Optimization of Networked Control Systems using Integrated Fuzzy Logic PID Controller and Hybrid GWO-WOA Algorithm

Problem Definition

NCSs, as spatially distributed systems with interconnected actuators, controllers, and sensors, heavily rely on efficient communication networks for data transfer. The delays and packet dropouts in these networks pose a significant challenge to the performance of the feedback control mechanism within NCS. While Fuzzy PID controllers have been effective in addressing stochastically varying time delays in defined cases, there is a clear need for a more comprehensive method that can handle both defined and undefined scenarios. This gap in existing methodologies highlights the importance of utilizing improved optimization techniques such as Grey Wolf and Whale optimization to enhance system accuracy and speed. By developing a robust approach that addresses the limitations of traditional methods, the overall efficiency and effectiveness of NCSs can be substantially improved.

Objective

The objective is to develop a robust approach to enhance the efficiency and effectiveness of networked control systems (NCSs) by addressing the challenges posed by communication delays and packet dropouts. This will be achieved by integrating PID controllers, Fuzzy logic, and improved optimization techniques such as Grey Wolf and Whale optimization algorithms to improve system accuracy and speed. The goal is to provide a more comprehensive solution to handle both defined and undefined scenarios in NCSs, ultimately improving the overall performance of the system.

Proposed Work

In this work, the focus is on addressing the challenges posed by networked control systems (NCSs) where communication plays a crucial role in the overall system performance. While fuzzy PID controllers have been effective in handling varying time delays in NCSs, there is a need for a more comprehensive approach that can cater to both defined and undefined cases. By incorporating improved optimization techniques such as the Grey Wolf and Whale optimization algorithms, the goal is to enhance system accuracy and speed, ultimately providing a more efficient solution to the shortcomings of traditional methods. The proposed work involves inputting random variables into the NCS plant with predefined parameters before integrating the PID controller and Fuzzy logic to monitor data communication. The PID controller focuses on managing communication flow, transmission time, and handling packet dropouts, while the Fuzzy logic improves efficiency.

Issues such as broadcast delays, random variations, and packet dropouts can impact controller performance, highlighting the significance of addressing network-induced delays. The integration of PID and Fuzzy logic controllers leads to the derivation of mathematical transfer functions, followed by optimization using enhanced Grey Wolf and Whale optimization algorithms to enhance overall system performance. By optimizing the output iteratively, the proposed approach aims to improve the response of the system, addressing the challenges posed by NCSs effectively.

Application Area for Industry

This project can be applied in various industrial sectors such as manufacturing, process control, robotics, and automation. Industries face challenges related to communication delays, packet dropouts, and network efficiency in their control systems, which can impact the overall performance and accuracy of the system. By using Fuzzy PID controllers integrated with improved optimization techniques like Grey Wolf and Whale optimization, the project offers solutions to address these challenges effectively. The enhanced system accuracy and speed achieved through this comprehensive method can benefit industries by improving control strategy, reducing transmission delays, and enhancing overall network performance. Implementation of these solutions can lead to increased productivity, efficiency, and reliability in industrial processes, making the project valuable across different industrial domains.

Application Area for Academics

The proposed project can enrich academic research, education, and training by providing a comprehensive method for dealing with the challenges faced in Networked Control Systems (NCS). By integrating Fuzzy PID controllers with improved optimization techniques such as Grey Wolf and Whale optimization, the project addresses issues such as packet dropouts, varying time delays, and network communication efficiency in NCS. Researchers in the field of control systems, optimization, and fuzzy logic can utilize the code and literature from this project for their work. Additionally, MTech students and PHD scholars focusing on networked control systems can benefit from the innovative research methods, simulations, and data analysis techniques proposed in this project. The relevance of this project lies in its potential applications in enhancing the accuracy and speed of NCS, thereby improving control system performance in various industries and sectors.

The integration of PID controllers with fuzzy logic and optimization techniques opens up new avenues for research and development in the field of networked control systems. With future scope, the project can be extended to explore different optimization algorithms, testing them on larger and more complex NCS models. Moreover, the application of this project can be expanded to other related domains such as automation, robotics, and industrial control systems.

Algorithms Used

In this project, the Hybrid Grey Wolf Optimization-Whale Optimization Algorithm, Fuzzy System, and PID controllers are utilized to enhance the performance of a Networked Control System (NCS). The Hybrid GWO-WOA algorithm optimizes the mathematical transfer functions derived from the integration of PID and fuzzy logic controllers, improving the efficiency of the network system. The Fuzzy System helps in addressing issues such as broadcast delays, random variations, and packet dropouts, while the PID controllers monitor communication flow and ensure data transmission reliability. By combining these algorithms, the project aims to achieve better control strategy, reduced network delay, and overall improved performance of the NCS.

Keywords

NCS, networked control systems, fuzzy PID controllers, Grey Wolf optimization technique, Whale optimization technique, data communication network, network delays, packet dropouts, feedback control mechanism, fuzzy logic parameter, PID controller, network system, optimization techniques, mathematical transfer functions, network latency, communication protocols, real-time systems, network synchronization, control system design

SEO Tags

NCS, networked control systems, fuzzy PID controller, Grey Wolf optimization technique, Whale optimization technique, communication network, wireless network, wired network, feedback control mechanism, time delays in networks, packet dropouts, control loop, system accuracy, system speed, optimization techniques, fuzzy logic, PID controller, network system efficiency, broadcast delays, packet dropouts, controller performance, network delay adjustment, control strategy, fuzzy logic controller, mathematical transfer functions, hybrid controllers, Grey wolf optimization, whale optimization, network performance optimization, real-time systems, network synchronization, control system design.