Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques

Häftad, Engelska, 2022

Del 1427 i serien Advances in Intelligent Systems and Computing

1 800 kr

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Beskrivning

It contains papers authored by both scientists and practitioners focused on an interdisciplinary approach to developing measuring techniques, robotic and mechatronic systems, industrial automation, numerical modelling and simulation, and application of artificial intelligence techniques required by the transformation leading to Industry 4.0.

Produktinformation

Utgivningsdatum:2022-04-16
Mått:155 x 235 x 23 mm
Vikt:628 g
Format:Häftad
Språk:Engelska
Serie:Advances in Intelligent Systems and Computing
Antal sidor:400
Förlag:Springer International Publishing AG
ISBN:9783031035012

Utforska kategorier

Innehållsförteckning

Invariant Subspaces of Fractional Linear Continuous-Time Systems.- The Initial Problem for a Discrete, Scalar Fractional Order System.- Variability in the Height of Layers for Robotised WAAM Process.- Synthesis of a State Feedback Controller for an Averaging Tank with Variable Filling.- Discrete Time Sliding Mode Control with State Constraints and Limited Control Signal.- PID and FOPID Controllers Combinations During Control of 3D Crane Optimized with GWO Algorithm.- Multi Depot UAVs Routing Subject to Changing Weather and Time Windows Variation.- Early-Stage Faults Detection using Harmony Search Algorithm and STFT-Based Spectral Kurtosis.- Comparison of Nonlinear and Linear Models’ Behaviour Regarding Rocket Stability.- Multithreading Errors in Data Reading Automation.- The Multivariable Control for Dynamic Partially Observable Objects.- The Optimization Model of the Production Process for Corporate Architecture.- Hardware and Software Design of Onboard Computer Controlling the FlightStabilisation System.- Implementation of the Ship's Autopilot in the CPDev Environment.- Research of Attractive Behaviour and Chaos Characteristics of a Control Object at Its Computer Modeling.- Resource Efficiency Forecasting Neural Network Model for the Sugar Plant Diffusion Station.