Comparison of UGV Position Estimation Equipped With GNSS-RTK and GPS Using EKF

Site assessments for bifacial Photovoltaic (PV) installation are quite challenging to conduct manually due to the area size and the extreme temperature conditions at desert sites. We designed and built an autonomous Unmanned Ground Vehicle (UGV) fitted with a Global Navigation Satellite Network-System Real-Time Kinematic (GNSS-RTK) positioning device, an Inertial Measurement Unit (IMU), encoder to improve and aid site assessments in desert condition. Sandy terrains deserts are challenging for UGV’s because they increase the likelihood of wheel slippage due to reduced traction. Sensor details such as IMU, GNSS-RTK, and encoder should be taken into consideration to account for the errors that the desert terrains pose. This study compared the Extended Kalman Filter (EKF) for standard GPS & GNSS-RTK to verify which performs better for the UGV’s position estimation. The estimated UGV’s position from the kinematics model and EKF are validated using a drone camera system that uses an image processing technique to verify the UGV’s position with the help of the visible reference cones. Throughout the experiments, the GNSS-RTK performed better than GPS. Also, the EKF performed as well as the GNSS-RTK by trusting it more than the encoder/gyroscope reading.

Data-Driven Methods for Detecting Traffic Jams in Vehicular Traffic Systems

Ground vehicle traffic jams are a serious issue in today’s society. Despite advances in traffic flow management in recent years, predicting traffic jams is still a challenge. Recently, novel techniques have been developed in complex systems theory to enable forecasting emergent behaviors in dynamical systems. Forecasting methods have been developed based on exploiting the phenomenon of critical slowing down, which occurs in dynamical systems near certain types of bifurcations and phase transitions. Herein, we explore recently developed tools of tipping point forecasting in complex systems, namely early warning indicators and bifurcation forecasting methods, and investigate their application to predict traffic jams on roads. The measurements required for forecasting are recorded dynamical features of the system such as headways between cars in traffic or density of cars on road. Forecasting approaches are applied to simulated and experimental traffic flow conditions. Results show that one can successfully predict proximity to the critical point of congestion as well as traffic dynamics after this critical point using the proposed approaches. The methodologies presented can be used to analyze stability of traffic models and address challenges related to the complexity of traffic dynamics.

Transient Vibration and Feedback Control of an Inductrack Maglev System

As a new strategy for magnetic levitation envisioned in 1990s, the Inductrack system with permanent magnets (PMs) aligned in Halbach arrays has been intensively studied and applied in many projects. Due to the nonlinear, time-varying electro-magneto-mechanical coupling in such a system, the dynamic behaviors are complicated with transient responses, which in most cases can hardly be predicted with fidelity by a steady-state Inductrack model. Presented in this paper is a benchmark 2-DOF transient Inductrack model, which is derived from the first laws of nature, without any assumed steady-state quantities. It is shown that the dynamic response of the Inductrack dynamic system is governed by a set of nonlinear integro-differential equations. As demonstrated in numerical simulations with the transient model, unstable vibrations in the levitation direction occur when the traveling speed of the vehicle exceeds a threshold. To resolve this instability issue, feedback control is implemented in the Inductrack system. In the development, an assembly of Halbach arrays and active coils that are wound on the PMs is proposed to achieve a controllable source magnetic field. In this preliminary investigation, the proposed control system design process takes two main steps. First, a PID controller is set and tuned based on a simple lumped-mass dynamic system. Second, the nonlinear force-current correlation is obtained from a lookup table that is pre-calculated by steady-state truncation of the full transient Inductrack model. With the implemented feedback control algorithms, numerical examples display that the motion of the vehicle in levitation direction can be effectively stabilized at different traveling speeds. Although only a 2-DOF transient model is used here, the modeling technique and the controller design approach developed in this work are potentially applicable to more complicated models of Inductrack Maglev systems.

Periodic Motions in an Autonomous System With a Discontinuous Vector Field

In this paper, periodic motions in an autonomous system with a discontinuous vector field are discussed. The periodic motions are obtained by constructing a set of algebraic equations based on motion mapping structures. The stability of periodic motions is investigated through eigenvalue analysis. The grazing bifurcations are presented by varying the spring stiffness. Once the grazing bifurcation occurs, periodic motions switches from the old motion to a new one. Numerical simulations are conducted for motion illustrations. The parameter study helps one understand autonomous discontinuous dynamical systems.

Circular Plates Under Hard Excitations to Include Casimir Effect: Amplitude-Voltage Response of Superharmonic Resonance of Second Order

This paper deals with voltage-amplitude response of superharmonic resonance of second order of electrostatically actuated clamped MEMS circular plates. A flexible MEMS circular plate, parallel to a ground plate, and under AC voltage, constitute the structure under consideration. Hard excitations due to voltage large enough and AC frequency near one fourth of the natural frequency of the MEMS plate resonator lead the MEMS plate into superharmonic resonance of second order. These excitations produce resonance away from the primary resonance zone. No DC component is included in the voltage applied. The equation of motion of the MEMS plate is solved using two modes of vibration reduced order model (ROM), that is then solved through a continuation and bifurcation analysis using the software package AUTO 07P. This predicts the voltage-amplitude response of the electrostatically actuated MEMS plate. Also, a numerical integration of the system of differential equations using Matlab is used to produce time responses of the system. A typical MEMS silicon circular plate resonator is used to conduct numerical simulations. For this resonator the quantum dynamics effects such as Casimir effect are considered. Also, the Method of Multiple Scales (MMS) is used in this work. All methods show agreement for dimensionless voltage values less than 6. The amplitude increases with the increase of voltage, except around the dimensionless voltage value of 4, where the resonance shows two saddle-node bifurcations and a peak amplitude significantly larger than the amplitudes before and after the dimensionless voltage of 4. A light softening effect is present. The pull-in dimensionless voltage is found to be around 16. The effects of damping and frequency on the voltage response are reported. As the damping increases, the peak amplitude decreases. while the pull-in voltage is not affected. As the frequency increases, the peak amplitude is shifted to lower values and lower voltage values. However, the pull-in voltage and the behavior for large voltage values are not affected.

Forming Canonical 8D Data Clouds to Explore the Transient Dynamics of Physical Stiffened Plates: A Machine Learning Approach for Complex Mechanical Structures

This work presents a data-driven explorative study of the physics of the dynamics of a physical structure of complicated geometry. The geometric complexity of the physical system renders the typical single sensor acceleration signal quite complicated for a physics interpretation. We need the spatial dimension to resolve the single sensory signal over its entire time horizon. Thus we are introducing the spatial dimension by the canonical eight-dimensional data cloud (Canonical 8D-Data Cloud) concept to build methods to explore the impact-induced free dynamics of physical complex mechanical structures. The complex structure in this study is a large scale aluminum alloy plate stiffened by a frame made of T-section beams. The Canonical 8D-Data Cloud is identified with the simultaneous acceleration measurements by eight piezoelectric sensors equally spaced and attached on the periphery of a circular material curve drawn on the uniform surface of the stiffened plate. The Data Cloud approach leads to a systematic exploration-discovery-quantification of uncertainty in this physical complex structure. It is found that considerable uncertainty is stemming from the sensitivity of transient dynamics on the parameters of space-time localized force pulses, the latter being used as a means to diagnose the presence of structural anomalies. The Data Cloud approach leads to aspects of machine learning such as reduced dynamics analytics of big sensory data by means of heavenly machine-assisted computations to carry out the unparalleled data reduction analysis enabled by the Advanced Proper Orthogonal Decomposition Transform. Emphasized is the connection between the characteristic geometric features of high-dimensional datasets as a whole, the Data Cloud, and the modal physics of the dynamics.

Vibration-Based Early Crack Diagnosis With Machine Learning for Spur Gears

Gear mechanisms are one of the most significant components of the power transmission systems. Due to increasing emphasis on the high-speed, longer working life, high torques, etc. cracks may be observed on the gear surface. Recently, Machine Learning (ML) algorithms have started to be used frequently in fault diagnosis with developing technology. The aim of this study is to determine the gear root crack and its degree with vibration-based diagnostics approach using ML algorithms. To perform early crack detection, the single tooth stiffness and the mesh stiffness calculated via ANSYS for both healthy and faulty (25-50-75-100%) teeth. The calculated data transferred to the 6-DOF dynamic model of a one-stage gearbox, and vibration responses was collected. The data gathered for healthy and faulty cases were evaluated for the feature extraction with five statistical indicators. Besides, white Gaussian noise was added to the data obtained from the 6-DOF model, and it was aimed at early fault diagnosis and condition monitoring with ML algorithms. In this study, the gear root crack and its degree analyzed for both healthy and four different crack sizes (25%-50%-75%-100%) for the gear crack detection. Thereby, a method was presented for early fault diagnosis without the need for a big experimental dataset. The proposed vibration-based approach can eliminate the high test rig construction costs and can potentially be used for the evaluation of different working conditions and gear design parameters. Therefore, catastrophic failures can be prevented, and maintenance costs can be optimized by early crack detection.

Smooth Time-Optimal Path Tracking for Robot Manipulators With Kinematic Constraints

Previous works solve the time-optimal path tracking problems considering piece-wise constant parametrization for the control input, which may lead to the discontinuous control trajectory. In this paper, a practical smooth minimum time trajectory planning approach for robot manipulators is proposed, which considers complete kinematic constraints including velocity, acceleration and jerk limits. The main contribution of this paper is that the control input is represented as the square root of a polynomial function, which reformulates the velocity and acceleration constraints into linear form and transforms the jerk constraints into the difference of convex form so that the time-optimal problem can be solved through sequential convex programming (SCP). The numerical results of a real 7-DoF manipulator show that the proposed approach can obtain very smooth velocity, acceleration and jerk trajectories with high computation efficiency.

Energy Resource for a RFID System Based on Dynamic Features of Reddy-Levinson Beam

Understanding the effect of design parameters on resonant frequency variation is a critically important aspect of piezoelectric energy harvester device design. As a first step in more accurately investigating the performance of a fixture designed for targeted RFID tag communication that also utilizes an energy harvesting application, this paper analyzes the variations in resonant frequency of a higher-order beam based on Reddy-Levinson theory (RLBT) under rotation effects. A long-term goal of this research is to implement an effective energy harvester on the RFID system. Part of the experimental RFID test fixture can be modeled as a beam (or beam element); thus, understanding the resonance frequency variations due to shear deformation and rotation effects is an important first step in obtaining information about the efficacy of the fixture in serving as an energy harvester. Investigating the performance of a beam also provides valuable information about the maximum power, frequency bandwidth, and tuning ability of the device that can be expected from an analogous energy harvester. For the first time, the resonant frequency variation of a rotating thick beam is investigated. Specifically, RLBT is used to verify the effects of shear deformation upon resonant frequency, and a coupled displacement field is utilized to enable tuning the potential piezoelectric energy harvester to low-input excitations by means of constraining translational and rotational movements of the system based on a linear constraint equation. Navier’s method as an analytical-numerical method is adopted to discretize the continuous system and to find resonant frequencies, respectively. Results reveal the significance of beam thickness and rotation effects of the proposed model for the purpose of minimizing energy usage. Current results are compared and verified numerically with available benchmarks to confirm a satisfactory level of accuracy. The proposed model, which is based on a coupled displacement field, can also be used to design other piezoelectric electro-mechanical-systems; e.g., vibration isolators, and vibration controllers. In other words, in an energy-scavenging system, a fundamental understanding of parameters affecting the resonant frequency can be accomplished through the presented analysis. The proposed model highlights the fact that, by adopting a proper speed factor, tuning the piezoelectric energy harvester to low-input excitations is possible. Additionally, it is observed that the rotation effect on the resonant frequency is more severe than effects of slenderness ratio. Finally, in this paper an improved model is proposed to capture the shear deformation effect, particularly for thick-beam energy harvesters, with the capability of tuning to low-input excitations.

A New Dynamic Model of a Two-Wheeled Two-Flexible-Beam Inverted Pendulum Robot

Inverted pendulums are traditional dynamic problems. If an inverted pendulum is used in a moving cart, a new type of exciting issues will appear. One of these problems is two-wheeled inverted pendulum systems. Because of their small size, high performance in quick driving, and their stability with controller, researchers and engineers are interested in them. In this paper, a new configuration of one specific robot is modeled, and its dynamic behavior is analyzed. The proposed model can move in two directions, and with a proper controller can keep its stability during the operation. In this robot, two cantilever beams are on the two-wheeled base, and they are excited by voltages to the attached piezoelectric actuators. The mathematical model of this system is obtained using the extended Hamilton’s Principle. The results show that the governing equations of motion are highly nonlinear and contain several coupled partial differential equations (PDEs). In order to extract the natural modes of the beams, the undamped, unforced equations of motion and boundary conditions of the beams are used. If a limited number of modes (N1 and N2) are selected for each beam, the coupled PDEs will be changed to N1 + N2 + 5 ordinary differential equations (ODEs). These complex equations are solved numerically, and the natural frequencies of the system are extracted. The system is then simulated in both lateral and horizontal plane movements. The simulation shows that the governing equations are correct, and the system is ready for designing a proper controller. It should be mentioned that in the future works, the derived equations will be validated experimentally, and a suitable control strategy will be applied to the system to make it automated and more applicable.