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Modern plantation forest procedures still rely heavily on manual data acquisition in the inventory process, limiting the quantity and quality of the collected data. This limitation in collection performance is often due to the difficulty of traversing the plantation forest environment on foot. This work presents an autonomous system for exploring plantation forest environments using multi-rotor UAVs. The proposed method consists of three parts: waypoint selection, trajectory generation, and trajectory following. Waypoint selection is accomplished by estimating the rows’ locations within the environment and selecting points between adjacent rows. Trajectory generation is completed using a non-linear optimization-based constant speed planner and the following is accomplished using a model predictive control approach. The proposed method is tested extensively in simulation against various procedurally generated forest environments, with results suggesting that it is robust against variations within the scene. Finally, flight testing is performed in a local plantation forest, demonstrating the successful application of our proposed method within a complex, uncontrolled environment.

This paper describes the design of an unmanned aerial vehicle (UAV) mounted system for recording sound from a targeted source or direction with a minimum amount of noise. The objective of the study is: i) select an optimum electric motor-propeller combination which minimises the level of unwanted noise from these components at the microphone positions; ii) design a microphone array configuration suitable for installation on a UAV; and iii) develop a signal processing algorithm that significantly reduces noise in the recording. The designed system was prototyped and tested in various scenarios simulated in an anechoic chamber as well as by recordings collected from a system mounted on a hovering UAV. The system succeeded in reducing the propeller noise level up to approximately 12 dB compared to the recording by a shotgun microphone. Results of subjective listening tests suggest the quality of the recording made by the designed UAV mounted system is significantly better than that of the recording by the shotgun microphone.

SUMMARYThe Mecanum wheel is one of the practical omni-directional wheel designs in industry, especially for heavy-duty tasks in a confined floor. An issue with Mecanum-wheeled robots is inefficient use of energy. In this study, the robotic motion trajectories are optimized to minimize the energy consumption, where a robotic path is expressed in polynomial functions passing through a given set of via points, and a genetic algorithm is used to find the polynomial’s coefficients being decision variables. To attempt a further reduction in the energy consumption, the via points are also taken as decision variables for the optimization. Both simulations and experiments are conducted, and the results show that the optimized trajectories result in a significant reduction in energy consumption, which can be further lowered when the via points become decision variables. It is also found that the higher the order of the polynomials the larger the reduction in the energy consumption.

The ability of multirotor UAVs to hold position accurately in a turbulent wind environment is important for a variety of commercial applications. In this work, a tilted-rotor configuration which offers the potential for improved disturbance rejection capability over traditional multirotor designs is presented, along with a design process to select optimal design parameters and components for a particular payload and hover time. The design process integrates models of UAV components and performance based off manufacturer data, and is applied to a range of payloads to explore resulting designs and trends. From the components considered used in this work, the tilted-rotor concept is found to provide the most benefit at payloads under 10 kg, and negligible benefit at payloads above 12 kg.

This paper describes a novel multirotor unmanned aerial vehicle aerodynamic force model with the aim of creating a multirotor simulation that is suitable for the evaluation of station-keeping perfo...

Aerial manipulation applications involve a physical interaction between an unmanned aerial vehicle and its operating environment. This paper presents the novel application of physical coupling between an aerial manipulator and tree toward semiautonomous canopy sampling. Interactions with unconstrained objects have been studied extensively; however, trees are a complex environment with unique and naturally varying mechanical characteristics. Such interactions have not appeared in the previous literature so the effects remain unknown, thus warranting this study. First, an aircraft-tree branch interaction model is introduced using known aircraft dynamic modeling methods and a specially developed tree branch mechanical model, representing environmental disturbances to the aircraft. Coupling behavior with a range of canopy branches is investigated in both simulation, and experimentally with the aid of motion capture. The case of interactions with a swaying quasi-rigid tree stem is also explored. These respective studies have revealed station-keeping flight performance while coupled with flexible branches, and bounded environmental motion interactions where force closure does not exist. The use of conventional PID control is also validated for branch-coupled flight. Furthermore, a comparison of simulation and experimental results has shown that coupling behavior is adequately represented by mechanical effects captured in the developed tree branch model.

