Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Efficient Vision Transformers for Autonomous Off-Road Perception Systems

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also quickly detect changes in the surrounding environment. In autonomous vehicle research, the environment perception system is one of the key components of development. Environment perception systems allow the vehicle to understand its surroundings. This is done by using cameras, light detection and ranging (LiDAR), with other sensor systems and modalities. Deep learning computer vision algorithms have been shown to be the strongest tool for translating camera data into accurate and safe traversability decisions regarding the environment surrounding a vehicle. In order for a vehicle to safely traverse an area in real time, these computer vision algorithms must be accurate and have low latency. While much research has studied autonomous driving for traversing well-structured urban environments, limited research exists evaluating perception system improvements in off-road settings. This research aims to investigate the adaptability of several existing deep-learning architectures for semantic segmentation in off-road environments. Previous studies of two Convolutional Neural Network (CNN) architectures are included for comparison with new evaluation of Vision Transformer (ViT) architectures for semantic segmentation. Our results demonstrate viability of ViT architectures for off-road perception systems, having a strong segmentation accuracy, lower inference speed and memory footprint compared to previous results with CNN architectures.

A hydrothermal investigation system for the Qianlong-Ⅱ autonomous underwater vehicle

Qianlong-Ⅱ is a fully autonomous underwater vehicle designed for the investigation of submarine resources,particularly polymetallic sulfides. It was used to successfully explore hydrothermal fields on the Southwest Indian Ridge. Here, we summarized the exploration of hydrothermal systems using Qianlong-Ⅱ, including detailed descriptions of its implementation along with the systems used for data management and fast mapping. We also introduced a method to remove platform magnetic interference using magnetic data while Qianlong-Ⅱ is spinning. Based on hydrothermal anomalies collected by Qianlong-Ⅱ, we developed a rapid method for locating hydrothermal vents. Taking one dive as an example, we systemically demonstrated the process for analyzing hydrothermal survey data to locate hydrothermal vents.

Geometric formulations and variational integrators of discrete autonomous Birkhoff systems

The variational integrators of autonomous Birkhoff systems are obtained by the discrete variational principle. The geometric structure of the discrete autonomous Birkhoff system is formulated. The discretization of mathematical pendulum shows that the discrete variational method is as effective as symplectic scheme for the autonomous Birkhoff systems.

Nonchaotic random behaviour in the second order autonomous system

Evidence is presented for the nonchaotic random behaviour in a second-order autonomous deterministic system. This behaviour is different from chaos and strange nonchaotic attractor. The nonchaotic random behaviour is very sensitive to the initial conditions. Slight difference of the initial conditions will generate wholly different phase trajectories. This random behaviour has a transient random nature and is very similar to the coin-throwing case in the classical theory of probability. The existence of the nonchaotic random behaviour not only can be derived from the theoretical analysis, but also is proved by the results of the simulated experiments in this paper.

Generating one-,two-,three-and four-scroll attractors from a novel four-dimensional smooth autonomous chaotic system

A new four-dimensional quadratic smooth autonomous chaotic system is presented in this paper, which can exhibit periodic orbit and chaos under the conditions on the system parameters. Importantly, the system can generate one-, two-, three- and four-scroll chaotic attractors with appropriate choices of parameters. Interestingly, all the attractors are generated only by changing a single parameter. The dynamic analysis approach in the paper involves time series, phase portraits, Poincare maps, a bifurcation diagram, and Lyapunov exponents, to investigate some basic dynamical behaviours of the proposed four-dimensional system.

