Bejczy Ctr Intelligent Robot ABC iRob Univ Res & Innovat Ctr Budapest Hungary

ISBN: (纸本)9781728173764

The limited output of various drives means a challenge in controller design whenever the acceleration need of the "nominal trajectory to be tracked" temporarily exceeds the abilities of the saturated control system. The prevailing control design methods can tackle this problem either in a single theoretical step or in two consecutive steps. In this latter case in the first step the design happens without taking into account the actuator constraints, then apply a saturation compensator if the phenomenon of windup is observed. In the Fixed Point Iteration-based Adaptive control (FPIAC) that has been developed as an alternative of the Lyapunov function-based approach the actuator saturation causes problems in its both elementary levels: in the kinematic/kinetic level where the desired acceleration is calculated, and in the iterative process that compensates the effects of modeling errors of the dynamic system under control and that of the external disturbances. The here presented approach tackles this problem in both levels by relatively simple considerations. To illustrate the method's efficiency simulation investigations were done in the FPIAC control of a modification of the van der Pol oscillator to which an additional strongly nonlinear term was added.

关键词： Adaptive control Fixed Point Iteration Banach Space Actuator Saturation Anti-windup Van der Pol Oscillator

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The Effects of Adaptive control on Learning Directed Locomotion

The Effects of Adaptive Control on Learning Directed Locomot...

引用

2020 ieee symposium Series on computational intelligence, SSCI 2020

作者： Diggelen, Fuda Van Babuska, Robert Eiben, A.E. Technische Universiteit Delft Netherlands Vrije Universiteit Amsterdam Netherlands

ISBN: (纸本)9781728125473

This study is motivated by evolutionary robot systems where robot bodies and brains evolve simultaneously. In such systems robot 'birth' must be followed by 'infant learning' by a learning method that works for various morphologies evolution may produce. Here we address the task of directed locomotion in modular robots with controllers based on Central Pattern Generators. We present a bio-inspired adaptive feedback mechanism that uses a forward model and an inverse model that can be learned on-the-fly. We compare two versions (a simple and a sophisticated one) of this concept to a traditional (open-loop) controller using Bayesian optimization as a learning algorithm. The experimental results show that the sophisticated version outperforms the simple one and the traditional controller. It leads to a better performance and more robust controllers that better cope with noise. © 2020 ieee.

关键词： controllers

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An Artificial intelligence Algorithm to Automate Situation Management for Operators of Unmanned Aerial Vehicles

An Artificial Intelligence Algorithm to Automate Situation M...

引用

ieee International Conference on Cognitive and computational Aspects of Situation Management (ieee CogSIMA)

作者： Zak, Yuval Parmet, Yisrael Oron-Gilad, Tal Ben Gurion Univ Negev Dept Ind Engn & Management Beer Sheva Israel

ISBN: (纸本)9781728160016

Unmanned Aerial Vehicle (UAV) operators must maintain high levels of situation awareness on their area of operation. To achieve this, they use the a Command and control (C2) map, which is shared among forces, and regularly overloaded with data that is irrelevant to their operational mission. Operators require distilled information at the right timing. Yet, the existing filtering mechanisms for C2 maps are layer-based and insufficient. We propose a new approach to automatically and dynamically filter information items on the map based on environmental and mission context. To achieve this, we introduce a three-tiers artificial intelligence (AI) based algorithm (GiCoMAF), where we delineate the use of machine learning (ML) models to support UAV missions. For the GiCoMAF development, tagged data was collected in simulated experimental runs with professional UAS operators. Different types of ML models were evaluated and fitted into the algorithm. The models achieved a relatively high accuracy at modeling human preference and area of interest. The approach presented in this study can be further implemented to support time-critical spatial-temporal operational problems.

关键词： artificial intelligence human systems integration uninhabited aerial vehicles mental workload situation awareness human-automation interaction intelligent systems decision making information processing

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Fuzzy Asynchronous Fault Tolerant control for Semi-Markov Jump Systems

Fuzzy Asynchronous Fault Tolerant Control for Semi-Markov Ju...

