A multi-agent controller on embedded system for complex mechatronics

This paper presents a control system design and development approach for a vision-based automated guided vehicle (AGV) based on the multi-agent system (MAS) methodology and embedded system resources. A three-phase agent-oriented design methodology Prometheus is used to analyse system functions, construct operation scenarios, define agent types and design the MAS coordination mechanism. The control system is then developed in an embedded implementation containing a digital signal processor (DSP) and an advanced RISC machine (ARM) by using the multitasking processing capacity of multiple microprocessors and system services of a real-time operating system (RTOS). As a paradigm, an onboard embedded controller is designed and developed for the AGV with a camera detecting guiding landmarks, and the entire procedure has a high efficiency and a clear hierarchy. A vision guidance experiment for our AGV is carried out in a space-limited laboratory environment to verify the perception capacity and the onboard intelligence of the agent-oriented embedded control system.

As the complexity and scale of modern buildings increase, there is a growing need for efficient, scalable, and flexible control systems to manage the myriad of sensors, actuators, and meters involved in building automation. Traditional building management systems (BMS) struggle with scalability, especially when dealing with multi-agent control setups that require extensive manual configuration. This limitation poses significant challenges in deploying advanced control strategies across different building environments, leading to inefficiencies and underutilization of building automation technologies.Previous research has explored various aspects of multi-agent systems (MAS) in building automation, including agent-based modeling, decentralized control strategies, and the application of machine learning to optimize building operations. However, much of the existing work has focused on small-scale implementations or specific applications, such as energy management or HVAC control. The problem of automating the setup of multi-agent control systems to adapt to different building environments with minimal manual intervention remains largely unaddressed.The aim of this work is to develop a scalable framework for the automated setup of multi-agent control systems in buildings. This framework will enable the seamless integration of sensors, actuators, and meters into a unified control system, significantly reducing the need for manual configuration. The framework will leverage large language models (LLMs) for semantic tagging and context understanding, thereby facilitating the automated configuration of action and input spaces for individual agents within the control system.The proposed framework will consist of three key components: (1) an LLM-based system for semantic tagging and context interpretation, (2) an automated setup process for defining the action and input spaces of the agents, (3) and an initial offline training of the agents. The LLM will be trained on a diverse dataset of building management setups to ensure it can accurately tag and interpret various building elements. The system will be tested in real-world office buildings to evaluate its scalability, accuracy, and effectiveness.Preliminary simulations indicate that the automated setup framework can significantly reduce the time and effort required to deploy multi-agent control systems in buildings. We expect that this framework will enable more scalable and flexible building management systems, ultimately leading to improved energy efficiency, occupant comfort, and overall operational performance. The significance of this work lies in its potential to transform the deployment of building automation systems, making advanced control strategies more accessible and cost-effective across various building types and scales.

This paper describes Artificial Immune-Based Control System that is applied to the automatic transportation control system of AGV (Automated Guided Vehicle) operated in a restricted area such as a container terminal and an ironworks. The authors propose the non-network type artificial immune system that is functioning in a unit level of antibodies instead of in a network of antigens and antibodies. AGVs equipped by the proposed method can avoid the collision and/or the deadlock and move autonomously from the source points to the destinations. The transportation system using AGVs has been expected because AGVs have the flexibility and efficiency. However the control system for AGVs is so flexible that the design has a big margin. Especially, the design for the control system is a hard work when the number of AGV becomes to be large. Only a few study of this problem is found in a past references. This paper focuses on the automatic transportation plan of AGVs in a real time scheduling using the non-network type artificial immune system. The comparison of the proposed method: the non-network type artificial immune system and the network type artificial immune system are also discussed and the computer simulation verifies the effectiveness of the proposed method.

The increasing use of Automated Guided Vehicles (AGV) in the industry points to a search for better techniques and technologies to adapt to market requirements. Proper position control and movement give an AGV greater movement accuracy and greater lateral oscillations stability and vibration. AGVs control techniques are not new, but new sensors applications are possible, such as RGB cameras, imposing the need for dynamic performance tests as an element of control systems. In this sense, it is necessary to ensure the sensor is adequate to control requirements. This work addresses AGVs driven by passive floor demarcations. It presents an analysis of RGB camera as a sensor for AGV control. We performed the experiments with a small AGV prototype on an eight-shaped lane, varying both image resolution parameters. Paper main contribution is a qualitative and quantitative analysis for the different sensor configurations. The experiments confirm sensor pertinence for the proposed control system.

Simulation of Human Effect to the Adaptive Logistics System Used in Public Facilities

The MAS (Multi-Agent System) theory is already widely applied to the mechanical machining, especially the study on the robot. This paper puts forward a multi-Agent alliance control model that is made up of the series robot Agent, the parallel moving platform Agent and the polishing tool system Agent and so on by the MAS theory. Through the introduction of point-curve constraint, the dynamics of the constraint multi-rigid body equation for the polishing system is established in order to accurately program the moving track of the robots. Meanwhile, the control parameters during the polishing can be optimized. The satisfied polishing effect on the curved surfaces can be obtained and the demand of the polishing can be achieved by the MAS.

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

The Automated Guided Vehicle (AGV) is a device that uses various sensor technologies, automation, and multiple control systems. AGVs have many navigation methods, of which the magnetic stripe navigation system is well developed. The magnetic stripe navigation AGV positioning is carried out precisely and at a lower cost level. However, the magnetic stripe is prone to breakage, and the AGV can only travel according to the magnetic stripe and cannot be intelligently avoided or the task changed in real-time by the control system. This paper draws on magnetic stripe navigation tracking principles, using grey-scale sensors for stable path tracking; distance sensors are combined for timely obstacle avoidance; Bluetooth is used to obtain approximate indoor locations for path planning. The navigation system simultaneously combines multi-sensor information for navigation, ultimately enabling the AGV to be quickly positioned accurately along the prescribed path and return to the route in time to avoid obstacles.

