Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

Laptop cooling pad temperature monitoring system

Cooling pads are commonly used to reduce temperature of laptop to avoid overheating problem. However, existing cooling pads are prone to various limitations: fixed voltage in the hardware component, inaccurate temperature readings and lacked of computer-based temperature monitoring functions. In this paper, a laptop cooling system with multivoltage fan speed controller using real-time processor temperature readings is proposed. A graphical user interface (GUI) and color coded LEDs are also implemented to provide visual inspection of the temperature values captured from the laptop. The temperature values are displayed in graph and tabular form. The performance of the proposed cooling pad with computer-based monitoring application is evaluated against two other types of existing cooling pad systems. The experiments have shown that the temperature values can be monitored clearly with the proposed GUI. More importantly, the proposed cooling pad system has the potential to achieve lower temperature faster than the rest of the existing cooling pad systems

Comparison of LQR and PID Controller Tuning Using PSO for Coupled Tank System

Coupled Tank System is one of the widely used applications in industries. Like other process control, it require suitable controller to obtain the good system performances. Hence, this paper presents the study of Coupled Tank System using LQR and PID controller. Both controller parameters are tuned using Single-Objective Particle Swarm Optimization (PSO). The performance of the system is compared based on the transient response in term of of Rise Time (Tr), SettlingTime (Ts), Steady State Error (ess) and Overshoot (OS).Simulation is conducted within MATLAB environment to verify the performances of the system. The result shows that both controller can be tuned using PSO, while LQR controller give slightly better results compared to PID controller

A Deep Reinforcement Learning-Based Controller for Magnetorheological-Damped Vehicle Suspension

This paper proposes a novel approach to controller design for MR-damped vehicle suspension system. This approach is predicated on the premise that the optimal control strategy can be learned through real-world or simulated experiments utilizing a reinforcement learning algorithm with continuous states/actions. The sensor data is fed into a Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which generates the actuation voltage required for the MR damper. The resulting suspension space (displacement), sprung mass acceleration, and dynamic tire load are calculated using a quarter vehicle model incorporating the modified Bouc-Wen MR damper model. Deep RL's reward function is based on sprung mass acceleration. The proposed approach outperforms traditional suspension control strategies regarding ride comfort and stability, as demonstrated by multiple simulated experimentsComment: 19 pages , 9 figures , 5 table

Robust multi-objective design of suspension systems

This thesis presents a robust multi-objective optimal design of four-degree-of-freedom passive and semi-active suspension systems. The passive suspension system is used in a racing car and the semi-active suspension is implemented on a passenger car. Mathematical models of the commercial and racing vehicle suspension systems are used in the computer simulations. A robust multi-objective design of the suspension systems is carried out by considering the minimization of three objectives: passenger’s head acceleration (HA), suspension deflection (SD), and tire deflection (TD). The first objective is concerned with the passenger’s health and comfort. The suspension stroke is described by SD and the tire holding is characterized by TD. The optimal design of the passive suspension involves tuning the coefficients of the sprung spring and damper, tire stiffness, and inertance of the inerter. Suspension systems’ parametric variations are very common and cannot be avoided in practice. To this end, a robust multi-objective optimization method that takes into consideration small changes in the design parameters should be considered. Unlike traditional multi-objective optimization problems where the focus is placed on finding the global Pareto-optimal solutions which express the optimal trade-offs among design objectives, the robust multi-objective optimization algorithms are concerned with robust solutions that are less sensitive to perturbations of decision variables. As a result, the mean effective values of the fitness functions are used as design objectives. Constraints on the design parameters and goals are applied. Numerical simulations show that the robust multi-objective design (RMOD) is very effective and guarantees a robust behavior as compared to that of the classical multi-objective design (MOD). The results also show that the robust region is inside the feasible search space and avoids all of its boundaries. The decision parameter space of the semi-active suspension includes both passive and active components. The passive components include the stiffness of the sprung spring, damping coefficient of the shock absorber, and stiffness of the tire. The active elements are the design details of the LQR algorithm. During the design, global sensitivity analysis is conducted to determine the elements of the suspension system that have high impact on the design objectives. The mass of the passenger’s head and upper body, the mass of the passenger’s lower body and cushion, passenger and cushion’s elastic properties, and the sprung mass of the vehicle are selected for the sensitivity analysis. Results show that the design goals are more sensitive to the variations in the sprung mass than the other parameters. As a result, parametric variations in the sprung mass of the vehicle and passive elements of the suspension system are considered. Similar to the design of the passive suspension, the mean effective values of SD, TD, and HA are used as design objectives. Also, constraints are applied on the objectives in compliance with the requirements of ISO 2631-1 on the design of car suspension systems. The optimization problem is solved by the NSGA-II (non-dominated sorting genetic algorithm) and robust Pareto front and set are obtained

Study on Vibration Characteristics and Human Riding Comfort of a Special Equipment Cab

Special equipment drivers often suffered from vibration which threatened their physical and mental health. In order to study the riding comfort of a special equipment cab, a hammering experiment has been carried out on it by acceleration sensors. According to the test results, the natural frequency has been calculated which was compared with the result analysis by the finite element method. Next, the equipment operating condition test on a flat road was done. The vibration characteristics of the whole vehicle were obtained later. The results show that the cab vibration and the finite element results agree well, but the natural frequency of the cab is close to the vibration frequency of the human body. And this is not conducive to long-term operation of the drivers. In order to improve the human operational comfort, it is necessary to reduce its natural frequency during the cab structure design process. The research in this paper can provide help for the similar human-machine operation comfort study and product design

Invited Review: Recent developments in vibration control of building and bridge structures

This paper presents a state-of-the-art review of recent articles published on active, passive, semi-active and hybrid vibration control systems for structures under dynamic loadings primarily since 2013. Active control systems include active mass dampers, active tuned mass dampers, distributed mass dampers, and active tendon control. Passive systems include tuned mass dampers (TMD), particle TMD, tuned liquid particle damper, tuned liquid column damper (TLCD), eddy-current TMD, tuned mass generator, tuned-inerter dampers, magnetic negative stiffness device, resetting passive stiffness damper, re-entering shape memory alloy damper, viscous wall dampers, viscoelastic dampers, and friction dampers. Semi-active systems include tuned liquid damper with floating roof, resettable variable stiffness TMD, variable friction dampers, semi-active TMD, magnetorheological dampers, leverage-type stiffness controllable mass damper, semi-active friction tendon. Hybrid systems include shape memory alloys-liquid column damper, shape memory alloy-based damper, and TMD-high damping rubber

State of the art of control schemes for smart systems featuring magneto-rheological materials

This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials