Nonlinear linear dynamics and numerical analysis of a sloshing tank

Enforcement avoidance behavior near automated speed enforcement areas in Korean expressways

Speed is the one of the basic reasons for vehicle accident in India. To reducing the accidents the system is used that is `Accident Detection and Alert System'. This system alert when accident occurred and immediately contact to the emergency unit. Arduino UNO is processor of this system. It control the whole system. The input are Acceleration meter , Gyroscope, Vibration Sensor and output are LCD , Buzzer, GSM module, GPS module .When accident occurred their vibrations are detected by vibration sensor and accelerometer detects sudden changes in speed that may indicate an accident or crash. Gyroscope monitors changes in orientation or rotation of the vehicle, which can be useful for detecting rollovers or sudden swerving. GPS module provides real-time location data, which is useful for sending SMS of accident locations to emergency unit. GSM module get accident location and data send it to emergency unit. And Buzzer get ON and LCD display danger message

When a permanent-magnet synchronous motor is driven by an electric tractor, potholes, sudden changes in speed and motor temperature rise may occur during transportation and plow operations. These factors may cause the motor operation and control parameters to change. The traditional maximum torque per ampere (MTPA) trajectory is based on the control parameters of the motor and the trajectory cannot be changed as the motor parameters change. However, the actual operation of the drive motor MTPA trajectory will change, which led to control deviation. This paper presents a torque current ratio limit tracking method, the torque in real time to consume the minimum current vector, MTPA trajectory closer to the actual operation of the motor drive MTPA curve, to obtain better maximum torque current ratio trajectory, the motor has More anti-interference. Through Simulink simulation and experimental verification, the improved MTPA algorithm can make the motor run more stable and can adapt to the harsh working environment of the driving motor.

This paper shows the differences that different models can have in the calculation of emissions from mobile sources. Mobile source emission models are designed to provide a quantification tool of the amount of pollution that is released to the atmosphere from the vehicles within a defined region. The most common models were developed based on aggregated data, such as vehicle miles traveled, fuel consumption and average traveling speed. Recently, new models have been developed. The models use a disaggregated analysis approach in order to include the sudden changes in speed and acceleration and the traffic interactions in the calculation. This paper presents a comparison between three different models developed on three different levels of data aggregation and their application on a road stretch. Traffic data (speed, acceleration and flow) is extracted from a micro simulation model and then used to calculate the total emissions during a specific period of time. Emission data was collected using a Portable Vehicular Emission Measuring System in a chassis dynamometer on a second by second basis. The main purpose of this research is to show the main differences in the calculation of emissions and their applicability to different levels of emission inventories.

Problem statement: The main objective of this research is to obtain the speed control of switched reluctance motor with minimum settling time and without overshoot. Approach: A new algorithm has been developed with the combination of differential evolution and particle swarm optimization and applied for speed control of switched reluctance motor under sudden change in speed. Also speed control of switched reluctance motor was obtained by other artificial intelligence methods such as fuzzy logic controller, fuzzy PI controller and particle swarm optimization based tuning of fuzzy PI controller. Matlab/Simulink environment was used for the simulation. Results: Results are discussed and tabulated based on the performance of the controllers. Conclusion: From the comparison of all above methods, the algorithm has given better results in speed response than other controllers.

In this research study, direct torque and flux control of an Induction Motor Drive (IMD) using Sliding-Mode Speed Controllers (SMSC) and Fuzzy-Logic Speed Controller (FLSC) are presented to achieve high performance of stator current, electromagnetic torque and motor speed in both transient as well as in steady-state conditions. The PI Speed Controller (PISC) gives good steady-state performance, but poor dynamic response. Therefore, the SMSC is considered to achieve continuous control of motor speed and also electromagnetic torque. Furthermore, FLSC is considered to get high performance, dynamic tracking and speed accuracy at various load torque conditions. The performances of each speed controller techniques are tested under various load toque and speed condition for its robustness. A detailed comparison of different control approaches are carried out in a MATALB/Simulink environment at different operating conditions, such as forward and reversal motoring with no-load, load, sudden change in speed and sudden zero speed.

