A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Sähköbussin nopeuden ja ohjauskulman säätö edellä ajavan ajoneuvon liike-radan seuraamisessa

Buses face problems when the capacity of a bus is limited but it should be larger to be able to carry more passengers. The capacity of a bus is already increased to its maximum that is allowed by the infrastructure. The capacity of a bus line could be increased by driving buses more frequently but it would increase costs, that is unwanted. Costs could be reduced by driving buses as platoons consisting of two buses where only the first bus would be operated by a professional driver and the second would be driven autonomously. Autonomous driving requires longitudinal and lateral control of a vehicle. The follower bus should be able to follow the path driven by the leader bus precisely and avoid inter-vehicular collisions while still driving as close together as possible to indicate other traffic that they move as a platoon. Lateral control is usually divided into path following and direct following methods in the literature. Path following methods include obtaining the path of the leader vehicle and following of that path. Path following methods are usually accurate in terms of lateral error but are complex and require a lot of computational capacity. Direct following methods are easy to compute but they do not guarantee precise path following. A simulation model consisting of two identical buses was developed. One longitudinal controller and four lateral control laws were proposed. Longitudinal controller was designed to work also in tight turns which is not usually investigated. Lateral control laws proposed were geometrical in nature and required only input as the relative position of the leader bus. Therefore, they did not require inter-vehicular communication. Longitudinal controller worked well for initialization of the system with inter-vehicular distances from 2 to 10 m. It worked well in acceleration and deceleration tests when both buses were loaded similarly but failed to prevent collisions when follower bus was loaded more heavily than the leader. In lateral controller tests, Pure Pursuit and Modified Pure Pursuit methods were able to follow the leader producing following lateral errors: 0,8 m and 1,1 m (steady-state tests), 0,8 m and 0,7 m (u-turn maneuver) and 0,3 m/0,4 m and 0,4 m/0,5 m (double lane change maneuver, 5 m/s/10 m/s respectively). Spline Pursuit method showed oscillatory behavior and did not follow the leader well. Circular Pursuit method showed also oscillatory behavior and did not follow the leader well. However, it showed better performance than the Spline Pursuit. It remains to be studied whether Pure Pursuit or Modified Pure Pursuit can challenge more sophisticated path following methods.Linja-autojen matkustajakapasiteetti on rajallinen, mikä aiheuttaa ongelmia, sillä sen tulisi olla suurempi. Kapasiteetti on jo nostettu suurimmalle mahdolliselle tasolle, mitä nykyinen infrastruktuuri mahdollistaa. Linja-autolinjan kapasiteettia voisi nostaa ajamalla linja-autoja tiheämmin. Tämä kuitenkin johtaa suurempiin kustannuksiin. Kustannuksia voisi vähentää ajamalla linja-autoja kahden ajoneuvon jonoina, joissa ensimmäistä ajo-neuvoa ohjaisi ammattilaiskuljettaja ja toinen olisi autonomisesti ohjattu. Autonominen ajaminen vaatii ajoneuvon nopeuden ja ohjauskulman säätöä. Seuraajalinja-auton pitää pystyä seuraamaan johtajalinja-auton ajamaa ajouraa tarkasti ja välttää törmäämistä johtajaan. Linja-autojen välinen etäisyys on kuitenkin oltava riittävän pieni, jotta se viestisi muulle liikenteelle, että ajoneuvot ajavat jonona. Kirjallisuus jakaa ohjauskulman säädön yleensä ajouran seuraamiseen ja suoraan seuraamiseen. Ajouran seuraaminen koostuu johtaja-ajoneuvon ajouran saamisesta ja tämän uran seuraamisesta. Ajouran seuraamisen metodit ovat yleensä tarkkoja poikittaisen virheen suhteen, mutta ovat monimutkaisia ja vaativat paljon laskennallista kapasiteettia. Suoran seuraamisen metodit ovat laskennallisesti kevyitä, mutta eivät takaa tarkkaa ajouran seuraamista. Kahdesta identtisestä linja-autosta koostuva simulaatiomalli kehitettiin. Yksi nopeussäädin ja neljä ohjauskulman säätölakia esitettiin. Nopeussäädin suunniteltiin toimimaan myös tiukoissa käännöksissä, mitä ei ole yleensä tutkittu. Ohjauskulman säätölait perustuivat geometriseen päättelyyn ja ne tarvitsivat vain johtajalinja-auton suhteellisen asentotiedon. Säätölait eivät vaatineet ajoneuvojen välistä kommunikaatiota. Nopeussäädin toimi järjestelmän alustamisessa ajoneuvojen välisen etäisyyden ollessa 2-10 m. Se toimi hyvin kiihdytys- ja jarrutustesteissä, kun molemmat linja-autot olivat lastattu identtisellä kuormalla, mutta epäonnistui estämään törmäämisen, kun seuraajalinja-auto oli lastattu suuremmalla kuormalla kuin johtaja. Ohjauskulman säädön testeissä Pure Pursuit ja Modified Pure Pursuit pystyivät seuraamaan johtajaa seuraavilla poikittaissuuntaisilla virheillä: 0,8 m ja 1,1 m (steady-state-testit), 0,8 m ja 0,7 m (u-käännös) ja 0,3 m/0,4 m ja 0,4 m/0,5 m (kaksoiskaistanvaihto, 5 m/s/10 m/s vastaavasti). Spline Pursuit käyttäytyi värähtelevästi eikä seurannut johtajaa hyvin. Circular Pursuit käyttäytyi värähtelevästi eikä seurannut johtajaa hyvin, mutta kuitenkin paremmin kuin Spline Pursuit. Jää nähtäväksi pystyykö Pure Pursuit tai Modified Pure Pursuit haastamaan monimutkaisempia ajouran seuraamisen metodeja

Close Formation Flight Missions Using Vision-Based Position Detection System

In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

Cognitive Vehicle Platooning in the Era of Automated Electric Transportation

Vehicle platooning is an important innovation in the automotive industry that aims at improving safety, mileage, efficiency, and the time needed to travel. This research focuses on the various aspects of vehicle platooning, one of the important aspects being analysis of different control strategies that lead to a stable and robust platoon. Safety of passengers being a very important consideration, the control design should be such that the controller remains robust under uncertain environments. As a part of the Department of Energy (DOE) project, this research also tries to show a demonstration of vehicle platooning using robots. In an automated highway scenario, a vehicle platoon can be thought of as a string of vehicles, following one another as a platoon. Being equipped by wireless communication capabilities, these vehicles communicate with one another to maintain their formation as a platoon, hence are cognitive. Autonomous capable vehicles in tightly spaced, computer-controlled platoons will lead to savings in energy due to reduced aerodynamic forces, as well as increased passenger comfort since there will be no sudden accelerations or decelerations. Impacts in the occurrence of collisions, if any, will be very low. The greatest benefit obtained is, however, an increase in highway capacity, along with reduction in traffic congestion, pollution, and energy consumption. Another aspect of this project is the automated electric transportation (AET). This aims at providing energy directly to vehicles from electric highways, thus reducing their energy consumption and CO2 emission. By eliminating the use of overhead wires, infrastructure can be upgraded by electrifying highways and providing energy on demand and in real time to moving vehicles via a wireless energy transfer phenomenon known as wireless inductive coupling. The work done in this research will help to gain an insight into vehicle platooning and the control system related to maintaining the vehicles in this formation

Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design and achieve solutions for optimal design features before implementation. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since vehicle movements are not as flexible as pedestrian movements, velocity angle constraints are included for vehicles. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs