Showing papers presented at "Mediterranean Conference on Control and Automation in 2016"

An autonomous multi-sensor UAV system for reduced-input precision agriculture applications

Abstract: The constant innovation and advancement in unmanned aerial vehicle (UAV) sensing technology has facilitated a series of applications in the field of agriculture. The adoption of precision agriculture and reduced-input farming technics entails higher level of input data, with enhanced spatial and spectral resolution, and increased frequency of information delivery. Whereas satellite remote sensing still has decisive limitations for use in farm management applications, especially in small-scale agriculture, the comparative advantages of UAVs in these aspects propelled them as an alternative data collection platform. However, automation in the deployment of UAV sensing systems for operational in-field use, integration of visible, near-infrared and thermal spectral ranges, standardization of data collection, data processing and analysis workflow, production of readily available services, and credibility of reliable economic return from their incorporation into agronomical practices are components still relatively absent from the agriculture industry. In this paper, we demonstrate the operational use of a recently developed autonomous multi-sensor UAV imaging system, which is designed to provide spectral information related to water management for a pomegranate orchard. Vegetation and water stress indices were derived from both multispectral and thermal spectral data collected simultaneously from the system, and were used as indicators for crop water stress and crop health condition. It is concluded that the developed system addresses the needs and challenges identified for the incorporation of UAV sensing technology into reduced-input precision agriculture applications.

Multicopter unmanned aerial vehicle for automated inspection of wind turbines

Abstract: A concept for a multicopter unmanned aerial vehicle (UAV) automatically performing inspection flights at a wind turbine is proposed. Key aspects of the concept are (1) a priori 3D mapping of the plant and (2) spline-based flight path planning as well as (3) a collision avoidance and distance control system. A quadrotor UAV prototype and its dynamical model are presented. Validation of the different aspects is carried out in simulation and partially in indoor tests using Robot Operating System (ROS). Existence of a 3D map is an essential precondition for path planning and collision-free flight. A brief initial flight preceding the actual inspection with a 2D LiDAR sensor yields a point cloud of the plant which is used for 3D mapping. This map is efficiently generated and represented using octrees, a hierarchical data structure that can be used for 3D maps. Subsequently a smooth and collision-free flight path is generated using splines. For redundancy's sake navigation tasks not only rely on GPS but also on the LiDAR sensor mentioned before. The sensor allows for continuous estimation of the distance between multicopter and wind turbine. A distance control algorithm guarantees collision-free flight.

Set-based Line-of-Sight (LOS) path following with collision avoidance for underactuated unmanned surface vessel

Abstract: A cornerstone ability of an autonomous unmanned surface vessel (USV) is to avoid collisions with stationary obstacles and other moving vehicles while following a predefined path. USVs are typically underactuated, and this paper extends recent results in set-based guidance theory to an underactuated surface vessel, resulting in a switched guidance system with a path following mode and a collision avoidance mode. This system can be used with any combination of path following and collision avoidance guidance laws. Furthermore, a specific guidance law for collision avoidance is suggested that ensures tracking of a safe radius about a moving obstacle. The guidance law is specifically designed to assure collision avoidance while abiding by the International Regulations for Preventing Collisions at Sea (COLREGs). It is proven that the USV successfully circumvents the obstacles in a COLREGs compliant manner and that path following is achieved in path following mode. Simulations results confirm the effectiveness of the proposed approach.

Real-time autonomous take-off, tracking and landing of UAV on a moving UGV platform

Abstract: This paper presents a control strategy for take-off, tracking, and landing of a quadrotor unmanned aerial vehicle (UAV) on an unmanned ground vehicle (UGV) to be applied to missions of forest fires monitoring, detection, and fighting and other applications. A combination of sliding mode control (SMC) and linear quadratic regulator (LQR) is presented as the UAV local controller, while pure-pursuit strategy is applied as the UGV controller. Leader-follower formation controller approach is used during take-off, tracking and landing phases based on SMC. Experimental results are presented in order to demonstrate the performance of the team in different scenarios.