This paper proposes a novel method to approximate the ideal internal dynamics state trajectories which coincide with accurate output tracking for known non-minimum phase nonlinear systems. The proposed approach resembles the stable system centre method, but uses a lower order dynamic system than the stable system centre to generate an approximation of the ideal internal dynamics state trajectories. This approximate stable system centre is used to construct a sliding mode based output tracking controller which can achieve improved transient response at the cost of some tracking accuracy in comparison to the use of the stable system centre. The effectiveness of the proposed approach has been demonstrated considering the position control of a two-wheeled robot and has been found to be promising.

Individual pitch control and trailing edge flaps have been shown to be capable of reducing flapwise fatigue loads on wind turbine blades, with research to date focusing on controller development and performance assessment. This work covers development of a blade optimisation process which integrates synthesis of individual pitch and trailing edge flap controllers to evaluate their impact on the levelised cost of energy. The optimisation process selects blade chord, twist and material distributions, along with the spar cap width, and integrates a turbine cost and mass model with existing simulation codes. Constraints based on ultimate stresses, fatigue damage, blade deflection, resonant frequency, and rotor thrust are considered. Using the NREL 5 MW reference turbine as an initial point, reductions in the levelised cost of energy of 1.05% are obtained with collective pitch control only, while the addition of individual pitch control increases this reduction to 1.17%. The use of trailing edge flaps on top of individual pitch control increases the reduction in the levelised cost of energy to 1.27%. Blade mass and material cost reductions from 13.6 to 16.4% and 18.1–21.5% respectively are also obtained. Optimised blade designs are driven by blade deflection, rotor thrust and ultimate stresses in the spar cap.

This paper presents an alternative approach for nonlinear trajectory-tracking control of quadrotor unmanned aerial vehicles (UAVs) based on analytical dynamics and quaternion theories. The equations of motion of constrained mechanical systems are reinterpreted as a solution for obtaining an explicit nonlinear control law. In addition, practical control aspects and the impact of nonidealities are investigated by providing qualitative and quantitative comparisons between simulated and experimental results. Numerical simulations demonstrate the efficacy of the proposed controller to track desired trajectories with very small tracking error for simple as well as aggressive or sharp trajectories. Using common open-source solutions, real-world implementation feasibility, performance, and limitations of the control method are discussed.

This paper investigates a novel approach for under-canopy exploration of plantation forests by exploiting the semi-structured nature of typical plantation forests by using tree stems as navigation cues within the environment. A simulation-based study is completed with the proposed method compared to the nearest frontier exploration method to determine relative performance using distance traveled as a surrogate for time. Results show our proposed method could explore an equivalent area with a shorter and more consistent travel distance across multiple runs. Testing also suggests further improvements to the strategy are possible within a plantation with culled stems.

Multirotor UAVs currently suffer from endurance issues due to limited battery capacity, greatly limiting their use for surveillance tasks in fields such as agriculture. To remedy this, we have developed a system used for perching of multirotor UAVs onto farm posts. The paper consists of two major sections: design and testing of a perching mechanism and design and testing of a computer vision based system for automated landing. Static experiments and flight testing of the completed system suggests that the design can withstand wind forces once perched and landing success is directly linked to the landing accuracy of the craft. However, performance of the controller was unsatisfactory during tests with wind, where further work could be completed.

As multirotor unmanned aerial vehicles (UAVs) increase in popularity and more complex applications are investigated, the ability to reliably and repeatably perform free-flight tests is becoming increasingly important. This paper thus describes the development and characterisation of an experimental setup for testing multirotors in a wind tunnel. The open-jet wind tunnel used is 3.5 m high and the width of its walls at the output can be changed between 2.5 and 7 m in order to adjust the mean speed of the wind produced. A grid is placed in front of the jet in order to increase turbulence and a motion capture system is used to provide accurate pose information to the UAV. Wind speeds up to 5.2 and 8.6m/s are found to be possible in the wide and narrow output wall configurations respectively. The frequency content of the wind is analysed and found to provide suitable excitation for a typical UAV. Finally, results from a typical station keeping experiment are presented to demonstrate the effectiveness of the system.

The station-keeping performance of multirotor UAVs in a turbulent wind field is of importance for a number of applications where close proximity to objects in the environment is expected. In this work, a tilted-rotor UAV which is able to generate horizontal forces without attitude changes is analysed over a range of wind speeds expected to be encountered in operation. The analysis process integrates aerodynamic models obtained from experimental tests, and compares the magnitude and bandwidth of the horizontal thrust force able to be generated by the tilted-rotor concept against a conventional UAV with rotors oriented along a common axis. It is found that while the tilted-rotor UAV is not able to generate as much thrust in the horizontal plane compared to conventional actuation involving attitude changes, it is able to offer an actuation bandwidth one order of magnitude greater than that of conventional actuation. The synergistic combination of both actuation methods on a single UAV thus has the potential to lead to improved station-keeping performance, while reducing high frequency attitude corrections.

