Introduction to the Theory of Smart Electromechanical Systems (Studies in Systems, Decision and Control, 486)

Preface
Contents
Abbreviations
1 Mechanisms and Control Systems
	1.1 SEMS Modules
	1.2 SEMS Architectures
		1.2.1 Serial Architecture
		1.2.2 Parallel Architecture
		1.2.3 Architecture of the “Star”
		1.2.4 Architecture of the “Ring”
		1.2.5 Architecture of the “Tree”
	1.3 Kinematic Models of SEMS
		1.3.1 The Direct Kinematics Problem
		1.3.2 The Inverse Problem of Kinematics
	1.4 Synthesis of Optimal SEMS Control Algorithms
		1.4.1 Mathematical Programming
		1.4.2 Mathematical Programming in the Ordinal Scale
		1.4.3 The Generalized Mathematical Programming
		1.4.4 Multistep Generalized Mathematical Programming
	1.5 Reduction of Logical-Probabilistic and Logical–Linguistic Constraints to Interval
		1.5.1 Prerequisites for Reducing Logical-Probabilistic Constraints to Interval Constraints
		1.5.2 Prerequisites for Reducing Logical–Linguistic Constraints to Interval Constraints
		1.5.3 An Example of Solving a Fuzzy Control Problem Using Interval Reduction Theorems
	1.6 SEMS Automatic Control Systems
		1.6.1 Architecture of Control Systems of Modules SEMS
		1.6.2 Automatic Control Subsystems of Mobile Elements of Modules SEMS
	1.7 Neuroprocessor Automatic Control System of the SEMS Module
	1.8 Anti-jamming in Automatic Control Systems of SEMS Modules
		1.8.1 The Use of Force Sensors
		1.8.2 Use of Pickoffs
		1.8.3 Using a Calculation Block of Optimal Trajectories
	1.9 Control of Vitality and Reliability Analysis
		1.9.1 A Simplified Accounting of the Relations Between the Blocks of a Complex System
		1.9.2 The Modeling of Changes with the Passing of Time of the Complex System Failure Probability with the Reservation of the Blocks
		1.9.3 The Algorithm of the Modeling of the Failure Probability with the Passing of Time of the Complex System with the Reservation of the Blocks
		1.9.4 Example
		1.9.5 Decision Making Methods for Durability Control
	1.10 Conclusion
	References
2 Central Nervous System
	2.1 Problems of Creating the Central Nervous System SEMS
		2.1.1 The Bodies of the Human Senses
		2.1.2 The Central Nervous System of the Human Senses
		2.1.3 Tasks of Construction of the Central Nervous System Robots
		2.1.4 Features of the Central Nervous System SEMS with Elements of the Psyche
		2.1.5 Supplementing the Structure of the Robot’s Central Nervous System with Elements of the Psyche
	2.2 Formation of Images Based on Sensory Data of Robots
		2.2.1 Fuzzification of Data
	2.3 Formation of the Robot’s Sensation Language
		2.3.1 Algorithm of Formation of the Language of Sensations of the Robot
		2.3.2 Quantization of the Surrounding Space
		2.3.3 Fuzzification of Sensory Information
		2.3.4 Image Formation in the Display of the Surrounding Space
		2.3.5 Formation of Images by Combining Images from Different Senses
	2.4 Classification of Images in the Central Nervous System
		2.4.1 Statement of the Problem of Inductive Formation of Images
		2.4.2 Algorithms for the Formation of Decision Rules
		2.4.3 Logical-Probabilistic and Logical–Linguistic Algorithms
		2.4.4 Testing Algorithms
	2.5 Image Classification System
		2.5.1 The Block Diagram of the System
		2.5.2 The Principle of Operation of the System
	2.6 Logical and Mathematical Model of Decision Making in the Central Nervous System SEMS
	2.7 Making Behavioral Decisions Based on Solving Systems of Logical Equations
		2.7.1 Stages of the Formation of Behavioral Decisions
		2.7.2 Features of Recognition, Described by Equations in Algebra Modulo Two
	2.8 Using Binary Relations When Decision Making
		2.8.1 The Tasks of Situational Control of a Group of Dynamic Objects
		2.8.2 Generalized Description of the Task of Situational Control of the SEMS Group
		2.8.3 Mathematical Methods for Using Binary Relations in Decision
	2.9 The Influence of Emotions on Decision Making
		2.9.1 The Emotional Component of the Decision Making System
		2.9.2 Estimates of the Strength of Emotion Based on the Use of Sensory Signals
		2.9.3 Estimates of the Strength of Emotion Based on the Analysis of Images Obtained After Processing Sensory Signals
		2.9.4 Example of Accounting for the Influence of Emotions