Line-of-sight curved path following for underactuated USVs and AUVs in the horizontal plane under the influence of ocean currents

Abstract: An essential ability of autonomous unmanned surface vessels (USVs) and autonomous underwater vehicles (AUVs) moving in a horizontal plane is to follow a general two-dimensional path in the presence of unknown ocean currents. This paper presents a method to achieve this. The proposed guidance and control system only requires absolute velocity measurements for feedback, thereby foregoing the need for expensive sensors to measure relative velocities. The closed-loop system consists of a guidance law and an adaptive feedback linearizing controller combined with sliding mode, and is shown to render the path cross-track error dynamics UGAS and USGES. Simulation results are presented to verify the theoretical results.

A survey on pneumatic wall-climbing robots for inspection

Abstract: The aim of this article is to present a survey on inspection applications of Pneumatic Wall-Climbing Robots (PWCR). In general, a PWCR utilizes negative pressure as its adhesion method, through mainly suction cups or negative pressure thrust-based mechanisms. Their main advantage being their ability to climb non-ferromagnetic surfaces, such as glass and composite materials, in comparison with climbing robots based on magnetic adhesion methods. A growing application area is the utilization of PWCRs for inspection purposes for accelerating the otherwise time consuming procedures of manual inspection, while offering the important advantage of protecting human workers from hazardous and/or unreachable environments. This article will summarize the key enabling inspection applications of PWCRs in the following areas: a) Construction, b) Industrial Infrastructures, as well as c) Aircraft applications.

Machine learning approach to automatic bucket loading

Abstract: The automation of bucket loading for repetitive tasks of earth-moving operations is desired in several applications at mining sites, quarries and construction sites where larger amounts of gravel and fragmented rock are to be moved. In load and carry cycles the average bucket weight is the dominating performance parameter, while fuel efficiency and loading time also come into play with short loading cycles. This paper presents the analysis of data recorded during loading of different types of gravel piles with a Volvo L110G wheel loader. Regression models of lift and tilt actions are fitted to the behavior of an expert driver for a gravel pile. We present linear regression models for lift and tilt action that explain most of the variance in the recorded data and outline a learning approach for solving the automatic bucket loading problem. A general solution should provide good performance in terms of average bucket weight, cycle time of loading and fuel efficiency for different types of material and pile geometries. We propose that a reinforcement learning approach can be used to further refine models fitted to the behavior of expert drivers, and we briefly discuss the scooping problem in terms of a Markov decision process and possible value functions and policy iteration schemes.

Flatness-based control for a quadrotor camera helicopter using model predictive control trajectory generation

Abstract: This paper addresses a flatness-based controller and a Model Predictive Control (MPC) trajectory generation for a quadrotor camera helicopter. Applications like aerial videography can highly benefit from an automation of the pilot's tasks, enabling the camera operator to solely focus on camera motion control. The coupled nonlinear system dynamics of a quadrotor pose difficulties precisely controlling several channels simultaneously for agile maneuvering using conventional controllers. A flatness-based approach is employed to obtain linear input-output dynamics, even for large attitude angles. The associated state feedback equations are explicitly derived. The resulting linear system dynamics are controlled using a cascaded proportional control structure. Feasible reference trajectories are generated using a linear MPC, which translates operator commands for camera motions — e.g. relative to a point-of-interest — into quadrotor trajectories complying with operational constraints. Flatness-based controller and MPC trajectory generation show tracking errors below 1% in simulation tests. Accurate and smooth positioning is achieved in first indoor test flights. The gained results motivate adoptions of the proposed control approach to other UAV applications with similar demands for pilot automation and accuracy.

Development of a fuel cell hybrid-powered unmanned aerial vehicle

Abstract: This paper describes the design and development of a hybrid fuel cell/battery propulsion system for a long endurance small UAV. The high level system architecture is presented, followed by the hardware-in-the-loop testing and performance analysis. A high fidelity 6-DoF simulation model of the complete system was developed and used to test the system under different battery state-of-charge. The simulation model included the power manager for the hybrid propulsion system configuration, which is based on rule-based control. The simulation results are compared with the experimental results obtained from the Hardware-in-the-Loop testing.