Analysis of Influencing Factors on Lift Coefficients of Autonomous Sailboat Double Sail Propulsion System Based on Vortex Panel Method

Sail is the core part of autonomous sailboat and wing sail is a new type of sail. Wing sail generates not only propulsion but also lateral force and heeling moment. The latter two will affect the navigation status and bring resistance. Double sail can effectively reduce the center of wind pressure and heeling moment. In order to study the effect of distance between two sails, airfoil and attack angle on the total lift coefficient of double sail propulsion system, pressure coefficient distribution and lift coefficient calculation model have been established based on vortex panel method. By using the basic finite solution, the fluid dynamic forces on the two-dimensional sails are computed.The results show that, the distance in the range of 0 to 1 time chord length, when using the same airfoil in the fore and aft sail, the total lift coefficient of the double sail increases with the increase of distance, finally reaches a stable value in the range of one to three times chord length. Lift coefficients of thicker airfoils are more sensitive to the change of distance. The thicker the airfoil, the longer distance is required of the total lift coefficient toward stable.When different airfoils are adopted in fore and aft sail, the total lift coefficient increases with the increase of the thickness of aft sail. The smaller the thickness difference is, the more sensitive to the distance change the lift coefficient is. The thinner the fore sail is, the lower the influence will be on the lift coefficient of aft sail.

A necessary and sufficient condition for transforming autonomous systems into linear autonomous Birkhoffian systems

The problem of transforming autonomous systems into Birkhoffian systems is studied. A reasonable form of linear autonomous Birkhoff equations is given. By combining them with the undetermined tensor method, a necessary and sufficient condition for an autonomous system to have a representation in terms of linear autonomous Birkhoff equations is obtained. The methods of constructing Birkhoffian dynamical functions are given. Two examples are given to illustrate the application of the results.

SUFFICIENT CONDITIONS FOR THE EXISTENCE OF PERIODIC SOLUTIONS OF A AUTONOMOUS DIFFERENTIAL SYSTEM

In this paper, some sufficient conditions on the existence of non-trivial periodic solutions of the system dx/dt=e(y), dy/dt=- f(x)h(y)- g(x)are obtained, which not only generalize some known results concerning the Lienard system in this direction, but also relax or eliminate some traditional assumptions.

Artificial Pheromone System Using RFID for Navigation of Autonomous Robots

Navigation system based on the animal behavior has received a growing attention in the past few years. The navigation systems using artificial pheromone are still few so far. For this reason, this paper presents our research that aim to implement autonomous navigation with artificial pheromone system. By introducing artificial pheromone system composed of data carriers and autonomous robots, the robotic system creates a potential field to navigate their group. We have developed a pheromone density model to realize the function of pheromones with the help of data carders. We intend to show the effectiveness of the proposed system by performing simulations and realization using modified mobile robot. The pheromone potential field system can be used for navigation of autonomous robots.

Direct method of finding first integral of two-dimensional autonomous systems in polar coordinates

A direct method to find the first integral for two-dimensional autonomous system in polar coordinates is suggested. It is shown that if the equation of motion expressed by differential 1-forms for a given autonomous Hamiltonian system is multiplied by a set of multiplicative functions, then the general expression of the first integral can be obtained, An example is given to illustrate the application of the results.

Stability Analysis on Speed Control System of Autonomous Underwater Vehicle

The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle（AUV）.The divergence of control,which the unstable system may be brought about,is fatal to the operation of AUV.The stability analysis of the PD and S-surface speed controllers based on the Lyapunov＇s direct method is proposed in this paper.After decoupling the six degree-of-freedom（DOF）motions of the AUV,the axial dynamic behavior is discussed and the condition is deduced,in which the parameters selection within stability domain can guarantee the system asymptotically stable.The experimental results in a tank and on the sea have successfully verified the algorithm reliability,which can be served as a good reference for analyzing other AUV nonlinear control systems.

On the Trends of Autonomous Unmanned Systems Research

In recent decades,academia and industry have put increasing attention and investment into the research and development of autonomous unmanned systems.An autonomous unmanned vehi-cle is a machine equipped with necessary data-processing units,sophisticated sensors,environment perception,automatic control,motion planning,task planning,mission management,and com-munication systems.

