Safe-guarded multi-agent control for mechatronic systems: implementation framework and design patterns

This thesis addresses two issues: (i) developing an implementation framework for Multi-Agent Control Systems (MACS); and (ii) developing a pattern-based safe-guarded MACS design method.\ud \ud The Multi-Agent Controller Implementation Framework (MACIF), developed by Van Breemen (2001), is selected as the starting point because of its capability to produce MACS for solving complex control problems with two useful features:\ud • MACS is hierarchically structured in terms of a coordinated group of elementary and/or composite controller-agents;\ud • MACS has an open architecture such that controller-agents can be added, modified or removed without redesigning and/or reprogramming the remaining part of the MACS

Describing Structure and Complex Interactions in Multi-Agent-Based Industrial Cyber-Physical Systems

The description of structure and complex interactions in Multi-agent-based Industrial Cyber-physical (MAS-ICPS) systems has been elusively addressed in the literature. Existing works, grounded on model-based engineering, have been successful at characterizing and solving system integration problems. However, they fail to describe accurately the collective and dynamic execution behaviour of large and complex industrial systems, particularly in more discrete production domains, such as: automotive, home appliances, aerospace, food and beverages, etc. In these domains, the execution flow diverts dynamically due to production disturbances, custom orders, fluctuations in demand in mixed model production, faults, quality-control and product rework, etc. These dynamic conditions require re-allocation and reconfiguration of production resources, redirection of production flows, re-scheduling of orders, etc. A meta-model for describing the structure and complex interactions in MAS-ICPS is defined in this paper. This contribution goes beyond the State-Of-The-Art (SOTA) as the proposed meta-model describes structure, as many other literature contributions, but also describes the execution behaviour of arbitrarily complex interactions. The previous is achieved with the introduction of general execution flow control operators in the meta-model. These operators cover, among other aspects, delegation of the execution flow and dynamic decision making. Additionally, the contribution also goes beyond the SOTA by including validation mechanisms for the models generated by the meta-model. Finally, the contribution adds to the current literature by providing a meta-model focusing on production execution and not just on describing the structural connectivity aspects of ICPSs.publishersversionpublishe

Assessing self-organization and emergence in Evolvable Assembly Systems (EAS)

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThere is a growing interest from industry in the applications of distributed IT. Currently, most modern plants use distributed controllers either to control production processes, monitor them or both. Despite the efforts on the last years to improve the implementation of the new manufacturing paradigms, the industry is still mainly using traditional controllers. Now, more than ever, with an economic crisis the costumers are searching for cheap and customized products, which represents a great opportunity for the new paradigms to claim their space in the market. Most of the research on distributed manufacturing is regarding the control and communication infrastructure. They are key aspects for self-organization and there is a lack of study on the metrics that regulate the self-organization and autonomous response of modern production paradigms. This thesis presents a probabilistic framework that promotes self-organization on a multiagent system based on a new manufacturing concept, the Evolvable Assembly Systems/Evolvable Production Systems. A methodology is proposed to assess the impact of self-organization on the system behavior, by the application of the probabilistic framework that has the dual purpose of controlling and explaining the system dynamics. The probabilistic framework shows the likelihood of some resources being allocated to the production process. This information is constantly updated and exchanged by the agents that compose the system. The emergent effect of this self-organization dynamic is an even load balancing across the system without any centralized controller. The target systems of this work are therefore small systems with small production batches but with a high variability of production conditions and products. The agents that compose the system originated in the agent based architecture of the FP7-IDEAS proejct. This work has extended these agents and the outcome has been tested in the IDEAS demonstrators, as the changes have been incorporated in the latest version of the architecture, and in a simulation and more controlled environment were the proposed metric and its influence were assessed

Towards the integration of process and quality control using multi-agent technology

