Desired Speed Research Articles

Comparing the Effect of Age, Gender, and Desired Speed on Car-Following Behavior by Using Driving Simulator

In this study, the effect of age, gender, and desired speed (DS) factors on General Motors car-following (CF) behavior was investigated. DS was defined as the speed selected by the driver in free driving situation. A low-level driving simulator was used to collect data. The CF model for each driver was calibrated by genetic algorithm. Gender and DS were effective in CF behavior, while the age factor was not. The drivers’ sensitivity to the variables of speed and distance in the CF model increased with increasing the DS. The gender factor affected only the magnitude of deceleration which was higher in women. For further investigation, the effect of the desired speed on the time headway in the steady-state CF was also examined. DS factor was effective in steady-state CF behavior. As the DS increased, the time headway decreased. Examining CF threshold demonstrated that women maintained larger distance than men. Finally, it can be said that DS and gender would be more important than age to be considered in CF models.

Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions.

This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.

Comparison Method of PI, PID and Fuzzy Logic Controller to Maintain Speed Stability in Single Phase Induction Motors

Induction motor speed control is one of the operating conditions that is often used so that feedback with a low error rate is required. To fulfill this, PI and PID controls have been implemented for single phase induction motors. This control has parameters, namely Kp, Ki and Kd. PI and PID controls can cover a variety of desired response conditions, but these controls still have weaknesses in the tuning process. The tuning process used still has a fairly large error value. So in this case we need an intelligent control to meet the desired motor speed response specifications. The performance of motor speed regulation was evaluated using a comparison between PI and PID control with Fuzzy in a closed loop. With a setting point of 1500 rpm, for PI control, with Kp = 7.32 and Ki = 0.005 can produce motor speeds up to 1499. While PID control with Kp = 0.95, Ki = 0.005 and Kd = 0.04 can produce similar speeds. 1492. Fuzzy control can produce an output of 1490 rpm. Fuzzy control is able to produce a settling time of 0.25 seconds and a steady error of 0.67%.

Driving and steering collision avoidance system of autonomous vehicle with model predictive control based on non-convex optimization

A planar motion control system is proposed for autonomous vehicles not only to follow the lanes, but also to avoid collisions by braking, accelerating, and steering. The supervisor is designed first to determine the desired speed and the risk of the maneuvering due to road boundaries and obstacles. In order to allow lane changes on multi-lane roads, the model predictive controller is formulated based on the probabilistic non-convex optimization. The micro-genetic algorithm is applied to calculate the target speed and target steering angle in real time. A software-in-the-loop unit is constructed with the Rapid Control Prototyping device in the vehicle communication environment. The performance of the proposed system is verified for various collision avoidance scenarios and the simulation results demonstrate the safe and effective driving performance of autonomous vehicles with no collision on multi-lane road.

Kontrol Kecepatan Motor BLDC dengan PID - Firefly

Conventional DC motors often experience problems that require regular maintenance. The use of conventional DC motors can be replaced with Brushless DC (BLDC) motors. This BLDC motor has good efficiency and durability. Increasing the ability of BLDC motors can be done by speed regulation using the Proportional-Integral-Derivative (PID) method combined with Firefly Algorithm. Testing this method uses matlab 2014a. The firefly algorithm can obtain parameter values of Kp, Ki, and Kd which are then used as PID input. Because of inaccuracies in determining the value of a constant in PID and can cause the length of time to reach the desired speed. BLDC motor speed regulation with the PID method combined with firefly algorithm can make the BLDC motor reach synchronous faster

Feedback Linearization of Inertially Actuated Jumping Robots

Inertially Actuated Jumping Robots (IAJR) provide a promising new means of locomotion. The difficulty of IAJR is found in the hybrid nature of the ground contact/flying dynamics. Recent research studies in our Systems Lab have provided a family tree of inertially actuated locomotion systems. The proposed Tapping Robot is the most prompt member of this tree. In this paper, a feedback linearization controller is introduced to provide controllability given the 3-dimensional motion complexity. The research objective is to create a general controller that can regulate the locomotion of Inertially Actuated Jumping Robots. The expected results can specify a desired speed and/or jump height, and the controller ensures the desired values are achieved. The controller can achieve the greatest response for the Basketball Robot at a maximum jump height of 0.25 m, which is greater than the former performance with approximately 0.18 m. The design paradigm used on the Basketball Robot was extended to the Tapping Robot. The Tapping Robot achieved a stable average forward velocity of 0.0773 m/s in simulation and 0.157 m/s in experimental results, which is faster than the forward velocity of former robot, Pony III, with 0.045 m/s.

Pembuatan Prototipe Kursi Roda Inovatif Dengan Akses Suara Menggunakan Smartphone Berbasis Mikrokontroler ATMega 8A

This low power consumption microcontroller is able to execute instructions with a maximum speed of 16MIPS at a frequency of 16MHz and the ATmega8 is tested to work at a voltage between 4.5 - 5.5 V. Test results of motor drivers 1 and 2 working at a voltage of 4.99 prove that the driver circuit has worked according to its function, namely controlling the motor in 2 directions according to the input given. Motor speed can be controlled by adjusting the motor voltage, the higher the voltage, the faster the motor rotates. The voltage drop will slow down the motor to the desired speed, The sensor response if it encounters an obstacle in front of the wheelchair will stop 10 cm before hitting the object. Then the load test is added gradually from 0 to 451 grams. The wheelchair will appear to be starting to slow down at its maximum weight, making it less responsive to commands. After testing, it can be concluded that the tool works as desired, namely controlling the motion of the wheelchair with voice commands and it can be declared successful although there are still some weaknesses and shortcomings that must be improved.

Investigation of an additively manufactured pentamode material using non-contact vibration transmissibility measurements

Pentamodal (PM) metamaterials are one potential means to enable concepts from transformation acoustics in underwater applications because they can be designed to support anisotropic longitudinal wave motion over wide frequency bands while simultaneously being impedance matched to water [Su et al., J. Acoust. Soc. Am. 141(6), (2017)]. In three dimensions, PM materials can be fabricated using additive manufacturing (AM) to create elastic lattice structures whose microstructure can be tailored to produce the desired anisotropic sound speed and impedance in a target frequency band. This work presents measurements of the vibrational response of a PM block designed to display anisotropic stiffness. The sample measures approximately 100x100x85 mm and is constructed from titanium using direct metal laser sintering. Measurements were made on a sample mounted on an electro-dynamic shaker providing base excitation between 0.05 and 20i kHz. A scanning laser Doppler vibrometer measured out-of-plane surface velocity with normals both parallel and orthogonal to the excitation axis. The finite extent of the sample introduces geometric asymmetry associated with domain truncation, which is observable in the vibrational modes. Measurements were made for various sample orientations and compared to full-featuredfinite element models. Simulation-experiment comparisons and other findings will be presented and discussed. [Work supported by ONR.]

Trajectory Tracking with Input Constraint based on LMI Approach of a Nonholonomic Mobile Robot

Nonholonomic Mobile Robot (NMR) is a mode of transportation that is widely used in industry. To achieve flexibility in carrying out its duties, an adequate control system is needed in transportation arrangements so that it is used as an object of research. The problem that is taken in this study is about tracking control for several reference trajectories with input constraint.To solve this problem two controllers were designed, kinematics controller and dynamics controller. Kinematics controller is designed so that the additional speed converges to the desired speed by adjusting the gain value , , and . Dynamic controller is designed using performance to overcome the input constraint and the Lyapunoc inequality is soleved by Linear Matric Inequalities (LMI) so the gain state-feedback can be obtained. Simulation results show that the designed controller is capable of tracking according to the reference trajectory with input constraint given.

Highly sensitive non-enzymatic glucose sensor with copper oxide nanoparticle impregnated mesoporous silica

Cuprous oxide (Cu2O) nanoparticles at a loading of 33.5 wt.% were impregnated in amine-functionalized mesoporous silica (NH2-SBA-15) particles, by an in situ chemical reduction method. Subsequently, Cu2O-NH2-SBA-15 hybrid was used as a modifier of glassy carbon electrode (GCE) for making a non-enzymatic glucose sensor. The optimum composition of the modifier on the GCE surface (0.47 mg Cu in Cu2O-NH2-SBA-15/cm2 surface area of GCE) resulted in a wide linearity range (0.2–15 mM glucose) and a high sensitivity of 438.3 µAcm−2 mM−1, due to the high loading of Cu2O in NH2-SBA-15 host. Furthermore, glucose was detected both in normal range (5 mM) and in hypoglycaemic range (2 mM), selectively in presence of concentrations of interfering species typically found in the normal blood, such as sodium chloride (142 mM), potassium chloride (3.7 mM), urea (4.7 mM) and ascorbic acid (0.05 mM). The response time was also less than 5 s. Therefore, it achieved the desirable sensor characteristics, like linearity, sensitivity, selectivity, and speed of response. This better performance of the sensor is mainly attributed to a high electrocatalytic activity of Cu2O nanoparticles towards glucose.

