Abstract
In industrial environments, disturbance handling is a major issue in reconfigurable manufacturing control systems, supporting the fast, effective and efficient response to the occurrence of unexpected disturbances. Those disturbances usually degrade the performance of the system, causing the loss of productivity and business opportunities, which are crucial roles to achieve competitiveness. This paper proposes an agent-based disturbance handling architecture that distributes the disturbance handling functions by several autonomous control units and considers the main types of shop floor disturbances that have impact at planning and scheduling level. The proposed architecture also integrates a prediction component, transforming the traditional "fail and recover" practices into "predict and prevent" practices. © 2007 IFAC.

Abstract
This paper discusses a new approach to the development life-cycle of agent-based production control applications, from the design to the operation, based in a catalogue of High-level Petri nets. The High-level Petri net-based approach facilitates the conception, definition and formal specification of an "encapsulation process" in industrial production systems. The catalogue includes elements for the identification of manufacturing components, the development of agent-based control units, the formal validation of the models and the formal specification of complete collaborative automation scenarios.

Abstract
In the last years, several manufacturing control architectures using emergent paradigms and technologies, such as multi-agent and holonic manufacturing systems, have been proposed to address the challenge of developing control systems capable of handling certain types of disturbances at the factory level. One of these holonic architectures is ADACOR, which integrates a set of paradigms and technologies for distributed manufacturing systems complemented by formal modelling techniques, to achieve a flexible and adaptive holonic/collaborative control architecture. The results obtained in the first experiments using the ADACOR architecture are presented in this paper, and also compared to the results produced by other control architectures. For this purpose a set of quantitative and qualitative parameters were measured, to evaluate static and dynamic performance of the control architectures.

Abstract
This paper intends to discuss self-organisation and learning capabilities in autonomous and cooperative holons that are part of a holonic manufacturing control system. These capabilities will support the dynamic adaptation of the manufacturing control to the manufacturing evolution and emergency, specially the agile reaction to unexpected disturbances.

Abstract
Disturbance handling is a crucial issue in the development of intelligent and reconfigurable manufacturing control systems, supporting the fast and promptly response to the occurrence of unexpected disturbances. In holonic manufacturing control systems, the disturbance handling functions are distributed by the several autonomous control units. In this paper, a predictive disturbance handling approach is presented, transforming the traditional "fail and recover" practices into "predict and prevent" practices, allowing improving the control system performance.

Abstract
The current demand for customization, flexibility and responsiveness constitutes a challenge to achieve intelligent and adaptive manufacturing systems. Understanding how in nature the complex things are performed in a simple and effective way, allows us to copy them and develop complex and powerful adaptive and evolvable systems. The paper overviews some principles found in nature and biology and analyses the application of bio-inspired solutions to solve complex engineering problems, especially in the manufacturing field. The paper also discusses the effective applicability of these methods in several areas of manufacturing systems and analyses the available agent-based tools to support the simulation of bio-inspired solutions.