Active load reduction strategies such as individual pitch control (IPC) and trailing edge flap (TEF) actuation present ways of reducing the fatigue loads on the blades of wind turbines. This may enable development of lighter blades, improving the performance, cost effectiveness and viability of future multi-megawatt turbine designs. Previous investigations into the use of IPC and TEFs have been limited to turbines with ratings up to 5 MW and typically investigate the use of these load reduction strategies on a single turbine only. This paper extends the design, implementation and analysis of individual pitch and TEFs to a range of classically scaled turbines between 5 and 20 MW. In order to avoid designing controllers which favour a particular scale, identical scale-invariant system identification and controller design processes are applied to each of the turbines studied. Gain-scheduled optimal output feedback controllers are designed using identified models to target blade root load fluctuations at the first and second multiples of the rotational frequency using IPC and TEFs respectively. The use of IPC and TEFs is shown in simulations to provide significant reductions in fatigue loads at the blade root. Fatigue loads on non-rotating components such as the yaw bearing and tower root (yaw moment) are also reduced with the use of TEFs. Individual pitch performance is seen to be slightly lower on larger turbines, potentially due to a combination of reduced actuator bandwidth and movement of the rotational frequency of larger turbines into a more energetic part of the turbulent spectrum. However, TEF performance is consistent irrespective of scale. Copyright © 2015 John Wiley & Sons, Ltd.

T HE development of high-efficiency engines and the introduction of composite light-weight materials and fly-by-wire systems has led to significant advances in the capability and versatility of small, ducted-fan aircraft [1,2]. Coupled with the benign stall characteristics, improved reliability and maneuverability of these aircraft, modern ducted-fan rotor-craft are being promoted as a viable alternative tomore traditional vertical take-off and landing configurations in a range of operating theaters [1,3].While thework of [4,5] has provided considerable insight into ducted-fan performance issues, tip leakage and inlet separation considerations continue to define the performance characteristics of these aircraft [6]. A number of research programs have been established to address these limitations and a wide range of control methodologies have been employed [7– 9]. Much of the existing work, however, pertains to small, single ducted-fan aircraft. Further, the use of handling qualities criteria is largely restricted to the assessment of unmanned ducted-fan configurations offering relaxed requirements on the transientmotion; or, as in the case of the BellX-22 and Doak VZ-4, those aircraft capable of independent orientation of the duct. One ducted-fan configurationwhich has received little attention by researchers is the Martin Jetpack (Fig. 1). Analyzing the handling qualities of the aircraftwithin the hover and low speedoperating regime, this paper presents the development of an optimal, multivariable flight control law. The objectives of this study are two-fold: 1) to identify the feasible design space of a novel, manned, twin ducted-fan aircraft based on predicted and expected levels of flying qualities; and, 2) to determine compliance of the augmented systemwith civil and military aviation requirements for manned, partially attended operation of the aircraft in good useable cue environments. The Martin Jetpack is a short range, small footprint prototype aircraft that was developed as a solution for personalized flight. The aircraft is equipped with two high-solidity fixed pitch fans and a 150 kilowatt two stroke engine. Attitude and translational rate control is achieved by deflection of the thrust vector via orientation of control vanes placed within the exhaust stream of each duct. Control of the aircraft is complicated by a large aerodynamic pitching and rolling moment, low inertia and large aerodynamic drag forces.

This paper presents the development of an object path following algorithm for a quadcopter using on-board vision and localization. This development aims to increase capabilities of autonomous unmanned aerial vehicles (UAV), with the use of object path following. By following an object's path, reliance on obstacle avoidance strategies can be reduced, under the assumption that the object's path is free of static obstacles. Relative position of the target has been estimated using onboard processing and monocular vision. On-board localization has been achieved through dead-reckoning, where velocity estimates are calculated from optical flow. Horizontal positional estimates with a standard deviation of 6.5cm have been achieved experimentally with this method. The use of optical flow allows for localization in GPS-denied environments. Both the position and path following can successfully run in moderate winds and variable lighting. The UAV can station- keep to within 40 cm of desired position. The object's path can be followed with an rms error of 28 cm and maximum deviation of 78 cm.

