scholarly journals Intelligent control of mobile robot with redundant manipulator & stereovision: quantum / soft computing toolkit

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Kirill V Koshelev ◽  
Alena V Nikolaeva ◽  
Andrey G Reshetnikov ◽  
Sergey Victorovich Ulyanov
Keyword(s):  
Quantum Computing ◽  
Mobile Robot ◽  
Knowledge Base ◽  
Soft Computing ◽  
Intelligent Control ◽  
Computational Intelligence ◽  
Control Object ◽  
Knowledge Bases ◽  
Self Organization ◽  
Redundant Manipulator

The task of an intelligent control system design applying soft and quantum computational intelligence technologies discussed. An example of a control object as a mobile robot with redundant robotic manipulator and stereovision introduced. Design of robust knowledge bases is performed using a developed computational intelligence – quantum / soft computing toolkit (QC/SCOptKBTM). The knowledge base self-organization process of fuzzy homogeneous regulators through the application of end-to-end IT of quantum computing described. The coordination control between the mobile robot and redundant manipulator with stereovision based on soft computing described. The general design methodology of a generalizing control unit based on the physical laws of quantum computing (quantum information-thermodynamic trade-off of control quality distribution and knowledge base self-organization goal) is considered. The modernization of the pattern recognition system based on stereo vision technology presented. The effectiveness of the proposed methodology is demonstrated in comparison with the structures of control systems based on soft computing for unforeseen control situations with sensor system.

scholarly journals Quantum Algorithm of Imperfect KB Self-organization. Pt II: Robotic Control with Remote Knowledge Base Exchange

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
A.G. Reshetnikov ◽  
S.V. Ulyanov
Keyword(s):  
Quantum Computing ◽  
Knowledge Base ◽  
Cooling System ◽  
Information Source ◽  
Synergetic Effect ◽  
Control Object ◽  
Knowledge Bases ◽  
Mobile Manipulator ◽  
Base Exchange ◽  
Fuzzy Controllers

The technology of knowledge base remote design of the smart fuzzy controllers with the application of the "Soft / quantum computing optimizer" toolkit software developed. The possibility of the transmission and communication the knowledge base using remote connection to the control object considered. Transmission and communication of the fuzzy controller’s knowledge bases implemented through the remote connection with the control object in the online mode apply the Bluetooth or WiFi technologies. Remote transmission of knowledge bases allows designing many different built-in intelligent controllers to implement a variety of control strategies under conditions of uncertainty and risk. As examples, two different models of robots described (mobile manipulator and (“cart-pole” system) inverted pendulum). A comparison of the control quality between fuzzy controllers and quantum fuzzy controller in various control modes is presented. The ability to connect and work with a physical model of control object without using than mathematical model demonstrated. The implemented technology of knowledge base design sharing in a swarm of intelligent robots with quantum controllers. It allows to achieve the goal of control and to gain additional knowledge by creating a new quantum hidden information source based on the synergetic effect of combining knowledge. Development and implementation of intelligent robust controller’s prototype for the intelligent quantum control system of mega-science project NICA (at the first stage for the cooling system of superconducted magnets) is discussed. The results of the experiments demonstrate the possibility of the ensured achievement of the control goal of a group of robots using soft / quantum computing technologies in the design of knowledge bases of smart fuzzy controllers in quantum intelligent control systems. The developed software toolkit allows to design and setup complex ill-defined and weakly formalized technical systems on line.

scholarly journals Intelligent robust control of redun-dant smart robotic arm Pt II: Quantum computing KB optimizer

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Sergey Victorovich Ulyanov
Keyword(s):  
Quantum Computing ◽  
Control Systems ◽  
Intelligent Control ◽  
Fuzzy Inference ◽  
Knowledge Bases ◽  
Cognitive Robotics ◽  
Self Organization ◽  
Classical Dynamic ◽  
Intelligent Control Systems ◽  
Quantum Programming

In the first part of the article, two ways of fuzzy controller’s implementation showed. First way applied one controller for all links of the manipulator and showed the best performance. However, such an implementation is not possible in complex control objects, such as a planar redundant manipulator with seven degrees of freedom (DoF). The second way use of separated control when an independent fuzzy controller controls each link. The decomposition control due to a slight decrease in the quality of management has greatly simplified the processes of creating and placing knowledge bases. In this paper (Part II), the advantages and limitations of intelligent control systems based on soft computing technology described. To eliminate the mismatch of the work of separate independent fuzzy controllers, methods for self-organizing coordination control based on quantum computing technologies to create and design robust intelligent control systems for robotic manipulators with 3DOF and 7DOF described. Quantum fuzzy inference as quantum self-organization algorithm of imperfect KBs introduced. Quantum computational intelligence smart toolkit QCOptKBTMbased on quantum fuzzy inference applied. QCOptKBTM toolkit include quantum deep machine learning in on line. Successful engineering application of end-to-end quantum computing information technologies (as quantum sophisticated algorithms and quantum programming) in searching of solutions of algorithmic unsolved problems in classical dynamic intelligent control systems, artificial intelligence (AI) and intelligent cognitive robotics discussed. Quantum computing supremacy in efficient solution of intractable classical tasks as global robustness of redundant robotic manipulator in unpredicted control situations demonstrated. As result, the new synergetic self-organization information effect of robust KB design from responses of imperfect KBs (partial KB robustness cretead on toolkit SCOptKBTM in Pat I) fined.