Face recognition using fusion of PCA and LDA: Borda count approach

Abstract: Face recognition has become one of the most successful applications in the field of image analysis and understanding. This paper presents a new approach for identity recognition using rank-level fusion of multiple face representations. In this paper, we propose face recognition based on fusion of two well-known appearance-based techniques, Principal Component Analysis and Linear Discriminant Analysis. Fusion is done at rank level using Borda count method. Our experimental work demonstrates significant improvement in recognition accuracy over individual face representations.

Impact of different spacing policies for adaptive cruise control on traffic and energy consumption of electric vehicles

Abstract: This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance in terms of safety, while only few deal with the effect of ACC on the traffic flow and the environment. In particular, very little is know on traffic stability and energy consumption. In this study, the vehicles equipped with ACC are modelled and controlled by two different spacing policies. Besides, Human Driving Behavior (HDB) is modelled by using Gipps model for comparison and for simulating different penetration rates. As distinguished from other studies, vehicle dynamics and energy consumption of an electric car is formulated, which has completely different characteristics and limitations than combustion engine cars. Hence the study aims at providing additional understanding of how ACC-equipped electric vehicles will behave in dense traffic conditions. HDB and ACC vehicles are placed in a roundabout at different penetration rates. String stability and energy consumption are investigated by giving a shock wave to a stable traffic condition. It is found that ACC with quadratic spacing policy has significantly positive effects on string stability and energy consumption.

A distributed load balancing algorithm for the control plane in software defined networking

Abstract: The increasing demand of bandwidth, low latency and reliability, even in mobile scenarios, has pushed the evolution of the networking technologies in order to satisfy the requirements of innovative services. In this context, Software Defined Networking (SDN), namely a new networking paradigm that proposes the decoupling of the control plane from the forwarding plane, enables network control centralization and automation of the network management. In order to address the performance issues related to the SDN Control Plane, this paper proposes a distributed load balancing algorithm with the aim of dynamically balancing the control traffic across a cluster of SDN Controllers, thus minimizing the latency and increasing the overall cluster throughput. The algorithm is based on game theory and converges to a specific equilibrium known as Wardrop equilibrium. Numerical simulations show that the proposed algorithm outperforms a standard static configuration approach.

On the design, modeling and control of a novel compact aerial manipulator

Abstract: The aim of this article is to present a novel four-degree-of-freedom aerial manipulator allowing a multirotor Unmanned Aerial Vehicle (UAV) to physically interact with the environment. The proposed design, named CARMA (Compact AeRial MAnipulator), is characterized by low disturbances on the UAV flight dynamics, extended workspace (with regard to its retracted configuration) and fast dynamics (compared to the UAV dynamics). The dynamic model is formulated and a control structure consisting of an inverse kinematics algorithm and independent joint position controllers is presented. Furthermore, the design specifications of the prototype are analyzed in detail, while experimental evaluations are conducted for the extraction of the manipulator's workspace and the evaluation of system's tracking capabilities over pick-and-place trajectories. Finally, it is shown that the selected joint position sensors, combined with the derived inverse dynamic algorithm allow to determine the wrenches exerted at the base, due to swift motions of the arm.

Model predictive control for energy-saving and comfortable temperature control in buildings

Abstract: Model predictive control has been recognized as one of the essential solutions to achieve considerable energy savings in buildings. However, its performance on a building zone level can be inferior to a well-tuned conventional controller, especially in situations with constant energy prices and conservative comfort constraints. Optimization problem in the background has to be chosen to guarantee recursive feasibility and considerable energy savings without compromising the users comfort at the same time. This paper gives a novel formulation of the model predictive temperature control problem in buildings and its fair comparison with conventional controllers with the same level of flexibility allowed in zone temperature control. All controllers are tested for a system with seasonal heating and cooling, which is the most common case in real applications. It is shown that the introduced formulation leads to the model predictive controller that significantly outperforms conventional controllers both in energy consumption and users comfort.

