Dynamic path planning over CG-Space of 10DOF Rover with static and randomly moving obstacles using RRT* rewiring

Dynamic path planning is a core research content for intelligent robots. This paper presents a CG-Space-based dynamic path planning and obstacle avoidance algorithm for 10 DOF wheeled mobile robot (Rover) traversing over 3D uneven terrains. CG-Space is the locus of the center of gravity location of Rover while moving on a 3D terrain. A CG-Space-based modified RRT* samples a random space tree structure. Dynamic rewiring this tree can handle the randomly moving obstacles and target in real time. Simulations demonstrate that the Rover can obtain the target location in 3D uneven dynamic environments with fixed and randomly moving obstacles.

Factorisation Path Based Refactorisation for High-Performance LU Decomposition in Real-Time Power System Simulation

The integration of renewable energy sources into modern power systems requires simulations with smaller step sizes, larger network models and the incorporation of complex nonlinear component models. These features make it more difficult to meet computation time requirements in real-time simulations and have motivated the development of high-performance LU decomposition methods. Since nonlinear component models cause numerical variations in the system matrix between simulation steps, this paper places a particular focus on the recomputation of LU decomposition, i.e., on the refactorisation step. The main contribution is the adoption of a factorisation path algorithm for partial refactorisation, which takes into account that only a subset of matrix entries change their values. The approach is integrated into the modern LU decomposition method NICSLU and benchmarked against the methods SuperLU and KLU. A performance analysis was carried out considering benchmark as well as real power systems. The results show the significant speedup of refactorisation computation times in use cases involving system matrices of different sizes, a variety of sparsity patterns and different ratios of numerically varying matrix entries. Consequently, the presented high-performance LU decomposition method can assist in meeting computation time requirements in real-time simulations of modern power systems.

Real-time tuning of PID controller based on optimization algorithms for a quadrotor

Purpose This study aims to develop a quadrotor with a robust control system against weight variations. A Proportional-Integral-Derivative (PID) controller based on Particle Swarm Optimization and Differential Evaluation to tune the parameters of PID has been implemented with real-time simulations of the quadrotor. Design/methodology/approach The optimization algorithms are combined with the PID control mechanism of the quadrotor to increase the performance of the trajectory tracking for a quadrotor. The dynamical model of the quadrotor is derived by using Newton-Euler equations. Findings In this study, the most efficient control parameters of the quadrotor are selected using evolutionary optimization algorithms in real-time simulations. The control parameters of PID directly affect the controller’s performance that position error and stability improved by tuning the parameters. Therefore, the optimization algorithms can be used to improve the trajectory tracking performance of the quadrotor. Practical implications The online optimization result showed that evolutionary algorithms improve the performance of the trajectory tracking of the quadrotor. Originality/value This study states the design of an optimized controller compared with manually tuned controller methods. Fitness functions are defined as a custom fitness function (overshoot, rise-time, settling-time and steady-state error), mean-square-error, root-mean-square-error and sum-square-error. In addition, all the simulations are performed based on a realistic simulation environment. Furthermore, the optimization process of the parameters is implemented in real-time that the proposed controller searches better parameters with real-time simulations and finds the optimal parameter online.

Dynamics of a vortex dipole in a holographic superfluid

We use holography to investigate the dynamics of a vortex-anti-vortex dipole in a strongly coupled superfluid in 2+1 dimensions. The system is evaluated in numerical real-time simulations in order to study the evolution of the vortices as they approach and eventually annihilate each other. A tracking algorithm with sub-plaquette resolution is introduced which permits a high-precision determination of the vortex trajectories. With the increased precision of the trajectories it becomes possible to directly compute the vortex velocities and accelerations. We find that in the holographic superfluid the vortices follow universal trajectories independent of their initial separation, indicating that a vortex-anti-vortex pair is fully characterized by its separation. Subtle non-universal effects in the vortex motion at early times of the evolution can be fully attributed to artifacts due to the numerical initialization of the vortices. We also study the dependence of the dynamics on the temperature of the superfluid.

Real-Time Anticipation and Prevention of Hot Spots by Monitoring the Dynamic Conductance of Photovoltaic Panels

<div>Hot spotting in photovoltaic (PV) panels causes physical damage, power loss, reduced lifetime reliability, and increased manufacturing costs. The problem arises routinely in defect-free standard panels; any string of cells that receives uneven illumination can develop hot spots, and the temperature rise often exceeds 100°C in conventional silicon panels despite on-panel bypass diodes, the standard mitigation technique. Bypass diodes limit the power dissipated in a cell subjected to reverse bias, but they do not prevent hot spots from forming. An alternative control method has been suggested by Kernahan [1] that senses in real time the dynamic conductance |dI/dV| of a string of cells and adjusts its operating current so that a partially shaded cell is never forced into reverse bias. We start by exploring the behavior of individual illuminated PV cells when externally forced into reverse bias. We observe that cells can suffer significant heating and structural damage, with desoldering of cell-tabbing and discolorations on the front cell surface. Then we test PV panels and confirm Kernahan’s proposed panel-level solution that anticipates and prevents hot spots in real time. Simulations of cells and panels confirm our experimental observations and provide insights into both the operation of Kernahan’s method and panel performance.</div>

Real-Time Anticipation and Prevention of Hot Spots by Monitoring the Dynamic Conductance of Photovoltaic Panels

<div>Hot spotting in photovoltaic (PV) panels causes physical damage, power loss, reduced lifetime reliability, and increased manufacturing costs. The problem arises routinely in defect-free standard panels; any string of cells that receives uneven illumination can develop hot spots, and the temperature rise often exceeds 100°C in conventional silicon panels despite on-panel bypass diodes, the standard mitigation technique. Bypass diodes limit the power dissipated in a cell subjected to reverse bias, but they do not prevent hot spots from forming. An alternative control method has been suggested by Kernahan [1] that senses in real time the dynamic conductance |dI/dV| of a string of cells and adjusts its operating current so that a partially shaded cell is never forced into reverse bias. We start by exploring the behavior of individual illuminated PV cells when externally forced into reverse bias. We observe that cells can suffer significant heating and structural damage, with desoldering of cell-tabbing and discolorations on the front cell surface. Then we test PV panels and confirm Kernahan’s proposed panel-level solution that anticipates and prevents hot spots in real time. Simulations of cells and panels confirm our experimental observations and provide insights into both the operation of Kernahan’s method and panel performance.</div>