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Robotic Smart Prosthesis Arm with BCI and Kansei/Kawaii/Affective Engineering Approach.Pt I: Quantum Soft Computing Supremacy
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作者 Alexey V.Nemchaninov Alena V.Nikolaeva +1 位作者 Sergey V.Ulyanov Andrey G.Reshetnikov 《Artificial Intelligence Advances》 2020年第2期68-87,共20页
A description of the design stage and results of the development of the conceptual structure of a robotic prosthesis arm is given.As a result,a prototype of man-made smart prosthesis on a 3D printer as well as a found... A description of the design stage and results of the development of the conceptual structure of a robotic prosthesis arm is given.As a result,a prototype of man-made smart prosthesis on a 3D printer as well as a foundation for computational intelligence presented.The application of soft computing technology(the first step of IT)allows to extract knowledge directly from the physical signal of the electroencephalogram,as well as to form knowledge-based intelligent robust control of the lower performing level taking into account the assessment of the patient’s emotional state.The possibilities of applying quantum soft computing technologies(the second step of IT)in the processes of robust filtering of electroencephalogram signals for the formation of mental commands of robotic prosthetic arm discussed.Quantum supremacy benchmark of intelligent control simulation demonstrated. 展开更多
关键词 Robotic prosthetic arm Cognitive computational intelligence Brain-computer-device neurointerface Mental commands Quantum soft computing Fuzzy cognitive controller Quantum supremacy benchmark
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Intelligent Control of Mobile Robot with Redundant Manipulator & Stereovision: Quantum / Soft Computing Toolkit
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作者 Kirill V.Koshelev Alena V.Nikolaeva +1 位作者 Andrey G.Reshetnikov Sergey V.Ulyanov 《Artificial Intelligence Advances》 2020年第2期1-31,共31页
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 ster... 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.The main objective of this article is to demonstrate the advantages of the approach based on quantum/soft computing. 展开更多
关键词 Quantum/Soft computing optimizer Knowledge base Fuzzy controller Quantum fuzzy inference Multi-agent systems Mobile robot stereo vision
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Intelligent Robust Control of Redundant Smart Robotic Arm Pt II: Quantum Computing KB Optimizer Supremacy
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作者 Alena V.Nikolaeva Sergey V.Ulyanov 《Artificial Intelligence Advances》 2020年第2期32-67,共36页
This article is a continuation of the work“Intelligent robust control of redundant smart robotic arm Pt I:Soft computing KB optimizer-deep machine learning IT”.In the first part of the paper,we examined control syst... This article is a continuation of the work“Intelligent robust control of redundant smart robotic arm Pt I:Soft computing KB optimizer-deep machine learning IT”.In the first part of the paper,we examined control systems with constant coefficients of the conventional PID controller(based on genetic algorithm)and intelligent control systems based on soft computing technologies.For demonstration,MatLab/Simulink models and a test benchmark of the robot manipulator demonstrated.Advantages and limitations of intelligent control systems based on soft computing technology discussed.Intelligent main element of the control system based on soft computing is a fuzzy controller with a knowledge base in it.In the first part of the article,two ways to implement fuzzy controllers showed.First way applyied 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 manipulator with seven degrees of freedom(7DOF).The second way use of separated control when an independent fuzzy controller controls each link.The control decomposition due to a slight decrease in the quality of management has greatly simplified the processes of creating and placing knowledge bases.In this Pt II,to eliminate the mismatch of the work of separate independent fuzzy controllers,methods for organizing coordination control based on quantum computing technologies to create robust intelligent control systems for robotic manipulators with 3DOF and 7DOF described.Quantum supremacy of developed end-to-end IT design of robust intelligent control systems demonstrated. 展开更多
关键词 Quantum computing supremacy Quantum-classical correlation Knowledge base Fuzzy controller Quantum fuzzy inference
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Robust PID Controller Design on Quantum Fuzzy Inference: Imperfect KB Quantum Self-Organization Effect-Quantum Supremacy Effect
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作者 L.V.Litvintseva V.S.Ulyanov Sergey V.Ulyanov 《Artificial Intelligence Advances》 2020年第1期59-70,共12页
The new method of robust self-organized PID controller design based on a quantum fuzzy inference algorithm is proposed.The structure and mechanism of a quantum PID controller(QPID)based on a quantum decision-making lo... The new method of robust self-organized PID controller design based on a quantum fuzzy inference algorithm is proposed.The structure and mechanism of a quantum PID controller(QPID)based on a quantum decision-making logic by using two K-gains of classical PID(with constant K-gains)controllers are investigated.Computational intelligence toolkit as a soft computing technology in learning situations is applied.Benchmark’s simulation results of intelligent robust control are demonstrated and analyzed.Quantum supremacy demonstrated. 展开更多
关键词 PID controller tuning Quantum fuzzy inference Intelligent control Quantum self-organization of imperfect KB Quantum supremacy
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Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit
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作者 Ulyanov Sergey Ulyanov Viktor Yamafuji Kazuo 《Artificial Intelligence Advances》 2020年第1期71-92,共22页
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 non... 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. 展开更多
关键词 Robotics unicycle Intelligent control systems Essentially nonlinear model Globally unstable model Stochastic simulation Soft computing
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