Ellipse detection-based visual servo control for capturing upper-stage rocket body

The quantity of space debris in orbit around the Earth including separated rockets, malfunctioning satellites, and small particles is continuously increasing. One such type of space debris is the upper stage of the H-series rockets, which has a joint, called the Payload Adapter Fitting (PAF), where the satellite to be deployed is connected. Because the PAF is circular, it offers a natural and desirable target marker for detecting the rocket stage attitude and capture the stage using image processing. Traditional visual servo control based on a single elliptical image of a circular feature cannot determine the normal direction of the PAF and is unable to maintain the imaged ellipse inside the camera field of view as the motion in the optical axis direction may exceed the desired speed. To overcome these problems, a method of control gain switching in visual servo control based on two elliptical images of two circular features of the PAF is proposed, in which the convergence of the projected ellipse to a circle is prioritized, followed by forward motion to adjust the relative distance. A 1/10 scale PAF model and a six degrees-of-freedom robotic manipulator equipped with a camera on its end-effector were used to validate the proposed control method. The experimental results show that the convergence time for the proposed method is shorter than that without control gain switching.

Adaptive Physics-Based Non-Rigid Registration for Immersive Image-Guided Neuronavigation Systems.

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A new adaptive method that automatically removes mesh elements in the area of the resected tumor, thereby handling deformation in the presence of resection is presented. To improve the user experience, we also present a new way of using mixed reality with ultrasound, MRI, and CT.Materials and methods: This study focuses on 30 glioma surgeries performed at two different hospitals, many of which involved the resection of significant tumor volumes. An Adaptive Physics-Based Non-Rigid Registration method (A-PBNRR) registers preoperative and intraoperative MRI for each patient. The results are compared with three other readily available registration methods: a rigid registration implemented in 3D Slicer v4.4.0; a B-Spline non-rigid registration implemented in 3D Slicer v4.4.0; and PBNRR implemented in ITKv4.7.0, upon which A-PBNRR was based. Three measures were employed to facilitate a comprehensive evaluation of the registration accuracy: (i) visual assessment, (ii) a Hausdorff Distance-based metric, and (iii) a landmark-based approach using anatomical points identified by a neurosurgeon.Results: The A-PBNRR using multi-tissue mesh adaptation improved the accuracy of deformable registration by more than five times compared to rigid and traditional physics based non-rigid registration, and four times compared to B-Spline interpolation methods which are part of ITK and 3D Slicer. Performance analysis showed that A-PBNRR could be applied, on average, in <2 min, achieving desirable speed for use in a clinical setting.Conclusions: The A-PBNRR method performed significantly better than other readily available registration methods at modeling deformation in the presence of resection. Both the registration accuracy and performance proved sufficient to be of clinical value in the operating room. A-PBNRR, coupled with the mixed reality system, presents a powerful and affordable solution compared to current neuronavigation systems.

Novel velocity estimation for symmetric and asymmetric self-paced treadmill training

BackgroundSelf-paced treadmills (SPT) can provide an engaging setting for gait rehabilitation by responding directly to the user’s intent to modulate the external environment and internal effort. They also can improve gait analyses by allowing scientists and clinicians to directly measure the effect of an intervention on walking velocity. Unfortunately, many common SPT algorithms are not suitable for individuals with gait impairment because they are designed for symmetric gait patterns. When the user’s gait is asymmetric due to paresis or if it contains large accelerations, the performance is diminished. Creating and validating an SPT that is suitable for asymmetric gait will improve our ability to study rehabilitation interventions in populations with gait impairment. The objective of this study was to test and validate a novel self-paced treadmill on both symmetric and asymmetric gait patterns and evaluate differences in gait kinematics, kinetics, and muscle activity between fixed-speed and self-paced treadmill walking.MethodsWe collected motion capture, ground reaction force data, and muscle activity from 6 muscles in the dominant leg during walking from 8 unimpaired subjects. In the baseline condition, the subjects walked at 3 fixed-speeds normalized to their leg length as Froude numbers. We developed a novel kinematic method for increasing the accuracy of the user’s estimated walking velocity and compared our method against other published algorithms at each speed. Afterward, subjects walked on the SPT while matching their walking speed to a given target velocity using visual feedback of the treadmill speed. We evaluated the SPT by measuring steady-state error and the number of steps to reach the desired speed. We split the gait cycle into 7 phases and compared the kinematic, kinetic, and muscle activity between the fixed speed and self-paced mode in each phase. Then, we validated the performance of the SPT for asymmetric gait by having subjects walk on the SPT while wearing a locked-knee brace set to 0° on the non-dominant leg.ResultsOur SPT enabled controlled walking for both symmetric and asymmetric gait patterns. Starting from rest, subjects were able to control the SPT to reach the targeted speeds using visual feedback in 13–21 steps. With the locked knee brace, subjects controlled the treadmill with substantial step length and step velocity asymmetry. One subject was able to execute a step-to gait and halt the treadmill on heel-strikes with the braced leg. Our kinematic correction for step-length outperformed the competing algorithms by significantly reducing the velocity estimation error at the tested velocities. The joint kinematics, joint torques, and muscle activity were generally similar between fixed-speed and self-paced walking. Statistically significant differences were found in 5 of 63 tests for joint kinematics, 2 of 63 tests for joint torques, and 9 of 126 tests for muscle activity. The differences that were statistically significant were not found across all speeds and were generally small enough to be of limited clinical relevance.ConclusionsWe present a validated method for implementing a self-paced treadmill for asymmetric and symmetric gaits. As a result of the increased accuracy of our estimation algorithm, our SPT produced controlled walking without including a position feedback controller, thereby reducing the influence of the controller on measurements of the user’s true walking speed. Our method relies only on a kinematic correction to step length and step time which can support transfer to systems outside of the laboratory for symmetric and asymmetric gaits in clinical populations.