Slung load transportation with a single aerial vehicle and disturbance removal

Abstract: We present a trajectory tracking controller for a quadrotor-load system, composed of a single load and a single unmanned aerial vehicle connected by a cable or rope. The load is modeled as a point mass while the aerial vehicle is assumed to be fully actuated, with thrust and attitude of the quadrotor as inputs to the system quadrotor-load. We assume there is a constant input disturbance at the thrust input, and a disturbance estimator is presented that guarantees that asymptotic tracking is guaranteed in the presence of such a disturbance. The load and the aerial vehicle are connected by a cable of fixed length that behaves as a rigid link under tensile forces, and as a non-rigid link when under compressive forces. The proposed controller guarantees that the cable is always under tensile forces, provided that the position trajectory to be tracked satisfies some mild conditions. The system quadrotor-load can be transformed into a form that resembles that of systems describing underactuated aerial vehicles, and for which a variety of control strategies have been proposed. In particular, we propose a controller based on a backstepping procedure in conjunction with a bounded double integrator controller. We present simulations validating the proposed control algorithm, and some preliminary experimental results are also presented.

Enhancing tracking performance in a smartphone-based navigation system for visually impaired people

Abstract: In this paper we show how to enhance the tracking performance of Arianna, a low-cost augmented reality system designed to meet the needs of people with problems of orientation, people with sight impairment and blind people. For augmented reality system we mean the design of: i) a set of paths and tags to be deployed in the environment, realized in various ways depending on the context (decorative elements easily identifiable, colorful stripes, QR code, RFID, etc.); ii) an instrument of mediation between the reality and the user (typically a smartphone) to access the information disseminated in the environment by means of a camera and provide a vibration feedback signal to the users for following pre-defined paths. In this paper we explore the possibility of applying optical flow techniques to the sequence of images captured by the camera along the paths, to identify the user movements and provide a position estimate. Experimental results show that the approach is promising.

Distributed area coverage control with imprecise robot localization

Abstract: This article examines the problem of area coverage for a network of mobile robots with imprecise agents' localization. Each robot has uniform radial sensing ability, governed by first order kinodynamics. The convex-space is partitioned based on the Guaranteed Voronoi (GV) principle and each robots area of responsibility corresponds to its GV-cell, bounded by hyperbolic arcs. The proposed control law is distributed, demands the positioning information about its GV-Delaunay neighbors and has an inherent collision avoidance property.

A Future Internet oriented user centric extended intelligent transportation system

Abstract: Intelligent Transportation Systems (ITS) are changing the way people plan a journey and travel around the world. Advanced mobility information systems, as well as intelligent multimodal mobility services, may take considerable advantage of consolidated technologies from emerging ICT frameworks. In this paper we propose an Extended Intelligent Transportation System (ExITS) consisting of a basic ITS equipped with a User Centric Control System (UCCS). The proposed ExITS relies on service personalization methodologies and is conceived as a Future Internet (FI) oriented, closed-loop, user centric architecture integrating and controlling ITS services. The proposed UCCS considers the trip planning service and takes into account both explicit and implicit user preferences in selecting travel solutions satisfying a given user request. The aim of the UCCS is to drive the trip planning service in proposing to the user travel typologies tailored to personal preferences. Implicit preferences are automatically inducted by similarity based unsupervised machine learning techniques and verified by a closed-loop control mechanism triggered by explicit user feedback.

Improvement of energy consumption for a lower limb exoskeleton through verticalization time optimization

Abstract: This paper focuses on a lower limb exoskeleton. The problem of improvement of energy efficiency of the exoskeleton during sit-to-stand motion (verticalization) is considered. Optimization of the time allocated for the verticalization motion is proposed as a way to improve energy efficiency. It is shown that optimal time of verticalization depends on the initial position of the exoskeleton and the relation between the two can be approximated by a polynomial function. An analysis and suggestions for practical applications of the obtained results are presented.

Attitude tracking of quadrotor UAV via mixed H2/H ∞ controller: An LMI based approach

Abstract: In this paper, a robust mixed H 2 /H ∞ static state feedback tracking controller with measurement noise and external disturbance robustness is presented for attitude tracking of a Quadrotor Unmanned Aerial Vehicle. Also, time response of the mixed H 2 /H controller is improved by adding regional pole-placement constraints. Since presented control design problem is a multi-objective convex optimization problem, so this problem is solved by Linear Matrix Inequalities (LMI). To ensure the presented robust controller performance, this controller and nonlinear model of quadrotor (with real parameters) are simulated in hard situation such as measurement noise and external disturbance and robust performance of the presented controller is proofed. Another contribution of this paper is, avoiding non-applicable simulation results that usually are happened in numerous articles. To reach this purpose, a saturation algorithm is developed which prevents the creation of non-applicable control signal values.