引用

International symposium on computational intelligence and Design, ISCID

作者： Kaixuan Chen Shuping He Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665438575

This work investigates the fault-tolerant control scheme for Takagi-Sugeno fuzzy semi-Markov jump systems with actuator faults. The hidden semi-Markov model is employed to describe the asynchronous phenomenon between the controller and plant. Based on Lyapunov theory, the fault tolerant controller depending on observable mode is presented to make sure that the semi-Markov jump systems is stochastically stable and satisfies the $H_{\infty}$ performance. A simulation example via a single-link robot is employed to prove the correctness of the studied approach.

关键词： Actuators Sufficient conditions computational modeling Fault tolerant systems Fault tolerant control Manipulators Takagi-Sugeno model

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Authentication Based on Touch Patterns Using an Artificial Immune System

Authentication Based on Touch Patterns Using an Artificial I...

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ieee symposium Series on computational intelligence (SSCI)

作者： Nawaf Aljohani Joseph Shelton Kaushik Roy Makkah Al-Mukaramah Region Branch Institute of Public Administration Saudi Arabia Virginia State University Petersburg USA North Carolina Agricultural and Technical State University Greensboro USA

ISBN: (纸本)9781728190495

Mobile users typically provide their credentials once for authentication purposes. However, as long as the user remains active in the system, there are no mechanisms to verify whether the user who provides the credential is still in control of the device. In mobile device systems, the user's identity is checked only in the login stage. Continuous authentication based on the user's touch behavior patterns could be a remarkable solution to verify without disruption that a legitimate user is still in control of a mobile device. In this research, an Artificial Immune System (AIS) is proposed to continuously authenticate the users in the background based on the user's touch gestures. Experiments with Clonal Selection (CS) and Negative Selection (NS) are conducted on three datasets. Our results show that the best AIS performance is able to authenticate 99.89% of the users correctly.

关键词： Performance evaluation Artificial immune systems Authentication Mobile handsets Artificial intelligence computational intelligence

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Action Detection Based on 3D Convolution Neural Network with Channel Attention Mechanism

Action Detection Based on 3D Convolution Neural Network with...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Gao, Yan Liang, Huilai Liu, Baodi Wang, Yanjiang China Univ Petr East China Coll Control Sci & Engn Qingdao Peoples R China

ISBN: (纸本)9781728125473

In this paper, we propose an action detection model. a simple yet effective combination of channel attention mechanism with 3D convolution neural network, by which to enhance the performance of feature extraction in the video. Channel attention module uses the channel information in the feature extraction process of our 3D convolutional network to efficaciously pick out the features that are essential for the task and suppress useless ones. The proposed model can effectively promote the spatio-temporal feature representation power in the video. We embed our feature extraction model into the R-C3D framework to test the performance of our method by conducting comparative experiments on the THUMOS'14 dataset. Experimental results indicate that the proposed method can authentically enhance the accuracy of action detection.

关键词： action detection channel attention 3D convolutional neural networks R-C3D

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Development of an LQ regulator for longitudinal vehcile control of an automated vehicle 19

Development of an LQ regulator for longitudinal vehcile cont...

引用

ieee Joint 19th International symposium on computational intelligence and Informatics / 7th International Conference on Recent Achievements in Mechatronics, automation, Computer Sciences and Robotics

作者： Ratkovics, Andras Vass, Sandor Tihanyi, Viktor Budapest Univ Tehncol & Econ Dept Automot Technol Budapest Hungary

ISBN: (纸本)9781728156255

Nowadays in road transport lower fuel consumption, higher traffic safety and reduced environmental impact are in the focus of the developments. To reach these future objectives it is necessary to increase the level of automation of road vehicles. Driving a road vehicle by a software is a complex controlling task. This paper presents a basic longitudinal motion controller, which uses a Linear-Quadratic (LQ) regulator. This controller is widespread in the controlling of MIMO systems, because it provides an interactive control, optimized for certain elements of the state vector. The aim of this work is to create an operative longitudinal vehicle control based on an LQ regulator and use it in a demonstration vehicle.