The paper presents a distributed computing environment for embedded control systems with time-triggered and event-triggered distributed processing. We have already presented a time-triggered distributed object model and a time-triggered distributed computing environment for embedded control systems. However, there are many embedded control systems with time-triggered and event-triggered processing. In this paper, we present two kinds of event-triggered distributed object models, a pure event-triggered distributed object model and a data-triggered distributed object model, in addition to the time-triggered distributed object model. We also present a distributed object computing environment based on a time-division scheduling for the mixed architecture with time-triggered and event-triggered distributed processing. The time division scheduling divides an execution cycle into a time-triggered processing segment and a non-time-triggered processing segment. The time-triggered distributed processing is executed in the former segment, and the event-triggered distributed processing is executed in the latter segment. The distributed object computing environment consists of a real-time operating system with the time division scheduling and distributed computing middleware to support the three kinds of distributed object models. We provide a development environment that generates stubs and configuration data to build distributed control systems.

This paper presents a distributed real-time control scheme based on multi-agent systems for cost optimisation of a micro-grid using real-time dynamic price estimation. The real-time prices are forecast using realistic UK energy price data via a Markov Chain Monte Carlo algorithm. A backup mechanism for main containers of the agent platform is implemented to improve fault tolerance of the control system, addressing the single point of failure problem at the hardware and software levels. The Multi-Agent system developed in JAVA and run with Raspberry Pi controls a simulated microgrid in an OPAL-RT real-time simulator to test the accuracy of the estimation method, the capacity of the control to realise power management at minimal supply cost, and uninterrupted operation in case of container faults.

An embedded control system is commonly used in the automotive industry to achieve complex and accurate control functionality. An embedded control system consists of three portions including a control object, i.e. the peripheral under control, a micro-controller and control software that is executed on the micro-controller. This paper presents an approach that meets well the challenge in entire embedded control system simulation. Two examples are presented to illustrate how an embedded control system can be simulated as an entity to explore the interaction among the three elements, including the customer code, the micro-controller and the control object of the system. The entire embedded control systems are implemented in Saber, a mixed-signal, mixed-technology simulator.

In this paper we propose a dynamic multi automated guided vehicle (AGV) scheduling method based on the scheduling properties of automated container terminal handling systems. In multi-AGV scheduling, the composition of AGV handling time and the precedence order of certain tasks are major constraints. Taking these into consideration, we design a genetic algorithm (GA) for a dynamic multi-AGV scheduling model to minimize completion time and standard deviation of handling time of quay cranes (QC), and validated the proposed model through numerical experiment. We expect this model to be significant for multi-agent scheduling of discrete production systems.

Engineering non-trivial open multi-agent systems is a challenging task. Our research focusses on situated multi-agent systems, i.e. systems in which agents are explicitly placed in a context – an environment – which agents can perceive and in which they can act. Two concerns are essential in developing such open systems. First, the agents must be adaptive in order to exhibit suitable behavior in changing circumstances of the system: new agents may join the system, others may leave, the environment may change, e.g. its topology or its characteristics such as throughput and visibility. A well-known family of agent architectures for adaptive behavior are free-flow architectures. However, building a free-flow architecture based on an analysis of the problem domain is a quasi-impossible job for non-trivial agents. Second, multi-agent systems developers as software engineers require suitable abstractions for describing and structuring agent behavior. The abstraction of a role obviously is essential in this respect. Earlier, we proposed statecharts as a formalism to describe roles. Although this allows application developers to describe roles comfortably, the formalism supports rigid behavior only, and hampers adaptive behavior in changing environments.In this paper we describe how a synergy can be reached between free-flow architectures and statechart models in order to combine the best of both worlds: adaptivity and suitable abstractions. We illustrate the result through a case study on controlling a collection of automated guided vehicles (AGVs), which is the subject of an industrial project.

The electric power system is an enabling infrastructure that supports the operation of other critical infrastructures and thus the economic well being of the nation. It is therefore very important to design a smart grid for resiliency and autonomous re-configurability in the electric power grid. For the operation of any power system, its control architecture consisting of hardware and software protocols is very essential for exchanging system status and control signals. This is accomplished by Supervisory Control and Data Acquisition (SCADA) systems. Current trends to control and monitor the operation of electric power systems are however moving towards the use of an automated agent technology using a multi-agent system which replaces SCADA system. The objective of this paper is to design and model a multiagent system which consists of Distributed Energy Resource (DER) agent, Data Base agent, Control agent and User agent. DER agent is modeled using MATLAB/SIMULINK. The simulation results presented in this paper show the seamless transition from grid connected to an island mode when upstream outages are detected. This denotes the capability of a multi-agent system as a technology for managing the microgrid operation.

The cyber-security of multi-agent control systems has become vital in practice. To protect the communication process between the individual agents over TCP/IP networks, one must encrypt the messages to be sent, which is costly in a large-scale network when high-level security is demanded. To lessen the burden of heavy encryption and decryption processes, we introduce the Homomorphic Encryption to reduce the number of encryption/decryption terminals that are supposed to equip with every agent. The security is enhanced by the quantum key distribution technology, which can generate secret keys that are theoretically absolutely secure even against quantum computation. We proposed a hybrid method that make good use of the randomness of quantum keys, one-time pad and symmetric encryption to make sure the overall security of homomorphic encryption algorithms. Numerical simulations are provided to illustrate how our scheme.