Evaluation of visual localization systems in underground mining

Abstract: In this article an evaluation of current technology on visual localization systems for underground mining is presented. The proposed study is considered to be the first step among others towards enabling vision-based mine inspection using Unmanned Micro Aerial Vehicles (UAVs). Furthermore, the aim of this article, is to verify applicable and reliable low cost existing methods and technologies for the problem of UAV localization in harsh and challenging environments. More specifically field trials were performed in one of the biggest mines in Europe, the iron ore mine of LKAB at Kiruna in Sweden. In this experimental evaluation the sensors employed were a RGB-D camera (Kinect for Windows) and a web camera (Playstation 3 Eye) in two configurations, as a stereo rig and as a monocular visual sensor. The processing of the stored data from the experiments will provide an insight into the efficiency of these sensors. Additionally, will identify what further technological and research developments are required to develop affordable autonomous UAV solutions for improving the underground mining production tasks.

Critical node detection based on attacker preferences

Abstract: The identification of Critical Nodes in technological, biological and social networks is a fundamental task in order to comprehend the behavior of such networks and to implement protection or intervention strategies aimed at reducing the network vulnerability. In this paper we focus on the perspective of an attacker that aims at disconnecting the network in several connected components, and we provide a formulation of the attacker behavior in terms of an optimization problem with two concurrent objectives: maximizing the damage dealt while minimizing the cost or effort of the attack. Such objectives are mediated according to the subjective preferences of the attacker. Specifically, the attacker identifies a set of nodes to be removed in order to disconnect the network in at least m connected components; the final objective is from one side to minimize the number of attacked nodes, and from another side to minimize the size of the largest connected component. We complement the paper by providing an heuristic approach to calculate an admissible solution to the problem at hand, based on the line graph of the original network topology and on the spectral clustering methodology.

A novel concept of attitude control for large multirotor-UAVs based on moving mass control

Abstract: In this work we aim to explore the concept of using the shift in the center of gravity, which in turn produces roll and pitch moments, to control the attitude of the quadrotor. We propose constructing a UAV with moving masses within each rotor arm. In this paper we show the mathematical equations describing the dynamics of the proposed system, propose a classical PID based control approach and analyze and confirm its stability. Furthermore, we analyze the effectiveness of the proposed controller in a Gazebo based simulation environment. Finally, we build a laboratory testbed that emulates the dynamics of the system and test our proposed control strategy.

Nonlinear model predictive extended eco-cruise control for battery electric vehicles

Abstract: Battery Electric Vehicles are becoming a promising technology for road transportation. However, the main disadvantage is the limited cruising range they can travel on a single battery charge. This paper presents a novel extended ecological cruise control system to increase the autonomy of an electric vehicle by using energy-efficient driving techniques. Driven velocity, acceleration profile, geometric and traffic characteristics of roads largely affect the energy consumption. An energy-efficient velocity profile should be derived based on anticipated optimal actions for future events by considering the electric vehicle dynamics, its energy consumption relations, traffic and road geometric information. A nonlinear model predictive control method with a fast numerical algorithm is adapted to determine proper velocity profile. In addition, a novel model to describe the energy consumption of a series-production electric vehicle is introduced. The hyperfunctions concept is used to model traffic and road geometry data in a new way. The proposed system is simulated on a test track scenario and obtained results reveal that the extended ecological cruise control can significantly reduce the energy consumption of an electric vehicle.

A linear-time algorithm for minimum-time velocity planning of autonomous vehicles

Abstract: Velocity planning on a path to be followed by a wheeled autonomous vehicle may be difficult when high curvatures and velocities are allowed. A fast, straightforward algorithm to address this problem is presented. It has linear-time computational complexity and provides an optimal minimumtime velocity profile. The algorithm is based on a curvilinear discretization that makes easy to take into account the constraint on the vehicle's maximal normal acceleration. Formal proofs of the algorithm's properties are included. Two examples illustrate the proposed approach.

