Fractional Order PID Controller for Tracking Control of SCARA Robot

Fractional Order PID Controller for Tracking Control of SCARA Robot

Sreejita Samadder, Samriddhi Dave, Vijay Mohan, Bharat Bhushan Sharma
DOI: 10.4018/978-1-6684-4969-1.ch014
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Abstract

E-commerce packaging has unique needs, and new robot technology is meeting those needs. These needs include handling mixed pallet loads, workforce problems, and a range of secondary packaging types. This chapter presents the trajectory tracking control of an industrial SCARA robot in a realistic simulated environment with the help of fractional order PID (FOPID) and PID controller. FOPID controller has two extra degrees of freedom, thereby providing added flexibility to the design over the PID scheme. The optimum parameters of these controllers are obtained using the genetic algorithm (GA) by minimizing a weighted sum of absolute errors as an objective. Further, a comparative study of the controllers is performed for set-point tracking and model parameter uncertainty based on settling time, rise time, overshoot, and integral absolute error (IAE). The results have proved that FOPID outperforms its integer-order counterpart under a variety of operating conditions.
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Introduction

Advanced information technology and artificial intelligence have enabled automation-based companies to bring about seismic shifts in the way that they handle day-to-day operations during the past few decades. Smart manufacturing and smart factories are at the vanguard of a new industrial revolution, which is currently in progress. The development of new developing technologies, such as industrial robots built to function in hazardous situations, is underway in order to address the needs of consumers in the future smart industrial sector. By utilising these technologies, manufacturers can achieve more flexible manufacturing while also decreasing human requirements and accelerating the development process. Industrial robots can be configured to perform a variety of tasks. Robots are able to optimise output and increase productivity in smart industrial environments because of their agility and flexibility.

A more flexible control strategy and a more calculative grasp over manipulators were required by the expansion of the automation sector, which were met by current control strategies and intelligent algorithms (Chhabra et al., 2020; Mohan et al., 2019). With recent technological advancements and the introduction of computers, businesses are shifting toward automation. Automation is the process of completing a task with more accuracy and precision by employing computer software or robotics. Warehouse automation is essential in this day and age, as delays in delivery enrage clients in the e-commerce industry. Automation has made its way into this industry and is transforming the way businesses manage their fulfilment processes. Currently, robots are working in collaboration with people, and in certain cases, they are functioning independently. The logistics trends in e-commerce are changing at a breakneck speed. Companies are increasingly seeking for alternative methods of ensuring timely delivery to clients in order to drive commercial success. The current trend in logistics operations is therefore toward automation rather than human labour as companies attempt to keep up with demand from the rapidly rising e-commerce market. Amazon has emerged as the modernizer among the key competitors in the e-commerce market, having embraced robotic technologies in its fulfilment centres. Amazon was a pioneer in the use of robots in fulfilment facilities, and it continues to be so today. Amazon began using 1,300 robots in 2011 and has since increased this number. Amazon was enthusiastic about the prospect of employing robots in its warehouse. Amazon's warehouses currently have 15,000 robots scattered across ten different locations.

One can easily envision robots taking over for people in numerous areas when it comes to performing simple repetitive activities. In five years, a robot will be less expensive than a full-time human employee, including perks and compensation. The entire concept of automation is around ensuring that customers are satisfied. While robots and automation may limit employment possibilities and may result in inaccuracies in delivery, they will be critical in improving the efficiency of the supply chain as well as the overall economy. Automation is the ideal solution for the dynamic and complicated difficulties that manufacturers, contract logistics providers, and distributors are faced with every day. Industry automation enables them to manufacture more things with higher quality and precision in a shorter period of time. Automation also lowers labour costs (Chen et al., 2021; Zheng et al., 2018).

Key Terms in this Chapter

Manipulators: It is a device that allows the operator to handle materials without having to make direct physical touch with them.

Genetic Algorithm: A natural selection-based strategy for addressing both constrained and unconstrained optimization problems, which is based on the process that drives biological evolution, is used to solve this type of problem.

Links: Essentially, it is a resisting body that is a component of the machine, linking other components that are in motion in relation to it.

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