	2.10 The Influence of Temperament on Decision Making
		2.10.1 Types of Classification of Human Temperament
		2.10.2 Methods of Temperament Diagnostics
		2.10.3 Adaptation of SEMS to Human Temperament in Human–Machine Systems
		2.10.4 Correction of the Structure of the Central Nervous System SEMS
		2.10.5 Example of Taking into Account the Influence of Temperament in Human–Machine Systems
	2.11 Conclusion
	References
3 Group Control
	3.1 Principles of Situational Control of the SEMS Group
		3.1.1 The Concept of Situational Control
		3.1.2 The Principles of Situational Control SEMS Groups
		3.1.3 The Methodology of Situational Control SEMS Group
	3.2 Situational Control a Group of Robots Based on SEMS
		3.2.1 The Construction of the Current Dynamic Model of the Environment
		3.2.2 The Construction of the Current Dynamic Models of Robots
		3.2.3 An Example of the Construction PDSCR for the Task of Extracting from the Premises Items Robots-Loaders
	3.3 Movement Control of the SEMS Group
		3.3.1 Setting the Task of Controlling the Movement of a Group of Robots
		3.3.2 Principles of Situational Control
	3.4 Decision Making an Autonomous Robot Based on Matrix Solution of Systems of Logical Equations that Describe the Environment of Choice for Situational Control
		3.4.1 Processing of Information in the CNSR
		3.4.2 Genetic Robot Algorithms
		3.4.3 Methods of Decision Making Based on Robot Reflections in the Environment of Choice
	3.5 Using Influence Diagrams in Group Control of SEMS
		3.5.1 Options for Using Influence Diagrams When Making a Decision
		3.5.2 Features of the Search for the Optimal Decision in Various Variants of Situational Control Structures
	3.6 Secure Control of the SEMS Group
	3.7 Logical–Linguistic Method of the Movement of Mobile SEMS with Minimal Probability of Accidents
		3.7.1 The Routes Ranking Problem
		3.7.2 The Database of Reference Route Segments
		3.7.3 Determining the Probability of an Accident on a Route
		3.7.4 Ranking and Optimization of Routes
	3.8 Assessment of the Group Intelligence of SEMS in RTS
		3.8.1 Test Simulation of a Robotic System
		3.8.2 Baseline Assessment of Group Intelligence in the Central Nervous System RTS
	3.9 Software Package for Testing Group Intelligence Assessment Models
		3.9.1 A Typical Structure of a Software System Testing of Models of Groups of Robots
		3.9.2 Assembly and Adjustment of Models of Control Object
		3.9.3 Assembly and Adjustment of Models of the Environment
		3.9.4 The Assembly of Test Models Groups of Robots
		3.9.5 Testing Groups of Robots
		3.9.6 Model Training and Correction
	3.10 Conclusion
	References
4 Examples of Using SEMS Modules
	4.1 Controlled Ciliated Thrusters
		4.1.1 Muscles
		4.1.2 Ciliated Apparatus
		4.1.3 Simple Ciliated Thruster
		4.1.4 Ciliated Thruster with Controlled Rigidity
		4.1.5 Ciliated Thruster with Controlled Rigidity and Shape
	4.2 Flagellar Thruster
		4.2.1 Biological Flagellum
		4.2.2 Structure of the Flagellar Thruster
		4.2.3 Architecture of the Automatic Control System
	4.3 Medical Micro Robot
		4.3.1 New Micro Robot Device
		4.3.2 Operation of the Device
	4.4 Adaptive Capture
		4.4.1 Capture Device
		4.4.2 Capture Operation
		4.4.3 Algorithms of Automatic Control System Operation
		4.4.4 Adaptive Capture Automatic Control System
	4.5 Using a Platform Based on SEMS Modules for Obtaining Radio Images in Astronomy
		4.5.1 Problems of Creating a Matrix Radio Receiver
		4.5.2 Estimation of Optimal Pixel Sizes of Matrix Receivers
		4.5.3 Matrix Receiver Adaptation Algorithms
		4.5.4 Adaptive Matrix Receiver Control System
	4.6 SEMS Actuator System for the Space Radio Telescope Subdish
		4.6.1 Simulation of Natural Oscillations of the Subdish
		4.6.2 Calculation of ACS Parameters
		4.6.3 Analysis of the Dynamics of the Automatic Control System
		4.6.4 Accounting for Nonlinearities in the Automatic Control System of the Actuator
	4.7 Antenna of the Space Radio Telescope
		4.7.1 Antenna Formation in Near-Earth Orbit
		4.7.2 The Device of the Space Radio Telescope
		4.7.3 Operation of the Control System
		4.7.4 The Choice of the Satellite Orbit During the Formation of the Adaptive Mirror Antenna System of the Space Radio Telescope
	4.8 Conclusion
	References