Robust Adaptive Control of 3D Overhead Crane System

In this chapter an adaptive anti-sway controller for uncertain overhead cranes is proposed. The system model including the system uncertainties and disturbances is introduced firstly. Next, the adaptive controller which can guarantee tracking the desired position of the trolley as well as the anti-sway of the load cable is established. In this chapter, the system is proven to be input-to-state stable (ISS) which is supported by Lyapunov technique. The proposed algorithm is verified by using Matlab/Simulink simulation tool. The simulation results shown that the presented controller gives the good performances (i.e., fast transient response, position tracking, and low swing angle) when there exist system parameters variation as well as input disturbances

Fuzzy Controllers for a Gantry Crane System with Experimental Verifications

The control problem of gantry cranes has attracted the attention of many researchers because of the various applications of these cranes in the industry. In this paper we propose two fuzzy controllers to control the position of the cart of a gantry crane while suppressing the swing angle of the payload. Firstly, we propose a dual PD fuzzy controller where the parameters of each PD controller change as the cart moves toward its desired position, while maintaining a small swing angle of the payload. This controller uses two fuzzy subsystems. Then, we propose a fuzzy controller which is based on heuristics. The rules of this controller are obtained taking into account the knowledge of an experienced crane operator. This controller is unique in that it uses only one fuzzy system to achieve the control objective. The validity of the designed controllers is tested through extensive MATLAB simulations as well as experimental results on a laboratory gantry crane apparatus. The simulation results as well as the experimental results indicate that the proposed fuzzy controllers work well. Moreover, the simulation and the experimental results demonstrate the robustness of the proposed control schemes against output disturbances as well as against uncertainty in some of the parameters of the crane

Time Localization of Abrupt Changes in Cutting Process using Hilbert Huang Transform

Cutting process is extremely dynamical process influenced by different phenomena such as chip formation, dynamical responses and condition of machining system elements. Different phenomena in cutting zone have signatures in different frequency bands in signal acquired during process monitoring. The time localization of signal’s frequency content is very important. An emerging technique for simultaneous analysis of the signal in time and frequency domain that can be used for time localization of frequency is Hilbert Huang Transform (HHT). It is based on empirical mode decomposition (EMD) of the signal into intrinsic mode functions (IMFs) as simple oscillatory modes. IMFs obtained using EMD can be processed using Hilbert Transform and instantaneous frequency of the signal can be computed. This paper gives a methodology for time localization of cutting process stop during intermittent turning. Cutting process stop leads to abrupt changes in acquired signal correlated to certain frequency band. The frequency band related to abrupt changes is localized in time using HHT. The potentials and limitations of HHT application in machining process monitoring are shown

Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda

Autonomous mobile robots (AMR) are currently being introduced in many intralogistics operations, like manufacturing, warehousing, cross-docks, terminals, and hospitals. Their advanced hardware and control software allow autonomous operations in dynamic environments. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs can communicate and negotiate independently with other resources like machines and systems and thus decentralize the decision-making process. Decentralized decision-making allows the system to react dynamically to changes in the system state and environment. These developments have influenced the traditional methods and decision-making processes for planning and control. This study identifies and classifies research related to the planning and control of AMRs in intralogistics. We provide an extended literature review that highlights how AMR technological advances affect planning and control decisions. We contribute to the literature by introducing an AMR planning and control framework t

Development of the framework for a lean, energy efficient, and environmentally friendly port: umm qasr port as a Case Study

The research focus is to examine rigorously how the implementation of Lean within the Umm Qasr Port improves the operation processes and to explore the Lean impact on environment improvement and energy efficiency management. In this research, the ROPMEE model has been developed by the researcher to evaluate the service quality in the cargo delivery process in the Port of Umm Qasr as it covers all the functional and non-functional areas in the cargo delivery process compared to other quality dimensions. The findings confirm that the process quality dimension is the most influential factor in service quality in the Port of Umm Qasr. The reasons for the poor performance of current practices adopted by the port are the use of traditional ways of information flow and a decision-making process that requires more time and steps within the whole process. The lack of smooth process flow is a potential cause of bottlenecks within port operation that create serious problems not only for the customer but also for the port itself. In this research, a visual representation is created of how the current value stream map for different port processes has been established on the identification and elimination of non- value-added activity or “waste” involved in delivering services in Umm Qasr port for customers. A VSM tool was applied to visually map the cargo handling flow, ship entrance, ship maneuvering and cargo clearance to display the current and future states of processes in a way that highlights opportunities for improvement. Based on the defined and classified waste according to the seven deadly wastes of Lean, this research suggests a future value stream map for port processes. The impact of the identified wastes has been quantified in terms of cost, carbon dioxide emissions working time efficiency, and energy consumption cost. This research is the first attempt to develop a Lean port model for improving port processes, as there have been no previous studies aimed at providing a holistic framework for improving port performance, which can be used by other ports. Implementing the Lean approach requires a gradual shift in work culture by involving all port employees and customers in the continuous improvement process and changing the service delivery from a push to pull system

NASA Tech Briefs, August 2002

Topics include: a technology focus on computers, electronic components and systems, software, materials, mechanics, machinery/automation, manufacturing, physical sciences, information sciences, book and reports, and Motion control Tech Briefs

Holistic, data-driven, service and supply chain optimisation: linked optimisation.

The intensity of competition and technological advancements in the business environment has made companies collaborate and cooperate together as a means of survival. This creates a chain of companies and business components with unified business objectives. However, managing the decision-making process (like scheduling, ordering, delivering and allocating) at the various business components and maintaining a holistic objective is a huge business challenge, as these operations are complex and dynamic. This is because the overall chain of business processes is widely distributed across all the supply chain participants; therefore, no individual collaborator has a complete overview of the processes. Increasingly, such decisions are automated and are strongly supported by optimisation algorithms - manufacturing optimisation, B2B ordering, financial trading, transportation scheduling and allocation. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems like supply chains. It is well-known that decisions made at one point in supply chains can have significant consequences that ripple through linked production and transportation systems. Recently, global shocks to supply chains (COVID-19, climate change, blockage of the Suez Canal) have demonstrated the importance of these interdependencies, and the need to create supply chains that are more resilient and have significantly reduced impact on the environment. Such interacting decision-making systems need to be considered through an optimisation process. However, the interactions between such decision-making systems are not modelled. We therefore believe that modelling such interactions is an opportunity to provide computational extensions to current optimisation paradigms. This research study aims to develop a general framework for formulating and solving holistic, data-driven optimisation problems in service and supply chains. This research achieved this aim and contributes to scholarship by firstly considering the complexities of supply chain problems from a linked problem perspective. This leads to developing a formalism for characterising linked optimisation problems as a model for supply chains. Secondly, the research adopts a method for creating a linked optimisation problem benchmark by linking existing classical benchmark sets. This involves using a mix of classical optimisation problems, typically relating to supply chain decision problems, to describe different modes of linkages in linked optimisation problems. Thirdly, several techniques for linking supply chain fragmented data have been proposed in the literature to identify data relationships. Therefore, this thesis explores some of these techniques and combines them in specific ways to improve the data discovery process. Lastly, many state-of-the-art algorithms have been explored in the literature and these algorithms have been used to tackle problems relating to supply chain problems. This research therefore investigates the resilient state-of-the-art optimisation algorithms presented in the literature, and then designs suitable algorithmic approaches inspired by the existing algorithms and the nature of problem linkages to address different problem linkages in supply chains. Considering research findings and future perspectives, the study demonstrates the suitability of algorithms to different linked structures involving two sub-problems, which suggests further investigations on issues like the suitability of algorithms on more complex structures, benchmark methodologies, holistic goals and evaluation, processmining, game theory and dependency analysis