关键词： longitudinal control vehicle control LQ regulator pedal position control

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2020 ieee symposium Series on computational intelligence, SSCI 2020

2020 IEEE Symposium Series on Computational Intelligence, SS...

引用

2020 ieee symposium Series on computational intelligence, SSCI 2020

ISBN: (纸本)9781728125473

The proceedings contain 419 papers. The topics discussed include: AiCE: automating horizon scanning for the detection of emerging technologies;DeepHealth: deep representation learning with autoencoders for healthcare prediction;simp3: social interaction-based multi-pedestrian path prediction by self-driving cars;exploring reward-based hyper-heuristics for the job-shop scheduling problem;data-driven neuro ARCH (DDNA) volatility model for option pricing on cloud resources;combined selection and parameter control of meta-heuristics;scale-invariance ideas explain the empirical soil-water characteristic curve;entropy-based recognition of anomalous answers for efficient grading of short answers with an evolutionary clustering algorithm;short-term trajectory planning in TORCS using deep reinforcement learning;and analyzing of LAM-CIoT: lightweight authentication mechanism in cloud-based IoT environment.

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Adaptive Backstepping Neural Tracking control of an Uncertain Robot Manipulator with Dynamic Disturbances

Adaptive Backstepping Neural Tracking Control of an Uncertai...

引用

2020 ieee symposium Series on computational intelligence, SSCI 2020

作者： Prakash, Ravi Gupta, Kurusetti Vinay Behera, Laxmidhar Indian Institute of Technology Kanpur Department of Electrical Engineering India

ISBN: (纸本)9781728125473

The varying system parameters, end effector payload and environmental uncertainties are quite natural in real-world robotics applications. Therefore in order to adapt to the changing control environment and improving robustness of the controller due to an uncertain system model and dynamic uncertainties adaptive control methods are developed. This paper presents an adaptive neural backstepping control for an uncertain robot manipulator with dynamic disturbances. The dynamics of an n-link uncertain robot manipulator with dynamic disturbances is expressed as a class of 3nth order nonlinear multi-input multioutput (MIMO) system using a nonlinear disturbance observer-based model. The uncertain plant and disturbances dynamics are approximated using Radial Basis Function Network (RBFN) to derive the control law. The proposed controller for each link has a simple structure with a single unknown parameter. The update law for this unknown parameter has been obtained using Lyapunov stability. It is shown that the proposed controller is able to ensure the semi-global uniformly ultimately boundedness (UUB) of all signals of the resulting closed-loop system and the actual response eventually reaches a bounded neighbourhood of the desired response. Simulation results demonstrate the feasibility of the proposed technique. The tracking performance of the proposed controller is validated experimentally on a four degrees-of-freedom (4 DOF) Barrett Whole Arm Manipulator while performing dynamic ball hitting experiments. © 2020 ieee.

关键词： controllers

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SfmCAD: Unsupervised CAD Reconstruction by Learning Sketch-based Feature Modeling Operations

SfmCAD: Unsupervised CAD Reconstruction by Learning Sketch-b...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Pu Li Jianwei Guo Huibin Li Bedrich Benes Dong-Ming Yan MAIS Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Computer Science Purdue University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

This paper introduces SfmCAD, a novel unsupervised network that reconstructs 3D shapes by learning the Sketchbased Feature Modeling operations commonly used in modern CAD workflows. Given a 3D shape represented as voxels, SfmCAD learns a neural-typed sketch+path parameterized representation, including 2D sketches of feature primitives and their 3D sweeping paths without supervision, for inferring feature-based CAD programs. SfmCAD employs 2D sketches for local detail representation and 3D paths to capture the overall structure, achieving a clear separation between shape details and structure. This conversion into parametric forms enables users to seamlessly adjust the shape's geometric and structural features, thus enhancing interpretability and user control. We demonstrate the effectiveness of our method by applying SfmCAD to many different types of objects, such as CAD parts, ShapeNet objects, and tree shapes. Extensive comparisons show that SfmCAD produces compact and faithful 3D reconstructions with superior quality compared to alternatives. The code is released at https://***/BunnySoCrazy/SfmCAD.

关键词： Solid modeling Computer vision Three-dimensional displays Codes Shape computational modeling Pattern recognition

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