Abnormal ship navigation behaviors in cross-sea bridge waters pose significant threats to maritime safety, creating a critical need for accurate anomaly detection methods. Ship AIS trajectory data contain complex temporal features but often lack explicit labels. Most existing anomaly detection methods heavily rely on labeled or semi-supervised data, thus limiting their applicability in scenarios involving completely unlabeled ship trajectory data. Furthermore, these methods struggle to capture long-term temporal dependencies inherent in trajectory data. To address these limitations, this study proposes an unsupervised trajectory anomaly detection model combining a transformer architecture with a variational autoencoder (transformer–VAE). By training on large volumes of unlabeled normal trajectory data, the transformer–VAE employs a multi-head self-attention mechanism to model both local and global temporal relationships within the latent feature space. This approach significantly enhances the model’s ability to learn and reconstruct normal trajectory patterns, with reconstruction errors serving as the criterion for anomaly detection. Experimental results show that the transformer–VAE outperforms conventional VAE and LSTM–VAE in reconstruction accuracy and achieves better detection balance and robustness compared to LSTM–-VAE and transformer–GAN in anomaly detection. The model effectively identifies abnormal behaviors such as sudden changes in speed, heading, and trajectory deviation under fully unsupervised conditions. Preliminary experiments using the POT method validate the feasibility of dynamic thresholding, enhancing the model’s adaptability in complex maritime environments. Overall, the proposed approach enables early identification and proactive warning of potential risks, contributing to improved maritime traffic safety.

<div class="htmlview paragraph">An integrated transient engine simulation methodology has been developed to allow the calculation of a thermal shock as it propagates in time through the engine structure. It links, in a fully consistent way, a very comprehensive thermodynamic model of in-cylinder processes, including a detailed gas-phase heat transfer representation, with a turbocharger/air flow/plenum model and a finite element model of the structure. The methodology tracks the turbocharger boost increase and the cycle-by-cycle build-up of in-cylinder heat transfer during engine load and speed changes, producing a transient thermal response in the structure, until new steady-state is reached. The presented results highlight the calculated transient engine performance response and the thermal and stress response of various metal and ceramic components during sudden speed and load changes in heavy duty diesel engines.</div>

In order to improve the tracking accuracy and safety of the cushion robot, this paper proposes a reinforcement learning control method with a safe motion velocity, aiming to suppress the impact of disturbances from human activities and sudden speed changes on the system's tracking performance. Based on considering disturbances from human activities, a dynamic model of the cushion robot is established, and a reinforcement learning controller design method is proposed. Furthermore, a control barrier function is constructed using velocity constraints, and quadratic programming is used to solve the reinforcement learning controller, resulting in a safe motion velocity tracking controller. Finally, the proposed control method is validated through simulation analysis, demonstrating the stability of the tracking error system. The results indicate that the proposed control method can suppress disturbances from human activities and enable individuals with disabilities to complete tracking tasks at safe speeds.

IntroductionFor patients with functional motor disorders of the lower limbs due to brain damage or accidental injury, restoring the ability to stand and walk plays an important role in clinical rehabilitation. Lower limb exoskeleton robots generally require patients to convert themselves to a standing position for use, while being a wearable device with limited movement distance.MethodsThis paper proposes a reconfigurable behavioral assistive robot that integrates the functions of an exoskeleton robot and an assistive standing wheelchair through a novel mechanism. The new mechanism is based on a four-bar linkage, and through simple and stable conformal transformations, the robot can switch between exoskeleton state, sit-to-stand support state, and wheelchair state. This enables the robot to achieve the functions of assisted walking, assisted standing up, supported standing and wheelchair mobility, respectively, thereby meeting the daily activity needs of sit-to-stand transitions and gait training. The configuration transformation module controls seamless switching between different configurations through an industrial computer. Experimental protocols have been developed for wearable testing of robotic prototypes not only for healthy subjects but also for simulated hemiplegic patients.ResultsThe experimental results indicate that the gait tracking effect during robot-assisted walking is satisfactory, and there are no sudden speed changes during the assisted standing up process, providing smooth support to the wearer. Meanwhile, the activation of the main force-generating muscles of the legs and the plantar pressure decreases significantly in healthy subjects and simulated hemiplegic patients wearing the robot for assisted walking and assisted standing-up compared to the situation when the robot is not worn.DiscussionThese experimental findings demonstrate that the reconfigurable behavioral assistive robot prototype of this study is effective, reducing the muscular burden on the wearer during walking and standing up, and provide effective support for the subject's body. The experimental results objectively and comprehensively showcase the effectiveness and potential of the reconfigurable behavioral assistive robot in the realms of behavioral assistance and rehabilitation training.