The spar-buoy floating wind turbine is one of the three main floating wind turbine concepts and one of the first to proceed to a full-scale prototype stage. Multiobjective linear state feedback controllers are implemented on the spar-buoy floating wind turbine with individual blade pitching (IBP). The spar-buoy's deep draft results in a low platform pitch and roll natural frequencies. The low-frequency pitch and roll modes interact with other low-frequency modes of the system (i.e., surge and sway, respectively). Therefore, the linear state-space model used for control design must include the surge and sway degrees of freedom. Furthermore, a low platform pitch natural frequency limits the effectiveness of IBP at regulating the platform pitch around the first tower fore-aft (FA) resonant frequency. Simulations using a high-fidelity model are carried out according to design load case 1.2 of the IEC-61400-3 standard for fatigue load testing under normal operating conditions. Simulation results relative to a gain-scheduled proportional-integral controller show that a multiobjective state feedback controller is able to reduce tower FA and side-side bending fatigue loads by an average of 9%. This improvement is mainly due to IBP despite its limited effectiveness around the first tower FA resonant frequency.

Following development of the canopy sampling aerial manipulator prototype, modeling and characterization work has been conducted towards the creation of an accurate dynamic simulation for all phases of the canopy sampling operation. The system model has been divided between aircraft, manipulator and environment to facilitate independent characterization and validation. An experimental methodology was favored to accurately represent the real system, and these results form a major contribution of the paper. With this model, some preliminary simulations are discussed for free-flight and coupled flight. Future work is proposed to improve and experimentally validate the complete model via flight tests, thus permitting its intended use as a supplementary tool for tasks such as flight controller tuning.

In the past decade, there has been much more research in two-wheeled robots which actively stabilize themselves. Various models and controllers have been applied both to explain and control the dynamics of two-wheeled robots. We explore the methods which have been investigated and the controllers which have been used, first for balancing and movement of two-wheeled robots on flat terrain, then for two-wheeled robots in other situations, where terrain may not be flat, where there may be secondary objectives and where the robots may have additional actuators.

An attempt to record speech signals using an array of directional microphones carried by an unmanned aerial vehicle (UAV) is reported. The speech enhancement algorithm estimates the power spectral densities (PSD) of the target speech and rotor noise which are used to calculate a Wiener filter for extracting the target speech. The calculated Wiener filter is then applied to the output of a beamforming implemented on the microphone array signals. The proposed algorithm was tested on a prototype UAV equipped with directional microphones each of which was orientated in different directions. The experimental results revealed that the proposed method was able to significantly reduce both the UAVs rotor noise and an interfering speech in a recording.

This paper presents an Unmanned Aerial System (UAS) for precision forestry applications. The UAS is capable of performing fully autonomous flights under the canopies of an unknown plantation forest by avoiding obstacles without the use of GPS navigation. The navigation framework of this system consists of a velocity estimator and an obstacle avoidance controller. In particular, the velocity estimator estimates raw velocity measurements from the 2D laser scanner using the Point-to-Line Iterative Corresponding Point (PLICP) scan matching algorithm and then fuses the filtered raw velocity measurements with readings from other on-board sensors using an Extended Kalman Filter (EKF). A high-level obstacle avoidance controller is realized by creating a local artificial potential field near the UAS, based on the goal point and nearby obstacles. The performance of the UAS is quantified using indoor and outdoor tests. During the outdoor test, in which the UAS flew autonomously for approximately 28 m within a stand of trees, the minimum distance between the obstacles and UAS was 1.38 m.

This paper investigates the rejection of wind disturbances of an Unmanned Aerial Vehicle (UAV). UAVs are used for increasingly complex operations that require a great deal of accuracy and minimal position changes. This calls for better disturbance rejection. The drag-inclusive dynamics of a quadcopter are derived and used to create two uniaxial wind disturbance rejection controllers: a disturbance accommodating controller (DAC) and a nonlinear feedforward controller. Both controllers are integrated into an open-source flight controller. The performance of the controllers is assessed in simulation against the unmodified baseline. Over a 60 second loiter test, the DAC and nonlinear controllers result in a 45 % and 66 % decrease in error compared to the baseline respectively. Both controllers are shown to react to wind more rapidly. However, the DAC is found to be affected by changes in wind speed due to its linear nature. The baseline controller is used to show the feasibility of rejecting the effects of a 5 meters per second wind in a physical experiment.

Development of an aerial manipulator prototype for canopy sampling is presented. As part of addressing the unique challenges of operating in a forest canopy environment, the prototype features an offset-mounted manipulator. The first steps of flight experiments have been conducted in an attempt to determine the viability of an off-the-shelf PID flight control implementation — acceptable performance would negate the need to use more complex implementations. Indoor testing has been conducted with the aid of motion capture in-the-loop to alleviate inertial sensing uncertainties. This work investigates the two simplest dynamic phases of a sampling operation: position holding during free-flight, and position holding whilst the arm is moving.

The Mecanum wheel, due to its omnidirectional mobility and heavy-duty transporting ability on the ground plane, is widely applied in the industry. However, the Mecanum wheel trades off energy efficiency for maneuverability. This paper proposes a novel energy consumption model of the four-wheel omnidirectional Mecanum mobile robots. The model is built based on a comprehensive understanding of the kinematics, dynamics, and energy flow of the Mecanum mobile robot. The energy consumption model has been mathematically implemented in MATLAB, and experimentally validated on Auckbot, the Mecanum mobile robot, developed in our lab. Simulation and experimental results show that for omnidirectional motion primitives on the ground plane, the energy consumption model has over 98% accuracy. This proposed energy consumption model is essential to the energy-optimal motion planning for the Mecanum mobile robot.

Accurate modelling of transient wind turbine wakes is an important component in the siting of turbines within wind farms because of wake structures that affect downwind turbine performance and loading. Many current industry tools for modelling these effects are limited to empirically derived predictions. A technique is described for coupling transient wind modelling with an aero-elastic simulation to dynamically model both turbine operation and wake structures. The important feature of this approach is a turbine model in a flow simulation, which actively responds to transient wind events through the inclusion of controller actions such as blade pitching and regulation of generator torque. The coupled nature of the aero-elastic/flow simulation also allows recording of load and control data, which permits the analysis of turbine interaction in multiple turbine systems. An aero-elastic turbine simulation code and a large eddy simulation (LES) solver using an actuator disc model were adapted for this work. Coupling of the codes was implemented with the use of a software framework to transfer data between simulations in a synchronous manner. A computationally efficient simulation was developed with the ability to model turbines exhibiting standard baseline control operating in an offshore environment. Single and multiple wind turbine instances were modelled in a transient flow domain to investigate wake structures and wake interaction effects. Blade loading data were analysed to quantify the increased fluctuating loads on downwind turbines. The results demonstrate the successful implementation of the coupled simulation and quantify the effect of the dynamic-turbine model. Copyright © 2012 John Wiley & Sons, Ltd.

As wind turbines become larger and hence more flexible the design of adv anced controllers to mitigate fatigue damage and optimise power capture is becoming increasingly important. The majority of the existing literature focuses on feedback controllers which use measurements from the turbine itself and possibly an estimate or measurement of the current local wind profile. This work investigates a predictive controller which can use s hort-term predictions about the approaching wind field in order to improve performance by compensating for measur ement and actuation delays. Simulations are carried out using the FAST aeroelastic design code modelling the NREL 5MW reference turbine, and controllers are designed for both above and below rated wind conditions using Model Predictive Control. Tests are conducted in various wind conditions and with different future wind information available. It is shown that in above rated wind conditions, significant fatigue load reductions are possible compare d with a controller which knows only the current wind profile. However, this is very much dependent on the speed of the p itch actuator response and the wind conditions. In below rated wind conditions the goals of power capture and fatigue load control were considered separately. It was found that power capture could only be improved using wind predictions if the wind speed changed rapidly during the simulation and that fatigue loads were not consistently reduced when wind predictions were available, indicating that wind predictions are of limited benefit in below rated wind conditions. Copyright c 2010 John Wiley & Sons, Ltd.

To improve the energy efficiency of the Mecanum wheel, this article extends the dynamic window approach by adding a new energy-related criterion for minimizing the power consumption of autonomous mobile robots. The energy consumption of the Mecanum robot is first modeled by considering major factors. Then, the model is utilized in the extended dynamic window approach–based local trajectory planner to additionally evaluate the omnidirectional velocities of the robot. Based on the new trajectory planning objective that minimizes power consumption, energy-reduction autonomous navigation is proposed via the combinational cost objectives of low power consumption and high speed. Comprehensive experiments are performed in various autonomous navigation task scenarios, to validate the energy consumption model and to show the effectiveness of the proposed technique in minimizing the power consumption and reducing the energy consumption. It is observed that the technique effectively takes advantage of the Mecanum robot’s redundant maneuverability, can cope with any type of path and is able to fulfil online obstacle avoidance.

Floating wind turbines offer a feasible solution for going further offshore into deeper waters. However, using a floating platform introduces additional motions that must be taken into account in the design stage. Therefore, the control system becomes an important component in controlling these motions. Several controllers have been developed specifically for floating wind turbines. Some controllers were designed to avoid structural resonance, while others were used to regulate rotor speed and platform pitching. The development of a periodic state space controller that utilizes individual blade pitching to improve power output and reduce platform motions in above rated wind speed region is presented. Individual blade pitching creates asymmetric aerodynamic loads in addition to the symmetric loads created by collective blade pitching to increase the platform restoring moments. Simulation results using a high-fidelity non-linear turbine model show that the individual blade pitch controller reduces power fluctuations, platform rolling rate and platform pitching rate by 44%, 39% and 43%, respectively, relative to a baseline controller (gain scheduled proportional–integral blade pitch controller) developed specifically for floating wind turbine systems. Turbine fatigue loads were also reduced; tower side–side fatigue loads were reduced by 39%. Copyright © 2009 John Wiley & Sons, Ltd.

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non-linearities in a wind turbine system, the use of non-linear model-based controllers has the potential to increase control performance. A non-linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive-train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive-train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non-linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.

The design and development of an autonomous camera platform for skydiving is presented. The device was designed to be compact, lightweight, and aerodynamically stable. Behavior of the device under a nominal wind speed at varying angles of attack, was obtained through Computational Fluid Dynamics analysis (CFD). A prototype was constructed for the purpose of verifying the CFD and simulation models. Wind tunnel testing was conducted, verifying the aerodynamic stability and roll performance when compared to open-loop simulations. An experimental test in a vertical wind tunnel proved inconclusive due to high turbulence and swirl.

Increasing research into aerial manipulation technology has widened the scope of possible applications for unmanned aircraft. One such application that is introduced in this paper is above-canopy sampling in forests. A preliminary study has investigated the problem experimentally as a means of determining a representative scenario whilst identifying key issues. These issues include relative position sensing and control of the aerial manipulation system, which is subjected to coupling disturbances from both the manipulator and forest canopy environment. Methodology for achieving a fully-autonomous system is proposed and initial modelling and simulation has been conducted as the first step toward future control design and testing, and future development of a physical prototype.

A Mecanum-wheeled robot benefits from great omni-direction maneuverability. However it suffers from random slippage and high-speed vibration, which creates electric power safety, uncertain position errors and energy waste problems for heavy-duty tasks. A lack of Mecanum research on heavy-duty autonomous navigation demands a robot platform to conduct experiments in the future. This paper introduces AuckBot, a heavy-duty omni-directional Mecanum robot platform developed at the University of Auckland, including its hardware overview, the control system architecture and the simulation design. In particular the control system, synergistically combining the Beckhoff system as the Controller-PC to serve low-level motion execution and ROS as the Navigation-PC to accomplish highlevel intelligent navigation tasks, is developed. In addition, a computer virtual simulation based on ISG-virtuos for virtual AuckBot has been validated. The present status and future work of AuckBot are described at the end.

This paper investigates the modelling and control of step traversal using a two-wheeled robot (TWR). The traversal of TWRs over steps and other uneven terrain requires large platform tilt angles to adjust the centre of mass. This process is highly nonlinear, which complicates the controller design process. An auxiliary reaction wheel actuator is used in a novel way to facilitate step traversal. A mathematical model of step ascent is derived and used to create a feedback linearisation controller. The performance of the controller is assessed in simulation against a baseline controller from literature. The feedback linearisation controller yields significant improvements in tracking performance, with a decrease in tracking error of up to 86% when climbing a step in 1 second. Furthermore, the effects of varying the ascent conditions on performance are assessed. The controller is shown to operate over a large range of ascent times and reference tilt angles.

Pitching the individual blades of a horizontal-axis wind turbine allows control of asymmetric aerodynamic loads, which in turn influences structural loads in the nonrotating frame such as tower side-side bending. These loads are not easily controlled by traditional collective pitch algorithms. This paper presents the design of individual pitch control systems for implementation on the Controls Advanced Research Turbine (CART) in Colorado to verify controller performance for load attenuation. The control designs are based on linear time-periodic state-space models of the turbine and use optimal control methods for gain calculation. Comparisons are made between new individual pitch, new collective pitch, and baseline controller performance in both above rated and below rated wind conditions. Results from simulations show the potential of individual pitch to reduce tower side-side fatigue damage in above rated wind speeds (by 70% compared to baseline control) but with no improvement over collective pitch in below rated wind speeds. Fatigue load reductions in tower fore-aft, shaft torsion, and blade flap are also observed. From 13h of field testing, both collective and individual pitch controllers achieve a reduction in fatigue damage. However, the superior performance of individual pitch control observed in simulation was not verified by the field test results.

Performance of a model-based periodic gain controller for wind turbines is presented using Disturbance Accommodating Control (DAC) techniques to estimate fluctuating wind disturbances. The control objective is to regulate rotor speed at above-rated wind speeds while mitigating cyclic blade root loads. Actuation is via individual blade pitch, and sensors are limited to rotor angle and speed. The modeled turbine is a two-bladed, downwind machine with simple blade and tower flexibility having four degrees of freedom. Comparisons are made to a time-invariant DAC controller and to a proportional-integral-derivative (PID) design. Simulations are performed using a fluctuating wind input and a nonlinear turbine model. Results indicate that the state-space control designs are effective in reducing blade loads without a sacrifice in speed regulation. The periodic controller shows the most potential because it uses a time-varying turbine model to estimate unmeasured states. The use of additional sensors to help reconstruct the blade flap rate can significantly improve the level of load attenuation, as witnessed in full-state feedback results.

A composite linear state-space controller was developed for a multi-objective problem in the variable-speed operation of wind turbines. Disturbance Tracking Control theory was applied to the design of a torque controller to optimize energy capture under the influence of persistent wind disturbances. A limitation in the theory for common multi-state models is described; this led to the design of a complementary pitch controller. The goal of the independent blade pitch design was to minimize blade root fatigue loads. A SymDyn model of a two-bladed, 600-kW machine was used for the simulation studies. Results indicate a 24% reduction in blade fatigue damage using the proposed controllers, compared to a conventional torque-only design. However, energy capture was not improved as much as expected, partly due to nonlinearity effects degrading the performance of the state-space estimator design. Tower base fatigue damage was shown to decrease significantly using active pitch.

This paper examines the operating modes of a two-bladed wind turbine structural model. Because of the gyroscopic asymmetry of its rotor, this turbine’s dynamics can be quite distinct from that of a turbine with three or more blades. This asymmetry leads to system equations with periodic coefficients that must be solved by the Floquet approach to extract the correct modal parameters. A discussion of results is presented for a series of simple models with increasing complexity. We begin with a single-degree-of-freedom system and progress to a model with seven degrees-of-freedom: tower fore-aft bending, tower lateral bending, tower twist, nacelle yaw, hub teeter, and flapwise bending of each blade. Results illustrate how the turbine modes become more dominated by the centrifugal and gyroscopic effects as the rotor speed increases. Parametric studies are performed by varying precone angle, teeter stiffness, yaw stiffness, teeter damping, and yaw damping properties. Under certain levels of yaw stiffness or damping, the gyroscopic coupling may cause yaw and teeter mode coalescence, resulting in self-excited dynamic instabilities. Teeter damping is the only parameter found to strictly stabilize the turbine model.

This paper presents the design and development of a single degree-of-freedom Active Balance Board (ABB) for progressive ankle rehabilitation. The stiffness and damping of the system can be varied through the gains of the implemented Proportional Derivative (PD) controller. The aim of this initial research is to tune the ABB to match the transient characteristics of a classic balance board (CBB). The dynamics of a CBB have not previously been defined and so this paper outlines the derivation for its equations of motion. Results are presented which validate that the performance of the ABB can match the CBB in the unloaded condition as well as with a 50kg subject. A method to objectively quantify the difficulty of balancing is proposed and this demonstrates the feasibility of controlling the performance of the ABB based on the clinical needs of the individual patient.

The development of an object tracking controller for a quadcopter using an on-board vision system is presented. Using low-cost components, a novel system is introduced that operates entirely on board the quadcopter, without external localization sensors or GPS. A low-frequency monocular computer vision algorithm is applied in closed-loop control to track an object of known color. Parallel PID controllers for aircraft bearing, relative height and range are implemented with feedback from object offset and size in the image frame. The noise exaggerated by measuring range from object pixel area is mitigated with a Kalman filter. Stable closed-loop tracking is demonstrated experimentally for all three control axes when tested individually and coupled together. Individual settling times were under 10 seconds and coupled control settling times under 25 seconds.

An investigation of the performance of a model-based periodic gain controller is presented for a two-bladed, variable-speed, horizontal-axis wind turbine. Performance is based on speed regulation using full-span collective blade pitch. The turbine is modeled with five degrees-of-freedom; tower fore-aft bending, nacelle yaw, rotor position, and flapwise bending of each blade. An attempt is made to quantify what model degrees-of-freedom make the system most periodic, using Floquet modal properties. This justifies the inclusion of yaw motion in the model. Optimal control ideas are adopted in the design of both periodic and constant gain full-state feedback controllers, based on a linearized periodic model. Upon comparison, no significant difference in performance is observed between the two types of control in speed regulation.

A review of the most important contributions made towards designing and testing controllers for floating wind turbines is presented in this chapter. These controllers range in complexity, description detail, simulation results and testing styles, and floating platform structure. Furthermore, they have not yet been compared against each other quantitatively using the same simulation conditions. However, the attributes of each control approach documented in the literature are listed in this chapter. Several approaches that deal with the reduction of platform pitch damping are discussed such as the use of individual blade pitching and tuned mass dampers.

Two-wheeled mobile robots (TWMRs) have a capability of avoiding the tip-over problem on inclined terrain by adjusting the centre of mass position of the robot body. The effects of terrain inclination on the robot performance are studied to exploit this capability. Prior to the real-time implementation of position control, an estimation of the stability region of the TWMR is essential for safe operation. A numerical method to estimate the stability region is applied and the effects of inclined surfaces on the performance and stability region of the robot are investigated. The dynamics of a TWMR is modelled on a general uneven terrain and reduced for cases of inclined and horizontal flat terrain. A full state feedback (FSFB) controller is designed based on optimal gains with speed tracking on a horizontal flat terrain. The performance and stability regions are simulated for the robot on a horizontal flat and inclined terrain with the same controller. The results endorse a variation in equilibrium points and a reduction in stability region for robot motion on inclined terrain.

Accurate modelling of wind turbine wakes in a wind farm is an important feature of developing wind farm layouts. This paper discusses a new technique for coupling wind and turbine modelling with an aero-elastic simulation to dynamically model turbine wakes and responses in a wind farm. The advantage of this approach is a turbine model in a simulation domain with the ability to actively respond to transient wind events through the inclusion of a controller. The coupled nature of the aero-elastic/ow simulation also allows recording of load and control data allowing analysis of single and multiple turbine systems. An aero-elastic turbine modelling code and a research LES code were chosen for this work. The research focused on developing a computationally ecient simulation with the ability to model a turbine exhibiting standard baseline control operating in a turbulent Atmospheric Boundary Layer (ABL) such as that observed in an o-shore environment. Multiple wind turbine instances were introduced to a transient ow domain to investigate wake structures and interaction eects between turbines. Results show the successful implementation of a coupled simulation. Preliminary results indicate the signicance of the controller and demonstrate signicant turbine interaction eects in simulations with multiple turbines. This work demonstrates promising techniques to increase the delity of transient modelling of turbulence and wake structures in wind farms for better prediction of load uctuations and power decits.

A large-eddy simulation code has been used to model the atmospheric boundary layer flowing through a pair of wind turbines. The wind turbines are modeled as actuator discs, with the disc loadings being calculated by a coupled wind turbine simulation code, FAST. In addition to modeling a steady wind, the case of an extreme gust passing through the farm is simulated. The persistence of the gust structure suggests the possibility of designing turbine controllers based partially on upstream information.

In this work, the possibility of using a predictive yaw controller to face a wind turbine into the wind, in order to reduce yaw misaligned and hence increase power capture, is investigated. Two such controllers are presented, one created by modifying a typical feedback yaw controller to include wind direction predictions, and one based on Model Predictive Control. Both controllers are evaluated in simulation with the assumption of perfect wind direction predictions up to 60s ahead. Both achieve at least an 8% increase in total power capture in below rated wind conditions in the presence of a large change in wind direction, and increases of approximately 0.5% during one hour of real turbulent wind. Reductions in structural fatigue damage equivalent loads were also observed due to reduced asymmetric aerodynamic loads. It is suggested that such a yaw control scheme may provide bene ts in a wind farm where wind direction swings can be predicted as they move through the farm.