An Efficient Computational Algorithm of Adaptive Control for Closed-Loop Robots and Experiments

1998 ◽  
Vol 10 (2) ◽  
pp. 147-153
Author(s):  
Yasuhito Oooka ◽  
◽  
Haruhisa Kawasaki ◽  
Nobuhito Takemura
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Computational Algorithm ◽  
Trajectory Control ◽  
Experimental Results ◽  
Serial Link ◽  
Model Based ◽  
Link Mechanism ◽  
Parallel Link

This paper presents an efficient computational algorithm of model-based adaptive control for closed-loop robots. The algorithm is an extension of the computational algorithm for serial-link robots, which was derived by Kawasaki and Bito. The proposed algorithm is implemented to a 6 DOF robot with a parallel-link mechanism using a 32-bit DSP. Experimental results of trajectory control are also shown.

Mechanism and Control of Parallel-Wire Driven System

2015 ◽  
Vol 27 (6) ◽  
pp. 599-607 ◽  
Author(s):  
Hitoshi Kino ◽  
◽  
Sadao Kawamura ◽  
Keyword(s):  
Robot Manipulators ◽  
Parallel Mechanisms ◽  
Serial Link ◽  
Parallel Wire ◽  
Link Mechanism ◽  
Human Arm ◽  
Driven System ◽  
Parallel Link ◽  
And Control ◽  
Controlled Object

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/01.jpg"" width=""300"" /> A parallel-wire driven system</div>Many of the conventional robot manipulators have a serial-link mechanism to imitate a human arm. In recent years, however, industries have been aggressive in putting parallel-link mechanisms into practical use to cope with various problems that no conventional serial-link mechanisms have ever been able to solve. Under the circumstances, this paper describes a parallel-wire driven system, one of the parallel mechanisms. It is a system to drive a controlled object with flexible and light wires instead of rigid links. It has many advantages over conventional serial-link mechanisms or other ordinary parallel-link mechanisms. This paper first overviews previous studies on parallel-wire driven robots, and then details the mechanism and control of these systems, as well as examples of their application.

scholarly journals Generalized analytical model based on harmonic coupling for hybrid plasmonic modes: comparison with numerical and experimental results

2015 ◽  
Vol 23 (21) ◽  
pp. 27376 ◽  
Author(s):  
Mitradeep Sarkar ◽  
Jean-François Bryche ◽  
Julien Moreau ◽  
Mondher Besbes ◽  
Grégory Barbillon ◽  
...  
Keyword(s):  
Analytical Model ◽  
Experimental Results ◽  
Model Based

scholarly journals A New No Equilibrium Fractional Order Chaotic System, Dynamical Investigation, Synchronization, and Its Digital Implementation

Inventions ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 49
Author(s):  
Zain-Aldeen S. A. Rahman ◽  
Basil H. Jasim ◽  
Yasir I. A. Al-Yasir ◽  
Raed A. Abd-Alhameed ◽  
Bilal Naji Alhasnawi
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Chaotic System ◽  
Real World ◽  
Experimental Results ◽  
Chaotic Attractors ◽  
State Variables ◽  
Digital Implementation ◽  
Dynamical Behaviors ◽  
Real World Applications

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.

scholarly journals Research of Personalized Recommendation Technology Based on Knowledge Graphs

2021 ◽  
Vol 11 (15) ◽  
pp. 7104
Author(s):  
Xu Yang ◽  
Ziyi Huan ◽  
Yisong Zhai ◽  
Ting Lin
Keyword(s):  
Neural Network ◽  
Hot Spot ◽  
Experimental Results ◽  
Graph Representation ◽  
Personalized Recommendation ◽  
Knowledge Graph ◽  
Learning Technology ◽  
Data Set ◽  
Model Based ◽  
Knowledge Graphs

Nowadays, personalized recommendation based on knowledge graphs has become a hot spot for researchers due to its good recommendation effect. In this paper, we researched personalized recommendation based on knowledge graphs. First of all, we study the knowledge graphs’ construction method and complete the construction of the movie knowledge graphs. Furthermore, we use Neo4j graph database to store the movie data and vividly display it. Then, the classical translation model TransE algorithm in knowledge graph representation learning technology is studied in this paper, and we improved the algorithm through a cross-training method by using the information of the neighboring feature structures of the entities in the knowledge graph. Furthermore, the negative sampling process of TransE algorithm is improved. The experimental results show that the improved TransE model can more accurately vectorize entities and relations. Finally, this paper constructs a recommendation model by combining knowledge graphs with ranking learning and neural network. We propose the Bayesian personalized recommendation model based on knowledge graphs (KG-BPR) and the neural network recommendation model based on knowledge graphs(KG-NN). The semantic information of entities and relations in knowledge graphs is embedded into vector space by using improved TransE method, and we compare the results. The item entity vectors containing external knowledge information are integrated into the BPR model and neural network, respectively, which make up for the lack of knowledge information of the item itself. Finally, the experimental analysis is carried out on MovieLens-1M data set. The experimental results show that the two recommendation models proposed in this paper can effectively improve the accuracy, recall, F1 value and MAP value of recommendation.

Logic-Based Switching Adaptive Control of DC-DC Buck Converter

2012 ◽  
Vol 229-231 ◽  
pp. 2209-2212
Author(s):  
Bao Bin Liu ◽  
Wei Zhou
Keyword(s):  
Adaptive Control ◽  
Closed Loop ◽  
Buck Converter ◽  
Uncertain Parameters ◽  
Small Signal ◽  
Closed Loop System ◽  
Unknown Parameters ◽  
Signal Model ◽  
Small Signal Model ◽  
Control Scheme

Logic-based switching adaptive control scheme is proposed for the model of DC-DC buck converter in presence of uncertain parameters and power supply disturbance. All uncertain parameters and the disturbance are estimated together through constructing Lyapunov function. And a switching mechanism is used to ensure global asymptotic stability of the closed-loop system. The results of simulation show that even if there are multiple unknown parameters in the small-signal model, the control system of DC-DC buck converter can estimate unknown parameters quickly and accurately.

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