Nowadays, traffic congestion is a significant issue globally. The vehicle quantity has grown dramatically, while road and transportation infrastructure capacities have yet to expand proportionally to handle the additional traffic effectively. Road congestion and traffic-related pollution have increased, which is detrimental to society and public health. This paper proposes a novel reinforcement learning (RL)-based method to reduce traffic congestion. We have developed a sophisticated Deep Q-Network (DQN) and integrated it smoothly into our system. In this study, Our implemented DQL model reduced queue lengths by 49% and increased incentives for each lane by 9%. The results emphasize the effectiveness of our method in setting strong traffic reduction standards. This study shows that RL has excellent potential to improve both transport efficiency and sustainability in metropolitan areas. Moreover, utilizing RL can significantly improve the standards for reducing traffic and easing urban traffic congestion.

In this investigation, the adaptive fractional-order non-singular fixed-time terminal sliding mode (AFoFxNTSM) control for the uncertain dynamics of robotic manipulators with external disturbances is introduced. The idea of fractional-order non-singular fixed-time terminal sliding mode (FoFxNTSM) control is presented as the initial step. This approach, which combines the benefits of a fractional-order parameter with the advantages of NTSM, gives rapid fixed-time convergence, non-singularity, and chatter-free control inputs. After that, an adaptive control strategy is merged with the FoFxNTSM, and the resulting model is given the label AFoFxNTSM. This is done in order to account for the unknown dynamics of the system, which are caused by uncertainties and bounded external disturbances. The Lyapunov analysis reveals how stable the closed-loop system is over a fixed time. The pertinent simulation results are offered here for the purposes of evaluating and illustrating the performance of the suggested scheme applied on a PUMA 560 robot.

This paper presents a fault tolerant scheme employing adaptive non-singular fixed-time terminal sliding mode control (AFxNTSM) for the application of robotic manipulators under uncertainties, external disturbances, and actuator faults. To begin, non-singular fixed-time terminal sliding mode control (FxNTSM) is put forth. This control method uses non-singular terminal sliding mode control to quickly reach fixed-time convergence, accomplish satisfactory performance in tracking, and produce non-singular and non-chatter control inputs. Then, without knowing the upper bounds beforehand, AFxNTSM is used as a reliable fault tolerant control (FTC) to estimate actuator faults and unknown dynamics. The fixed-time stability of the closed-loop system is established by the theory of Lyapunov analysis. The computer simulation results of the position tracking, control inputs, and adaptive parameters are presented to verify and illustrate the performance of the proposed strategy.

This paper presents an adaptive fixed-time fractional integral control for externally disturbed Euler–Lagrange systems. In the first step of the control design, the approach of fractional-order fixed-time integral nonsingular terminal sliding mode control (FoIFxTSM) is introduced. This scheme combines the benefits of fractional calculus with integral sliding mode control, resulting in fast convergence, smooth nonsingular control inputs, and fixed-time stability. By integrating an adaptive scheme, the proposed method is used to control the dynamical system in the presence of uncertainty and external perturbations. The findings of the fixed-time stability using Lyapunov analyses are provided for the closed-loop system. The simulation results are compared with the adaptive fractional-order sliding mode control scheme, and they show the better tracking and convergence performance of the proposed method.

Purpose – The role of business process re-engineering (BPR) in implementing enterprise resource planning (ERP) systems is of paramount importance. A variety of approaches are used for such re-engineering as the best-fitting ERP solution can only give a maximum of 80 percent fit with the existing workflow of the organization in which ERP is being implemented. The aim of this paper is to focus on the issues involved. Design/methodology/approach – The paper presents some sample ERP installations to come out with various types of business BPR, ranging from small-r to big-R, practised while implementing ERP. Findings – Based on the literature review, it could be found that all organizations implementing ERP have chosen their own approach based on organizational constraints and the needs. The importance of BPR in ERP implementation is highlighted in earlier studies. Research limitations/implications – The recursive relationship between BPR and information technology has only resulted in the rapid evolution of ERP systems. ERP integration with supply chain management and its web readiness are major agenda for ERP developers. Many re-engineering possibilities are yet to evolve based on research in knowledge, artificial intelligence and expert database systems. A suitable approach to implement the same in an organization can only be done using the most suitable approach and hence the importance of the BPR approaches presented here along with their advantages and disadvantages. Practical implications – As the various BPR approaches are categorized based on implementation followed by major corporations, it is definitely a forerunner for any ERP-implementing organization under study. Also the common problems encountered during re-engineering for ERP implementation and the suggested remedial measures are presented based on earlier work. Originality/value – An attempt has been made to identify BPR problems, causes and approaches used in implementing ERP solutions. It is only aimed at synthesis of technical and general issues using the literature.

The results of this research provide fixed-time fractional-order control for Euler–Lagrange systems that are subject to external disturbances. The first step in the process of developing a new system involves the introduction of a method known as fractional-order fixed-time non-singular terminal sliding mode control (FoFtNTSM). The advantages of fractional-order calculus and NTSM are brought together in this system, which result in rapid convergence, fixed-time stability, and smooth control inputs. Lyapunov analysis reveals whether the closed-loop system is stable over the duration of the time period specified. The performance of the suggested method when applied to the dynamics of the Euler–Lagrange system is evaluated and demonstrated with the help of computer simulations.