The paper introduces a vision on the design of distributed manufacturing control systems using the multi-agent principles to enhance the integration of the production and quality control processes. It is highlighted how agent technology may enforce interaction of manufacturing execution system and distributed control system, enhancing the exploitation of the available information at the quality control and process control levels. A specific focus is made on a suitable engineering methodology for the design and realization of such concept. Innovation is also presented at the level of adaptive process control and self-optimizing quality control, with examples related to a home appliance production line

Design of Lane Keeping Algorithm of Autonomous Vehicle

The paper presents the design and realization of lane keeping function of an autonomous electric go-cart. The requirement towards the system concerning this paper is navigating the vehicle on a closed track with road markings, based on information from an optical camera with lane detection capabilities. To achieve this task, two solutions were used, a double-loop control with feedforward load disturbance compensation and a nonlinear method. The control algorithms were designed and tuned in a Hardware-In-The-Loop framework. The nonlinear algorithm was implemented on two different hardware devices and validated in CarSim–Matlab software environment

A decentralized control framework for modular robots

Distributed control paradigm offers robustness, scalability, and simplicity to the control and organization of module based systems. MSR (Modular Self-Reconfigurable) robot is a class of robot that best demonstrate the effectiveness of distributed systems as all modules in the robot are individuals that perform their own actuation and computation; the behavior of the complete robot is a collective behavior of all independent modules. In this paper, a general control framework, named General Suppression Framework, is proposed and a distributed control system based on the framework is presented. The control system is designed to control a set of MSR robots configured into a planar manipulator arm. All modules in the manipulator arm contain their own processing and actuation units, which allow them to evaluate and react to the environment independently. The modules can perform passive communication with their immediate neighbors and can exhibit aggressive or tolerant behavior based on the environment change to generate emergent group behaviors. A simulation program is developed to demonstrate the effectiveness of the distributed system in controlling the module based planar manipulator arm.published_or_final_versio

Data-Driven Predictive Control for Multi-Agent Decision Making With Chance Constraints

In the recent literature, significant and substantial efforts have been dedicated to the important area of multi-agent decision-making problems. Particularly here, the model predictive control (MPC) methodology has demonstrated its effectiveness in various applications, such as mobile robots, unmanned vehicles, and drones. Nevertheless, in many specific scenarios involving the MPC methodology, accurate and effective system identification is a commonly encountered challenge. As a consequence, the overall system performance could be significantly weakened in outcome when the traditional MPC algorithm is adopted under such circumstances. To cater to this rather major shortcoming, this paper investigates an alternate data-driven approach to solve the multi-agent decision-making problem. Utilizing an innovative modified methodology with suitable closed-loop input/output measurements that comply with the appropriate persistency of excitation condition, a non-parametric predictive model is suitably constructed. This non-parametric predictive model approach in the work here attains the key advantage of alleviating the rather heavy computational burden encountered in the optimization procedures typical in alternative methodologies requiring open-loop input/output measurement data collection and parametric system identification. Then with a conservative approximation of probabilistic chance constraints for the MPC problem, a resulting deterministic optimization problem is formulated and solved efficiently and effectively. In the work here, this intuitive data-driven approach is also shown to preserve good robustness properties. Finally, a multi-drone system is used to demonstrate the practical appeal and highly effective outcome of this promising development in achieving very good system performance.Comment: 10 pages, 6 figure

A complex overview of modeling and control of the rotary single inverted pendulum system

The purpose of this paper is to present an in-depth survey of the rotary single inverted pendulum system from a control engineer's point of view. The scope of the survey includes modeling and open-loop analysis of the system as well as design and verification of balancing and swing up controllers which ensure successful stabilization of the pendulum in the unstable upright equilibrium. All relevant tasks and simulation experiments are conducted using the appropriate function blocks, GUI applications and demonstration schemes from a Simulink block library developed by the authors of the paper. The library is called Inverted Pendula Modeling and Control (IPMaC) and offers comprehensive program support for modeling, simulation and control of classical (linear) and rotary inverted pendulum systems