**2. Design and application of agent-based control system to all sets of 'clustered' controller agents**

**3. Mathematical modelling and transfer function of agent-based control**

*Agent-based control system using directed communication graph approach as a tool towards Industry 4.0.*

*Agent-Based Control System as a Tool towards Industry 4.0: Directed Communication Graph…*

*DOI: http://dx.doi.org/10.5772/intechopen.87180*

This section explores the techniques around the modelling and detailed design for the agent-based control system development. The mathematical theory involve multiple modelling techniques, while the decomposition of the control system is the shows the dynamic behaviour of all these modelling techniques. The idea synthesis and process model for an agent's collaboration and communication concepts was adopted from other scholars in the field of control. The development of an open architecture (OA) based intelligent fuzzy-PID; require the processing of the input signal variables (balise signal) going through the fuzzification with linguistic membership generation does not require a precise mathematical representation of the process. The train controller agent provides robust control and stability for the brake traction via rail controller agent within a range of operating parameter

The closed-loop transfer function can be derived as shown in **Figure 2**, as a

*C s*ðÞ¼ *G*3*Ds* þ *G*2*G*3*G*<sup>1</sup> *GffRs* þ *GfbGc*

*C s*ðÞ¼ *G*3*Ds* þ *G*2*G*3*G*4*G*<sup>1</sup> *GffRs* þ *Gfb*½ � *Rs* � *HCS*

(1)

(2)

**system for sets of 'clustered' controller agents**

function of the fuzzy-PID controller gains as follows:

Solving Eq. (2) for C(s), we get;

changes.

**231**

**Figure 1.**

The design of agent-based control systems involves the cooperation of agents in multi-agent systems (MASs), which is dependent on effective communication and sharing information to reach a global coordination. This design required a sensing information from local sensors, or collected data by some agent or subset of nearby agents with a set of rules for assigning decision tasks. The communicated information is a point-to-point message with assumed limited bandwidth routed in more modularised design send information that is more complex. The control models for agent interaction protocol as presented in **Figure 1** use directed communication graph (DCG), which displays the topographical features as a form of information feedback loops for the flow of information (sensed or communicated). It is to strongly connect a directed path between any two agents and weakly connect an undirected path between any two agents if exists. The dynamics of the agents is the encoding of intra-agent internal state associated with the definition of the functionality and behavioural aspects of the relationship to current task.

The agent-based system conceptualisation brings about a great deal of deep and vast thought. The success of the agent-based control system necessitates the synthesis of ideas and the processes revision that ought to be model for agent's collaboration and communication. The method for integration of agents into a control system is of significance in facilitating the conception and visualisation of the needs to perform the iteration.

*Agent-Based Control System as a Tool towards Industry 4.0: Directed Communication Graph… DOI: http://dx.doi.org/10.5772/intechopen.87180*

#### **Figure 1.**

Internet of Things (IOT), energy efficiency services, and cloud computing. In the development of products and services adaption to human needs and corporate social responsibility, the promotion of the Industry 4.0 revolution proliferate in the three tier of industries namely: primary, secondary and tertiary with the horizontal expansion of information technology, creative connection between the market and acquisition of a leadership position in manufacturing sector in the world [44]. At the same time, USA developed the 'Advanced Manufacturing Partnership', a reindustrialization plan aimed at innovating manufacturing through the adoption of intelligent production systems and improving the occupational levels of the country in order to increase productivity and reduce costs. The idea include key dimensions in the technology landscape, which includes big data, connectivity, automation, machine learning, application of intelligent agents, artificial intelligence, use of sensors, block chains, virtual reality, augmented reality and 3D printing. In 2015, France launched the 'Alliance for the Future program' to implement the digitization process for support innovation, while in 2016 Italy approved the Industry 4.0 revolution plan [45]. The short supplies in the requisite human skills and technological capabilities with the unknown in product and processes of the next generation of equipment with embedded custom designed software for responsive and interactive tracking of own activities along with other product activity around them

This section introduces a review of the general concepts of agent's, agent-based systems and integration into control systems. The rest of the chapter is organized as follows. In Section 2, design and application was treated with some concepts in graph theory, and Section 3 mathematical modelling and transfer function of agentbased control system where the problem to be investigated is formulated with theoretical results for consensus were derived. Section 4 is the conclusion.

**2. Design and application of agent-based control system to all sets of**

of nearby agents with a set of rules for assigning decision tasks. The

communicated information is a point-to-point message with assumed limited bandwidth routed in more modularised design send information that is more complex. The control models for agent interaction protocol as presented in **Figure 1** use directed communication graph (DCG), which displays the topographical features as a form of information feedback loops for the flow of information (sensed or communicated). It is to strongly connect a directed path between any two agents and

weakly connect an undirected path between any two agents if exists. The

dynamics of the agents is the encoding of intra-agent internal state associated with the definition of the functionality and behavioural aspects of the relationship to

The agent-based system conceptualisation brings about a great deal of deep and vast thought. The success of the agent-based control system necessitates the synthesis of ideas and the processes revision that ought to be model for agent's collaboration and communication. The method for integration of agents into a control system is of significance in facilitating the conception and visualisation of the needs

The design of agent-based control systems involves the cooperation of agents in multi-agent systems (MASs), which is dependent on effective communication and sharing information to reach a global coordination. This design required a sensing information from local sensors, or collected data by some agent or subset

are the subject of the chapter.

*Control Theory in Engineering*

**'clustered' controller agents**

current task.

**230**

to perform the iteration.

*Agent-based control system using directed communication graph approach as a tool towards Industry 4.0.*
