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

Optimisation-based verification process of obstacle avoidance systems for unmanned vehicles

This thesis deals with safety verification analysis of collision avoidance systems for unmanned vehicles. The safety of the vehicle is dependent on collision avoidance algorithms and associated control laws, and it must be proven that the collision avoidance algorithms and controllers are functioning correctly in all nominal conditions, various failure conditions and in the presence of possible variations in the vehicle and operational environment. The current widely used exhaustive search based approaches are not suitable for safety analysis of autonomous vehicles due to the large number of possible variations and the complexity of algorithms and the systems. To address this topic, a new optimisation-based verification method is developed to verify the safety of collision avoidance systems. The proposed verification method formulates the worst case analysis problem arising the verification of collision avoidance systems into an optimisation problem and employs optimisation algorithms to automatically search the worst cases. Minimum distance to the obstacle during the collision avoidance manoeuvre is defined as the objective function of the optimisation problem, and realistic simulation consisting of the detailed vehicle dynamics, the operational environment, the collision avoidance algorithm and low level control laws is embedded in the optimisation process. This enables the verification process to take into account the parameters variations in the vehicle, the change of the environment, the uncertainties in sensors, and in particular the mismatching between model used for developing the collision avoidance algorithms and the real vehicle. It is shown that the resultant simulation based optimisation problem is non-convex and there might be many local optima. To illustrate and investigate the proposed optimisation based verification process, the potential field method and decision making collision avoidance method are chosen as an obstacle avoidance candidate technique for verification study. Five benchmark case studies are investigated in this thesis: static obstacle avoidance system of a simple unicycle robot, moving obstacle avoidance system for a Pioneer 3DX robot, and a 6 Degrees of Freedom fixed wing Unmanned Aerial Vehicle with static and moving collision avoidance algorithms. It is proven that although a local optimisation method for nonlinear optimisation is quite efficient, it is not able to find the most dangerous situation. Results in this thesis show that, among all the global optimisation methods that have been investigated, the DIviding RECTangle method provides most promising performance for verification of collision avoidance functions in terms of guaranteed capability in searching worst scenarios

Air Traffic Management Safety Challenges

The primary goal of the Air Traffic Management (ATM) system is to control accident risk. ATM safety has improved over the decades for many reasons, from better equipment to additional safety defences. But ATM safety targets, improving on current performance, are now extremely demanding. Safety analysts and aviation decision-makers have to make safety assessments based on statistically incomplete evidence. If future risks cannot be estimated with precision, then how is safety to be assured with traffic growth and operational/technical changes? What are the design implications for the USA’s ‘Next Generation Air Transportation System’ (NextGen) and Europe’s Single European Sky ATM Research Programme (SESAR)? ATM accident precursors arise from (eg) pilot/controller workload, miscommunication, and lack of upto- date information. Can these accident precursors confidently be ‘designed out’ by (eg) better system knowledge across ATM participants, automatic safety checks, and machine rather than voice communication? Future potentially hazardous situations could be as ‘messy’ in system terms as the Überlingen mid-air collision. Are ATM safety regulation policies fit for purpose: is it more and more difficult to innovate, to introduce new technologies and novel operational concepts? Must regulators be more active, eg more inspections and monitoring of real operational and organisational practices

Decentralized UAV guidance using modified boid algorithms

Decentralized guidance of Unoccupied Air Vehicles (UAVs) is a very challenging problem. Such technology can lead to improved safety, reduced cost, and improved mission efficiency. Only a few ideas for achieving decentralized guidance exist, the most effective being the boid algorithm. Boid algorithms are rule-based guidance methods derived from observations of animal swarms. In this paper, boid rules are used to autonomously control a group of UAVs in high-level transit simulations. This paper differs from previous work in that, as an alternative to using exponentially scaled behavior weightings, the weightings are computed off-line and scheduled according to a contingency management system. The motivation for this technique is to reduce the amount of on-line computation required by the flight system. Many modifications to the basic boid algorithm are required in order to achieve a flightworthy design. These modifications include the ability to define flight areas, limit turning maneuvers in accordance with the aircraft dynamics, and produce intelligent waypoint paths. The use of a contingency management system is also a major modification to the boid algorithm. A Simple Genetic Algorithm is used to partially optimize the behavior weightings of the boid algorithm. While a full optimization of all contingencies is not performed due to computation requirements, the framework for such a process is developed. Wolfram\u27s Matlab software is used to develop and simulate the boid guidance algorithm. The algorithm is interfaced with Cloud Cap Technology\u27s Piccolo autopilot system for Hardware-in-the-Loop simulations. These high-fidelity simulations prove this technology is both feasible and practical. They also prove the boid guidance system developed herein is suitable for comprehensive flight testing

Real-time simulations to evaluate the RPAS integration in shared airspace

This paper presents the work done during the first year in the WP-E project ERAINT (Evaluation of the RPAS-ATM Interaction in Non-Segregated Airspace) that intends to evaluate by means of human-in-the-loop real-time simulations the interaction between a Remotely Piloted Aircraft System (RPAS) and the Air Traffic Management (ATM) when a Remotely Piloted Aircraft (RPA) is being operated in shared airspace. This interaction will be evaluated from three different perspectives. First, the separation management, its results are presented in this paper. Secondly, during the next year, the contingency management, also including loss of link situations and, lastly, the capacity impact of such operations in the overall ATM system. The used simulation infrastructure allows to simulate realistic exercises from both the RPAS Pilot-in-Command (PiC) and the Air Traffic Controller (ATCo) perspectives. Moreover, it permits to analyze the actual workload of the ATC and to evaluate several support tools and different RPAS levels of automation from the PiC and ATC sides. The simulation results and the usefulness of the support tools are presented for each selected concept of operations.Peer ReviewedPostprint (published version