A Path-Planning Strategy for Overhead Cranes With High Hoisting Speed

2002 ◽  
Author(s):  
Ho-Hoon Lee
Keyword(s):  
Path Planning ◽  
High Performance ◽  
Stability Theorem ◽  
Lyapunov Stability Theorem ◽  
Control Laws ◽  
Planning Strategy ◽  
Overhead Cranes ◽  
Time Control ◽  
Small Load ◽  
Load Swing

This paper proposes a path planning strategy for high-performance anti-swing control of overhead cranes, where the anti-swing control problem is solved as a kinematic problem. First, two anti-swing control laws, one for hoisting up and the other for hoisting down, are proposed based on the Lyapunov stability theorem. Then a new path-planning strategy is proposed based on the concept of minimum-time control and the proposed anti-swing control laws. The proposed path planning is free from the usual constraints of small load swing, slow hoisting speed, and small hoisting distance. The effectiveness of the proposed path planning is shown by computer simulation with high hoisting speed and hoisting ratio.

A New Trajectory-Generation Scheme for Overhead Cranes With High-Speed Load Hoisting

2004 ◽  
Author(s):  
Ho-Hoon Lee ◽  
Del Segura ◽  
Yi Liang
Keyword(s):  
High Speed ◽  
High Performance ◽  
Trajectory Generation ◽  
Control Law ◽  
Mathematical Tool ◽  
Lyapunov Stability Theorem ◽  
Overhead Cranes ◽  
Time Control ◽  
Load Swing ◽  
Generation Problem

This paper proposes a new trajectory-generation scheme for a high-performance anti-swing control of overhead cranes, where the trajectory-generation problem is solved as a kinematic problem. First, a new anti-swing control law is designed based on the load-swing dynamics, for which the Lyapunov stability theorem is used as a mathematical tool. Then a new trajectory-generation scheme is proposed based on the anti-swing control law and typical crane operation in practice. For g iven hoisting motions, trolley-traveling trajectory references are computed based on the concept of minimum-time control, and then anti-swing trajectories are generated based on the trajectory references through the anti-swing control law. The new trajectory-generation scheme generates a typical anti-swing trajectory in industry with high-speed load hoisting. The effectiveness of the proposed trajectory-generation scheme is shown by generating high-performance anti-swing trajectories with high hoisting speed and hoisting ratio.

A New Motion-Planning Scheme for Overhead Cranes With High-Speed Hoisting

2004 ◽  
Vol 126 (2) ◽  
pp. 359-364 ◽  
Author(s):  
Ho-Hoon Lee
Keyword(s):  
Motion Planning ◽  
High Speed ◽  
High Performance ◽  
Control Law ◽  
Planning Problem ◽  
Lyapunov Stability Theorem ◽  
Overhead Cranes ◽  
Swing Angle ◽  
Planning Scheme ◽  
Load Swing

This paper proposes a motion-planning method for a high-performance anti-swing control of overhead cranes, where the motion-planning problem is solved as a kinematic problem. First, an anti-swing regulating control law is proposed based on the Lyapunov stability theorem, where the proposed anti-swing control drives trolley velocity regulating error asymptotically to zero while suppressing load swing rapidly to zero for given arbitrary high-speed hoisting motions. Then a motion-planning scheme is designed based on the concept of minimumtime control, the proposed anti-swing control law, and typical anti-swing crane-operation practices. The motion-planning scheme is free from the usual mathematical constraints in anti-swing control such as small swing angle, small hoisting speed, and small hoisting distance. The effectiveness of the proposed motion planning is shown by generating high-performance anti-swing trajectories with high hoisting speed and hoisting ratio.

scholarly journals Chaotic Path Planning for 3D Area Coverage Using a Pseudo-Random Bit Generator from a 1D Chaotic Map

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1821
Author(s):  
Lazaros Moysis ◽  
Karthikeyan Rajagopal ◽  
Aleksandra V. Tutueva ◽  
Christos Volos ◽  
Beteley Teka ◽  
...  
Keyword(s):  
Path Planning ◽  
Chaotic Map ◽  
Dynamical Behavior ◽  
Area Coverage ◽  
Phase Portraits ◽  
Planning Strategy ◽  
Spline Curves ◽  
Key Space ◽  
Aerial Vehicle ◽  
Discrete Motion

This work proposes a one-dimensional chaotic map with a simple structure and three parameters. The phase portraits, bifurcation diagrams, and Lyapunov exponent diagrams are first plotted to study the dynamical behavior of the map. It is seen that the map exhibits areas of constant chaos with respect to all parameters. This map is then applied to the problem of pseudo-random bit generation using a simple technique to generate four bits per iteration. It is shown that the algorithm passes all statistical NIST and ENT tests, as well as shows low correlation and an acceptable key space. The generated bitstream is applied to the problem of chaotic path planning, for an autonomous robot or generally an unmanned aerial vehicle (UAV) exploring a given 3D area. The aim is to ensure efficient area coverage, while also maintaining an unpredictable motion. Numerical simulations were performed to evaluate the performance of the path planning strategy, and it is shown that the coverage percentage converges exponentially to 100% as the number of iterations increases. The discrete motion is also adapted to a smooth one through the use of B-Spline curves.

Model-Independent Control of a Flexible-Joint Robot Manipulator

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
Withit Chatlatanagulchai ◽  
Peter H. Meckl
Keyword(s):  
Neural Networks ◽  
Open Problem ◽  
High Performance ◽  
Robot Manipulator ◽  
Intrinsic Property ◽  
Variable Structure ◽  
System Model ◽  
Control Input ◽  
Control Laws ◽  
Flexible Joint

Flexibility at the joint of a manipulator is an intrinsic property. Even “rigid-joint” robots, in fact, possess a certain amount of flexibility. Previous experiments confirmed that joint flexibility should be explicitly included in the model when designing a high-performance controller for a manipulator because the flexibility, if not dealt with, can excite system natural frequencies and cause severe damage. However, control design for a flexible-joint robot manipulator is still an open problem. Besides being described by a complicated system model for which the passivity property does not hold, the manipulator is also underactuated, that is, the control input does not drive the link directly, but through the flexible dynamics. Our work offers another possible solution to this open problem. We use three-layer neural networks to represent the system model. Their weights are adapted in real time and from scratch, which means we do not need the mathematical model of the robot in our control algorithm. All uncertainties are handled by variable-structure control. Backstepping structure allows input efforts to be applied to each subsystem where they are needed. Control laws to adjust all adjustable parameters are devised using Lyapunov’s second method to ensure that error trajectories are globally uniformly ultimately bounded. We present two state-feedback schemes: first, when neural networks are used to represent the unknown plant, and second, when neural networks are used to represent the unknown parts of the control laws. In the former case, we also design an observer to enable us to design a control law using only output signals—the link positions. We use simulations to compare our algorithms with some other well-known techniques. We use experiments to demonstrate the practicality of our algorithms.

Wavelet Transform Based Feature Extraction for EEG Signal Classification

2021 ◽  
Vol 20 ◽  
pp. 199-206
Author(s):  
Seda Postalcioglu
Keyword(s):  
Wavelet Transform ◽  
High Performance ◽  
Feature Vector ◽  
Fast Response ◽  
Eeg Signal ◽  
Real Time Control ◽  
Time Control ◽  
Band Power ◽  
Performance Rate

This study focused on the classification of EEG signal. The study aims to make a classification with fast response and high-performance rate. Thus, it could be possible for real-time control applications as Brain-Computer Interface (BCI) systems. The feature vector is created by Wavelet transform and statistical calculations. It is trained and tested with a neural network. The db4 wavelet is used in the study. Pwelch, skewness, kurtosis, band power, median, standard deviation, min, max, energy, entropy are used to make the wavelet coefficients meaningful. The performance is achieved as 99.414% with the running time of 0.0209 seconds

Efficient CNC Tool Path Planning Using Point Cloud

2018 ◽  
Author(s):  
Sumedh Ghogare ◽  
S. S. Pande
Keyword(s):  
Path Planning ◽  
Point Cloud ◽  
Tool Path ◽  
Planning Process ◽  
Cnc Milling ◽  
Tool Path Planning ◽  
Planning Strategy ◽  
Part Quality ◽  
Nc Program ◽  
Cutter Path

This paper reports the development of an efficient iso-scallop tool path planning strategy for machining of freeform surfaces on a three axis CNC milling center using the point cloud as the input. Boundary of the point cloud is chosen as the Master Cutter Path, using which the scallop points are computed. Adjacent side tool paths are computed using these scallop points and the path planning process is completed till the entire surface is covered. The system generates post-processed NC program in ISO format which was extensively tested for various case studies. The results were compared with the iso-planar tool path strategy from commercial software. Our system was found to generate efficient tool path in terms of part quality, productivity and storage memory.

scholarly journals Smooth Autonomous Navigation Considering Avoidance Behavior Characteristics of Pedestrians

2022 ◽  
Author(s):  
Ryunosuke Harada ◽  
Hiroshi Yoshitake ◽  
Motoki Shino
Keyword(s):  
Angular Velocity ◽  
Path Planning ◽  
Avoidance Behavior ◽  
Autonomous Navigation ◽  
Personal Mobility ◽  
Planning Strategy ◽  
Short Period ◽  
Behavior Characteristics

Abstract To ensure the coexistence of autonomous personal mobility vehicles (PMVs) and pedestrians in a pedestrian zone, they should be able to smoothly pass across and avoid each other. Studies suggest that it is possible that PMVs and pedestrians can pass each other in a short period of time without compromising their comfort; this can be achieved through understanding how pedestrians react to the behavior of PMVs and by modifying the autonomous navigation of PMVs accordingly. Therefore, in this study, the avoidance behavior characteristics of pedestrians were investigated. Experiments were conducted to understand the influence of the selected avoiding behavior parameters and to understand the behavior characteristics of pedestrians in relation to the behavior of PMVs. Furthermore, a path planning strategy that enables smooth passing was developed based on these characteristics. The usefulness of this method was evaluated. The avoidance time and the avoiding angular velocity at the start and end of the avoidance behavior were the parameters that contributed to smooth autonomous navigation. The results show that pedestrian tolerance improves and the avoidance width decreases depending on these parameters. Furthermore, smooth autonomous navigation can be achieved using the characteristics of pedestrians’ cognition against PMVs.

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