Acceleration of the Multilayer Network Operator Method Using MPI for Mobile Robot Team Control Synthesis

The paper presents a solution to the problem of optimal control of a quadrocopter under phase constraints by the numerical method of a network operator based on multi-point stabilization. According to this approach, the task of control system synthesis is initially solved. As a result, the quadrocopter is stabilized with respect to a certain point in the state space. At the second stage, a sequence of stabilization points is searched in the state space such that switching the stabilization points at fixed times ensures the movement of the quadrocopter from the initial state to the terminal state with an optimal value of the quality criterion taking into account phase constraints. To solve the problem of stabilization system synthesis, the network operator method is used. The method is numerical and, unlike the well-known analytical methods, allows to synthesize a control system automatically without a specific analysis of the right parts of the model. The method allows to find the structure and parameters of a mathematical expression in the encoded form using the genetic algorithm. The network operator code is an integer upper-triangular matrix. At the stage of solving the synthesis problem, the mathematical model of quadrocopter motion is decomposed into angular and spatial motions in order to separate control components for angular and spatial motions, respectively. The synthesized stabilization system consists of two subsystems connected in series for spatial and angular motion. As controls for spatial motion, moments around the axes and the total thrust of all quadcopter propellers were used. And the inputs for the angular motion stabilization system are the desired angles of inclination of the quadrocopter. The stabilization problem is considered as a general synthesis task for a control system. Using the network operator method, one control function is searched that provides stabilization of the object at a given point in the considered state space from the set of initial conditions. At the stage of the search for equilibrium points, the evolutionary particle swarm algorithm is used. A numerical example of solving the problem of optimal control of a quadrocopter with four phase constraints is given.

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Self-adjusting control for multi robot team by the network operator method

2015 European Control Conference (ECC) ◽

10.1109/ecc.2015.7330625 ◽

2015 ◽

Cited By ~ 8

Author(s):

A. I. Diveev ◽

E. Yu. Shmalko

Keyword(s):

Operator Method ◽

Network Operator ◽

Multi Robot

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Testbed for control synthesis for multiple mobile robot systems : General concept and current research*

2020 7th International Conference on Control, Decision and Information Technologies (CoDIT) ◽

10.1109/codit49905.2020.9263878 ◽

2020 ◽

Author(s):

Elzbieta Roszkowska ◽

Janusz Jakubiak

Keyword(s):

Mobile Robot ◽

General Concept ◽

Control Synthesis ◽

Robot Systems

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Synthesis of a mobile robot spatial stabilization system based on machine learning control by symbolic regression

RUDN Journal of Engineering Researches ◽

10.22363/2312-8143-2021-22-2-129-138 ◽

2021 ◽

Vol 22 (2) ◽

pp. 129-138

Author(s):

Askhat I. Diveev ◽

Neder Jair Mendez Florez

Keyword(s):

Machine Learning ◽

Mobile Robot ◽

Initial Conditions ◽

Symbolic Regression ◽

Synthesis Problem ◽

Terminal Point ◽

Control Synthesis ◽

Stabilization System ◽

Nonlinear Feedback ◽

Regression Methods

The spatial stabilization system synthesis problem of the robot is considered. The historical overview of methods and approaches for solving the problem of control synthesis is given. It is shown that the control synthesis problem is the most important task in the field of control, for which there are no universal numerical methods for solving it. As one of the ways to solve this problem, it is proposed to use the method of machine learning based on the application of modern symbolic regression methods. This allows you to build universal algorithms for solving control synthesis problems. Several most promising symbolic regression methods are considered for application in control tasks. The formal statement of the control synthesis problem for its numerical solution is given. Examples of solving problems of synthesis of system of spatial stabilization of mobile robot by method of network operator and variation Cartesian genetic programming are given. The problem required finding one nonlinear feedback function to move the robot from thirty initial conditions to one terminal point. Mathematical records of the obtained control functions are given. Results of simulation of control systems obtained by symbolic regression methods are given.

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