The temperature control performance of a developed temperature feedback control system was experimentally investigated. The control system was based on a real-time temperature control of a cooling fluid. In particular, this study focused on the temperature control performance of a built-in motor spindle that used the developed temperature fedback control system. The built-in motor used in the study had water cooling jackets. The temperature of the built-in motor spindle was measured and feedback into the developed temperature feedback control system. Temperature control accuracy of the built-in motor spindle under steady state was then assessed. Furthermore, the effects of the time-variant changes in spindle rotation and ambient temperature on the performance of the temperature control system was investigated. The results of the experiments show that the temperature control accuracy of the built-in motor spindle under steady state condition was ±0.03°C. The temperature control performance of the built-in motor spindle under changes in the rotational speed of the spindle was examined. The experimental results show that the temperature change of the spindle could be suppressed to a maximum of approximately 0.3°C under transient state during sudden change in spindle speed. In addition, the effects of the changes in ambient and cooling water temperatures, which simulated actual environmental operating conditions, on the spindle temperature were investigated. The results show that the change in the spindle temperature could be suppressed by approximately less than ±0.1°C. These experimental results indicate that the developed temperature feedback control system achieved high temperature control accuracy and high response for the built-in motor spindle. In particular, the developed control system successfully controlled the time-variant change in the generated heat, thereby improving the thermal stability of the machine tool spindle.

This paper describes a simple but powerful and robust fuzzy tuning procedure for on-line adapting the scaling factors of a fuzzy logic controller (FLC) for the high performance drives induction motor (IM). This fuzzy adaptation does not require the knowledge of the system model. The improvements and the performances of the proposed controller based on IM drive are investigated and illustrated by some simulation results at different dynamic operating conditions such as sudden change in command speed, step change in load and some key parameters deviation. The suggested controller can be applied to a large class of robotic and other mechanical systems.

Hysteretic dynamics inducing coexistence of attractors in a thin magnetostrictive actuator system with quintic nonlinearity

This paper investigates the nonlinear dynamics of a flexible tyre coupling via computer modelling and simulation. The research mainly focused on identifying basins of attraction of coexisting solutions of the formulated phenomenological coupling model. On the basis of the derived mathematical model, and by assuming ranges of variability of the control parameters, the areas in which chaotic clutch movement takes place are determined. To identify multiple solutions, a new diagram of solutions (DS) was used, illustrating the number of coexisting solutions and their periodicity. The DS diagram was drawn based on the fixed points of the Poincaré section. To verify the proposed method of identifying periodic solutions, the graphic image of the DS was compared to the three-dimensional distribution of the largest Lyapunov exponent and the bifurcation diagram. For selected values of the control parameter ω, coexisting periodic solutions were identified, and basins of attraction were plotted. Basins of attraction were determined in relation to examples of coexistence of periodic solutions and transient chaos. Areas of initial conditions that correspond to the phenomenon of unstable chaos are mixed with the conditions of a stable periodic solution, to which the transient chaos is attracted. In the graphic images of the basins of attraction, the areas corresponding to the transient and periodic chaos are blurred.

We investigate the nature of Allee thresholds and basins of attraction in a predation model with double Allee effect in the prey and a competition behaviour in the predator. From a mathematical perspective, this implies to find and characterise the corresponding basin boundaries in phase space. This is typically a major challenge since the objects that act as boundaries between 2 different basins are invariant manifolds of the system, which may also undergo topological changes at bifurcations. For this goal, we make an extensive use of analytical tools from dynamical systems theory and numerical bifurcation analysis and determine the full bifurcation diagram. Local bifurcations include saddle‐node, transcritical and Hopf bifurcations, while global phenomena include homoclinic bifurcations, heteroclinic connections, and heteroclinic cycles. We identify the Allee threshold to be either a limit cycle, a homoclinic orbit, or the stable manifold of an equilibrium. This strategy based on bifurcation and invariant manifold analysis allows us to identify the mathematical mechanisms that produce rearrangements of separatrices in phase space. In this way, we give a full geometrical explanation of how the Allee threshold and basins of attraction undergo critical transitions. This approach is complemented with a study of the dynamics near infinity. In this way, we determine the conditions such that the basins of attraction are bounded or unbounded sets in phase space. All in all, these results allow us to show a complete description of phase portraits, extinction thresholds, and basins of attraction of our model under variation of parameters.