A semantic-centered cloud control framework for autonomous unmanned system

Rich semantic information in natural language increases team efficiency in human collaboration, reduces dependence on high precision data information, and improves adaptability to dynamic environment. We propose a semantic centered cloud control framework for cooperative multi-unmanned ground vehicle(UGV) system. Firstly, semantic modeling of task and environment is implemented by ontology to build a unified conceptual architecture, and secondly, a scene semantic information extraction method combining deep learning and semantic web rule language(SWRL) rules is used to realize the scene understanding and task-level cloud task cooperation. Finally, simulation results show that the framework is a feasible way to enable autonomous unmanned systems to conduct cooperative tasks.

Reinforcement Learning Behavioral Control for Nonlinear Autonomous System

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear controllers.In this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error learning.Specifically,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission priority.Compared with existing mission supervisors,the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural networks.In the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control policy.Compared with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and consumption.All error signals are proved to be semi-globally uniformly ultimately bounded(SGUUB).Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers,respectively.

The Graph Structure of the Internet at the Autonomous Systems Level during Ten Years

We study how the graph structure of the Internet at the Autonomous Systems (AS) level evolved during a decade. For each year of the period 2008-2017 we consider a snapshot of the AS graph and examine how many features related to structure, connectivity and centrality changed over time. The analysis of these metrics provides topological and data traffic information and allows to clarify some assumptions about the models concerning the evolution of the Internet graph structure. We find that the size of the Internet roughly doubled. The overall trend of the average connectivity is an increase over time, while that of the shortest path length is a decrease over time. The internal core of the Internet is composed of a small fraction of big AS and is more stable and connected the external cores. A hierarchical organization emerges where a small fraction of big hubs are connected to many regions with high internal cohesiveness, poorly connected among them and containing AS with low and medium numbers of links. Centrality measurements indicate that the average number of shortest paths crossing an AS or containing a link between two of them decreased over time.

Practical Security Approaches against Border Gateway Protocol (BGP) Session Hijacking Attacks between Autonomous Systems

The border gateway protocol (BGP) is the default inter domain routing protocol used on the internet for exchanging information between autonomous systems. Available literature suggests that BGP is vulnerable to session hijacking attacks. There are a number of proposals aimed at improving BGP security which have not been fully implemented. This paper examines a number of approaches for securing BGP through a comparative study and identifies the reasons why these proposals have not been implemented commercially. This paper analyses the architecture of internet routing and the design of BGP while focusing on the problem of BGP session hijacking attacks. Using Graphical Network Simulator 3 (GNS-3), a session hijack is demonstrated and a solution which involves the implementation of route filtering, policy-maps and route-maps on CISCO routers representing ASes is carried out. In the end, a workable industry standard framework for securing and protecting BGP sessions and border routers from exploitation with little or no modification to the existing routing infrastructure is demonstrated.

Predefined-Time Backstepping Stabilization of Autonomous Nonlinear Systems

Dear Editor,In this letter,the backstepping technique is applied to solve the predefined-time stabilization problem for autonomous nonlinear systems,where nonlinear terms are unknown but satisfy a linear growth condition.A linear time-varying control law is designed to drive all states of an autonomous nonlinear system to the origin for an a priori preassigned time.

Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent and mathematical foundations of autonomous systems.It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems.It explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive process.The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering.Emerging paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are described.Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.

Adaptive PID control system for an autonomous underwater vehicle

The control system of an autonomous underwater vehicle （AUV） is introduced. According to control requirements of the AUV, a simple but practical adaptive PID control method is designed The semi-physical simulation is done to test the feasibility of the control system. The neural network idea and the structure of PID controller are referred to design the adaptive PID controller. An intelligent integral is introduced to improve control precision. Compaed with traditional PID con- trollers, the adaptive PID controller has simple structure, good online adjusting ability, fast convergence and good robustness. The simulation experiments also show that the adaptive PID control system has high precision and fine antijamming ability.