Multiclass Traffic Flow Dynamics: An Endogenous Model

Vehicles on roads can be distinguished, each defined by its own set of properties (e.g., fleet length and free-flow speed). The traffic states on roads can be attributed to the longitudinal heterogeneity in vehicles. Vehicles slower than prevailing vehicles are defined as moving bottlenecks. On a multilane road section with multiple vehicle types, slower vehicles create moving bottlenecks and induce overtaking by faster vehicles so as to maintain their higher desired speed. The influence of single-class moving bottlenecks has been studied in the past. However, the impacts of multiple classes of moving bottlenecks have not yet been fully explored. This paper categorizes vehicles into passenger cars, medium trucks, and heavy trucks. By defining medium trucks and heavy trucks as moving bottlenecks, we develop analytical formulas for the fundamental diagram on a multilane road section with heterogeneous moving bottlenecks. The formula confirms that the composition of traffic and the longest truck platoon length influence the fundamental diagram. We then conduct simulations using a first-order kinematic wave model in Lagrangian coordinates to validate the fundamental diagram developed with the analytical formula and obtain promising results. This study provides fundamental knowledge for multiclass traffic modeling and multilane traffic operations.

Fuzzy Logic Control System for Fuel Mixture Quality in Spark Ignition Engines.(Dept.M)

Spark ignition engine performance and exhaust emissions are strongly affected by the fuel/air ratio used. A considerable amount of investigations have been carried out by engine manufacturers to control engine performance and meet exhaust emission standards of governmental agencies by developing control systems for some operating variables such as ignition timing(IT), Fuel Air Ratio(FAR), and Exhaust Gas Recirculation (EGR) This paper presents a fuzzy control system that measures exhaust temperature and operates a needle valve on the engine earburetor jet that enables the fuel to air ratio lo oscillate about a desired value. A group of experiments have been carried out to obtain the relationship between fuel to air ratio or (ɸ), Exhaust temperature and exhaust emissions. A group of fuzzy logic rules which relate exhaust temperature, to the desired speed with the position of a needle valve actuated by a stepping motor are prop osed. A beneficial of fuzzy control method was that the rules determined the characteristics of control system are interpreted by the operator. Experimental and simulated results show that the prop osed fuzzy system improves the fuel/air mixture quality.

Effect of PID Controller on Direct Current Motor Speed Control Performance under Varying Load Torque Disturbance

The MATLAB/Simulink model of DC motor speed control with varying load torque disturbance has been studied. Simulation was initially conducted without a controller considering unit step input and the transient response time domain performance characteristics of the uncompensated system were found to be remarkable but the desired speed was not tracked. The response speed was found to reach 1.649 rad/sec, which was well above the reference speed (1.0 rad/sec) by 64.9%. The introduction of load torque at 4 seconds further increased the magnitude of the motor speed response from 1.649 rad/sec to 3.008 rad/sec, which is 82.4% increment. With 300 rad/sec reference speed, simulation was conducted without PID controller and the resulting response was 494.6 rad/sec which was 64.9% increment. Thereafter, a load torque from 0 to 10 Nm is introduced at 4 seconds into the DC motor control loop and the response showed that the magnitude of the response motor is increased to 508.2 rad/sec, whicj is undesirable. A Proportional integral derivative (PID) controller plus pre-filter was introduced to DC motor speed control loop to compensate for the performance of the system. The step response showed that with the PID plus pre-filter circuit, the desired motor speed was tracked with remarkable time domain performance characteristics. With the introduction of unit load torque at 4 seconds, the step response of the PID controlled DC motor speed changed and tracked the desired speed with just 1% (0.01) deviation. Simulations were further performed with PID controller by setting the reference speed at 300 rad/sec without and with load torque varied from 0 to 10 Nm introduced into the control loop. The response was the same as the desired motor speed but increased to 300.1 rad/sec which is just 0.03% increment from the desired speed. Generally, the simulation tests conducted showed that the designed real PID controller plus pre-filter actually provided better speed response performance for DC motor control by offering precise tracking and robustness under varying load torque disturbance.

Design and Implementation of Fuzzy PID Controller for Controlling the Speed of Robotic Vehicle System in MATLAB

In recent years, researchers have been developed robotic vehicles for different applications especially in agriculture system. This system consists of a Robotic Vehicle which directs through the area in the required path doing digging as it goes through the path. This paper includes the modeling, design and analytical results of fuzzy PID and PID controller for tracking the speed of the robotic vehicle. The proposed controller was employed to track the desired speed and tracks the direction of the robot vehicle. Ziegler Nicholas and Auto tune based PID algorithm have been used by some authors to find the tuning parameters of P, PI and PID Controllers for achieving the desired set point. The Conventional PID and fuzzy PID algorithms are modelled and simulated in the MATLAB environment using programming code and Simulink. Finally, the performance assessment is contrasted with standard controller PID and fuzzy PID. Fuzzy PID controller tracks the desired speed of robotic vehicle with accuracy in performance indices as compared to conventional PID controller, specified by the designer.

An Improved Intelligent Driver Model Considering the Information of Multiple Front and Rear Vehicles

This paper proposes an improved intelligent driver model (IDM) by considering the information of multiple front and rear vehicles to describe the car-following behaviour of CAVs (Connected and autonomous vehicles). The model involves the velocity and acceleration of multiple front and rear vehicles as well as the velocity difference and headway between the host vehicle and its surrounding vehicles. By introducing location-related parameters, the model quantitatively expresses the change in influence degree of a surrounding vehicle with its location to the host vehicle. To maximize traffic stability, we obtain the optimal value of the parameters in the model and the effect of specific time delays on the stability of traffic flow with numerical simulation. The results indicate that for a single vehicle control, the proposed model provides a much quicker and smoother acceleration and deceleration process to the desired speed than the IDM and multi-front IDM. And for fleet control, the proposed multi-front and rear IDM is superior to the other two models in decreasing the starting and braking time and increasing the stability of speed and acceleration. With effective car-following behaviour control, it is helpful to improve the operation efficiency of CAVs and enhance the stability of traffic flow. In addition to the car-following behaviour control, the model can be utilized for fleet control in the case of CAVs’ homogeneous flow. This model can also serve as an effective tool to simulate car-following behaviour, which is beneficial for road traffic management and infrastructure layout in connected environments.

Implementation and design non-linear controller for stand-alone generator

This article describes the implementation and design of a non-linear controller for a stand-alone generator which has a DC motor as a prime mover based on input-output feedback linearization (FL) technique. While in the grids-connected synchronous generator the attention is focused on the load angle as stability assessment, the speed and terminal voltage is the main effective state in stand-alone generators. Therefore, the FL robust control design method is utilized to truck the desired speed and terminal voltage. First, a non-linear mathematical model is derived for the synchronous generator with a dc motor as a prime mover then input-output FL is applied to this non-linear model to make it linear. The tracking control low of the linearized model is designed using a pole placement technique. For verifying the efficiency and performance of the system, several tests were conducted in the Matlab simulation with some experimental results. These results showed a high dynamic response to a large and fast load difference and zero steady-condition error.

Pseudo-Steady-State Reduced-Order-Model Approximation for Constant-Current Parameter Identification in Lithium-Ion Cells

The challenges of parameter identification for a lumped-parameter, physics-based model of a lithium-ion cell motivate a closed-form approximation that can be used inside an optimization routine. Present reduced-order models of the lithium-ion cell do not achieve the desired speed and fidelity for the parameter-identification application when applied to a constant-current test. This paper introduces a novel approximation to the cell internal and terminal-voltage dynamics that is specialized for constant-current applications and incorporates a model of solid and electrolyte diffusion, solid and electrolyte potential, and the kinetics of the solid–electrolyte interphase layer. The approximation leverages non-time-varying profiles for electrolyte-level quantities under a pseudo-steady-state assumption coupled with a nonlinear approximation to the lithium stoichiometry at the electrode surface. The proposed approximation achieves significantly improved speed and accuracy over a comparable reduced-order model simplified for constant current when evaluated against a full-order-model simulation using the true parameter values.