Abstract
Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.
Highlights
The major novelty of this work is that the feedback control part is realized in a real-time periodic multiagent control system (MACS), while the learning feedforward control algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS
This paper has presented a novel MACS-based time-index learning feedforward control (LFFC) design method for mechatronic systems
The feedback control part is realized in a real-time periodic MACS, while the time-index LFFC algorithm can be deployed on-line, asynchronously, and in a separate non-real-time aperiodic MACS
Summary
Open Robot Control Software (OROCOS) is a software framework for general robot/machine control that provides a real-time toolkit to develop component-based real-time control applications [34,36]. In the OROCOS framework, a component is a basic unit of functionality that executes one or more (real-time) programs or tasks in a single thread. Multithreaded components can be built such that they form real-time, thread-safe robot/machine control applications [37,38]. Components in OROCOS are implemented by subclassing the C++ TaskContext class. An OROCOS component is called a TaskContext. TaskContext defines the “context” in which application-specific tasks are executed. A TaskContext is described through five primitives, i.e., attributes and properties, commands, methods, events, and data flow ports [38]. The interface between TaskContexts is implemented based on these primitives
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