Soft computing algorithms for intelligent control of a mobile robot for service use

1997 ◽  
Vol 1 (2) ◽  
pp. 99-106 ◽  
Author(s):  
T. Tanaka ◽  
J. Ohwi ◽  
L. V. Litvintseva ◽  
K. Yamafuji ◽  
S. V. Ulyanov
Keyword(s):  
Mobile Robot ◽  
Soft Computing ◽  
Intelligent Control ◽  
Service Use

scholarly journals Robust PID Controller Design on Quantum Fuzzy Inference: Imperfect KB Quantum Self-Organization Effect-Quantum Supremacy Effect

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
L V Litvintseva ◽  
S V Ulyanov ◽  
Sergey Victorovich Ulyanov
Keyword(s):  
System Theory ◽  
Intelligent Control ◽  
Computational Intelligence ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Controller Design ◽  
Self Organization ◽  
Computing Technology ◽  
Quantum Approach ◽  
Pid Controller Design

Quantum PID controller design based on quantum fuzzy inference from two K-gains ( and ) of classical PID (with constant K-gains) controllers investigated. Computational intelligence toolkit as soft computing technology in learning situations applied. Quantum approach performance in design of robust conventional controllers as intractable classical task of control system theory demonstrated. Simulation of intelligent control Benchmark demonstrated.

scholarly journals Intelligent robust control of redundant smart robotic arm Pt I: Soft computing KB optimizer - deep machine learning IT

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Alena V Nikolaeva ◽  
Sergey Victorovich Ulyanov
Keyword(s):  
Machine Learning ◽  
Control System ◽  
Robust Control ◽  
Control Systems ◽  
Soft Computing ◽  
Intelligent Control ◽  
Control Object ◽  
Robotic Arm ◽  
Control Laws ◽  
Intelligent Control Systems

Redundant robotic arm models as a control object discussed. Background of computational intelligence IT based on soft computing optimizer of knowledge base in smart robotic manipulators introduced. Soft computing optimizer is the toolkit of deep machine learning SW platform with optimal fuzzy neural network structure. The methods for development and design technology of intelligent control systems based on the soft computing optimizer presented in this Part 1 allow one to implement the principle of design an optimal intelligent control systems with a maximum reliability and controllability level of a complex control object under conditions of uncertainty in the source data, and in the presence of stochastic noises of various physical and statistical characters. The knowledge bases formed with the application of a soft computing optimizer produce robust control laws for the schedule of time dependent coefficient gains of conventional PID controllers for a wide range of external perturbations and are maximally insensitive to random variations of the structure of control object. The robustness of control laws is achieved by application a vector fitness function for genetic algorithm, whose one component describes the physical principle of minimum production of generalized entropy both in the control object and the control system, and the other components describe conventional control objective functionals such as minimum control error, etc. The application of soft computing technologies (Part I) for the development a robust intelligent control system that solving the problem of precision positioning redundant (3DOF and 7 DOF) manipulators considered. Application of quantum soft computing in robust intelligent control of smart manipulators in Part II described.

Soft computing algorithms for intelligent control of a mobile robot for service use

1997 ◽  
Vol 1 (2) ◽  
pp. 88-98 ◽  
Author(s):  
T. Tanaka ◽  
J. Ohwi ◽  
L. V. Litvintseva ◽  
K. Yamafuji ◽  
S. V. Ulyanov
Keyword(s):  
Mobile Robot ◽  
Soft Computing ◽  
Intelligent Control ◽  
Service Use

scholarly journals Intelligent robust control system of robotic unicycle based on the end-to-end soft computing technology

2019 ◽  
pp. 58-86
Author(s):  
Sergey Ulyanov ◽  
Viktor Ulyanov ◽  
Andrey Reshetnikov ◽  
Olga Tyatyushkina ◽  
Kazuo Yamafuji
Keyword(s):  
Control System ◽  
Robust Control ◽  
Entropy Production ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fitness Function ◽  
Control Object ◽  
Minimum Entropy ◽  
Intelligent Control System ◽  
Production Calculation

The concept of an intelligent control system for a complex nonlinear biomechanical system of an extension cableless robotic unicycle is considered. A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems is used. The results of stochastic simulation of a fuzzy intelligent control system for various types of external/ internal excitations for a dynamic, globally unstable control object -extension cableless robotic unicycle based on Soft Computing (Computational Intelligence Toolkit) technology are presented. A new approach to design an intelligent control system based on the principle of the minimum entropy production (minimum of useful resource losses) determination in the movement of the control object and the control system is developed. This determination as a fitness function in the genetic algorithm is used to achieve robust control of a robotic unicycle. An algorithm for entropy production calculation and representation of their relationship with the Lyapunov function (a measure of stochastic robust stability) is described.

scholarly journals Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Sergey Victorovich Ulyanov ◽  
Ulyanov Viktor ◽  
Yamafuji Kazuo
Keyword(s):  
Control System ◽  
Robust Control ◽  
Entropy Production ◽  
Intelligent Control ◽  
Computational Intelligence ◽  
Fitness Function ◽  
Control Object ◽  
Minimum Entropy ◽  
Intelligent Control System ◽  
Minimum Entropy Production

The concept of an intelligent control system for a complex nonlinear biomechanical system of an extension cableless robotic unicycle discussed. A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems applied. The results of stochastic simulation of a fuzzy intelligent control system for various types of external / internal excitations for a dynamic, globally unstable control object - extension cableless robotic unicycle based on Soft Computing (Computational Intelligence Toolkit - SCOptKBTM) technology presented. A new approach to design an intelligent control system based on the principle of the minimum entropy production (minimum of useful resource losses) determination in the movement of the control object and the control system is developed. This determination as a fitness function in the genetic algorithm is used to achieve robust control of a robotic unicycle. An algorithm for entropy production computing and representation of their relationship with the Lyapunov function (a measure of stochastic robust stability) described.

Sign in / Sign up

Export Citation Format

Share Document