Design of LQR controller with big bang-big crunch optimization algorithm based on time domain criteria

Abstract: LQR controller is the most popular technique that provides an optimal control law for linear systems among the state space feedback control strategies. However, the conventional LQR controller synthesis is unfortunately an iterative process due to the trial and error approach involved in determining the parameters values of the weighing matrices Q and R. Here, the Big Bang-Big Crunch (BB-BC) optimization algorithm is used that optimizes a time domain fitness function in the design of the state feedback optimal control law and thus avoiding the repeated adjustment process of LQR parameters. In this study, a special performance fitness function that is inversely proportional to the certain time domain step response criteria of a dynamical system is proposed for the optimization procedure. In order to test the performance of the proposed method, firstly a simulation study is done within the MATLAB to stabilize an inverted pendulum on cart. Then, the proposed controller is used in a real time implementation to stabilize a DC-DC boost converter benchmark in the lab. Both MATLAB simulations and laboratory experiments demonstrate the effectiveness of the proposed controller.

On the control of energy storage systems for electric vehicles fast charging in service areas

Abstract: This paper presents a real time control strategy for energy storage systems integration in electric vehicles fast charging applications combined with generation from intermittent renewable energy sources. A two steps approach taking advantage of the model predictive control methodology is designed on purpose to optimally allocate the reference charging power while managing the priority among the plugged vehicles and then control the storage for efficiently sustaining the charging process. Two different use cases are considered: in the former the charging area is disconnected from the grid, so that the objective is to minimize the deviation of electric vehicles charging power from the nominal value; in the latter the focus is on the point of connection to the grid and the need of mitigating the related power flow. In both cases the fundamental requirement for feasible control system operation is to guarantee stability of the storage's state of charge over the time. Simulation results are provided and discussed in detail, showing the effectiveness of the proposed approach.

Biased proportional navigation with exponentially decaying error for impact angle control and path following

Abstract: In this paper, a bias term to enhance proportional navigation is designed through an error signal that is a function of pursuit angles with the objective of accommodating both the problem of impact angle control against a stationary target and the problem of path following using the virtual target concept. The design leads to a second order transfer function describing the linear error dynamics contained within the nonlinear environment. The performance of the proposed guidance law is demonstrated in a comparative simulation study that also involves a well-known trajectory shaping guidance law. Straightforward to implement with no need for time to go, the technique may be utilized in various planar scenarios involving missiles or unmanned aerial vehicles.

Modelling and control of a Tilt-Wing Unmanned Aerial Vehicle

Abstract: In this article a Tilt-Wing Unmanned Aerial Vehicle (TW-UAV) and the preliminary evaluation of its hovering characteristics in extended simulation studies are presented. In the beginning, an overview of the TW-UAV's design properties are established, highlighting the novelties of the proposed structure and the overall merits. The TW-UAV's design and structural properties are mathematically modeled and utilized for the synthesis of a cascaded P-PI and PID based control structure for the regulation of its hovering performance. In addition, extensive simulation trials are performed in order to evaluate the structure's efficiency in controlling the TW-UAV's attitude and position under various noise and disturbance scenarios.

Robust voltage regulation in islanded microgrids: A LMI based mixed H2/H ∞ control approach

Abstract: In this paper, islanded operation of a microgrid system under load uncertainties is considered using a robust control strategy. This system includes two Distributed Generation (DG) units that are connected to the local load using inverter and LC filters. The main objective is regulating the load voltage in the presence of large perturbations in the local load. To achieve the objective, a LMI-based mixed H2/H ∞ state-feedback control technique with regional pole placement is utilized for each DG. Fast tracking, zero steady-state error, and robust performance in presence of uncertainties are some of the achievements of the proposed technique. The effectiveness of the proposed method is illustrated in different operating conditions using MATLAB/SimPower System. A PWM inverter block from SimPower System toolbox is used in all simulations to implement a realistic nonlinear model of each DG.