Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle

Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wing Natureinspired (NI) FW MAV is modeled and controlled inspiring by its advanced features like quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability when contrasted with comparable-sized fixed and rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilized to demonstrate the NIFW MAV model, which has points of interest over first principle based modelling since it does not depend on the system dynamics, rather based on data and can incorporate various uncertainties like sensor error. The same clustering strategy is used to develop an adaptive fuzzy controller. The controller is then utilized to control the altitude of the NIFW MAV, that can adapt with environmental disturbances by tuning the antecedent and consequent parameters of the fuzzy system.Comment: this paper is currently under review in Journal of Artificial Intelligence and Soft Computing Researc

PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles

There exists an increasing demand for a flexible and computationally efficient controller for micro aerial vehicles (MAVs) due to a high degree of environmental perturbations. In this work, an evolving neuro-fuzzy controller, namely Parsimonious Controller (PAC) is proposed. It features fewer network parameters than conventional approaches due to the absence of rule premise parameters. PAC is built upon a recently developed evolving neuro-fuzzy system known as parsimonious learning machine (PALM) and adopts new rule growing and pruning modules derived from the approximation of bias and variance. These rule adaptation methods have no reliance on user-defined thresholds, thereby increasing the PAC's autonomy for real-time deployment. PAC adapts the consequent parameters with the sliding mode control (SMC) theory in the single-pass fashion. The boundedness and convergence of the closed-loop control system's tracking error and the controller's consequent parameters are confirmed by utilizing the LaSalle-Yoshizawa theorem. Lastly, the controller's efficacy is evaluated by observing various trajectory tracking performance from a bio-inspired flapping-wing micro aerial vehicle (BI-FWMAV) and a rotary wing micro aerial vehicle called hexacopter. Furthermore, it is compared to three distinctive controllers. Our PAC outperforms the linear PID controller and feed-forward neural network (FFNN) based nonlinear adaptive controller. Compared to its predecessor, G-controller, the tracking accuracy is comparable, but the PAC incurs significantly fewer parameters to attain similar or better performance than the G-controller.Comment: This paper has been accepted for publication in Information Science Journal 201

Toward Long-Endurance Flight- Tamkang’s Aspect of Micro Ornithopters

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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

Fixed-wing MAV attitude stability in atmospheric turbulence-part 2: Investigating biologically-inspired sensors

Challenges associated with flight control of agile fixed-wing Micro Air Vehicles (MAVs) operating in complex environments is significantly different to any larger scale vehicle. The micro-scale of MAVs can make them particularly sensitive to atmospheric disturbances thus limiting their operation. As described in Part 1, current conventional reactive attitude sensing systems lack the necessary response times for attitude control in high turbulence environments. This paper reviews in greater detail novel and emerging biologically inspired sensors, which can sense the disturbances before a perturbation is induced. A number of biological mechanoreceptors used by flying animals are explored for their utility in MAVs. Man-made attempts of replicating mechanoreceptors have thus been reviewed. Bio-inspired flow and pressure-based sensors were found to be the most promising for complementing or replacing current inertial-based reactive attitude sensors. Achieving practical implementations that meet the size, weight and power constraints of MAVs remains a significant challenge. Biological systems were found to rely on multiple sensors, potentially implying a number of research opportunities in the exploration of heterogeneous bio-inspired sensing solution

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

A Surrogate Model Approach in 2-D Versus 3-D Flapping Wing Aerodynamic Analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76107/1/AIAA-2008-5914-508.pd

Analysis and optimisation of passive flapping wing propulsion for micro aerial vehicles

Flapping wing propulsion has the potential to revolutionise the field of Micro Aerial Vehicles (MAVs), but little is known about the effect of flapping motion on the performance of flapping wings. Prototype MAVs have achieved flight with passive flapping wings moving in a sinusoidal flapping motion, but the possible benefits of alternative flapping motions have not been studied in detail. This thesis presents the development of an Integrated Testing System (ITS), which allows the evaluation of flapping wing performance for different flapping motions. A detailed parametric study of the effect of flapping motion on wing performance is performed, and the optimal flapping motion for several passive flapping wings is determined by hardware-in-the-loop optimisation of two wing performance metrics. The developed ITS was able to automatically test a variety of passive flapping wings, and demonstrated precise control of the flapping motion and accurate and repeatable measurements of average lift force, mechanical power, and wing twist angle. The parametric study revealed that of the three flapping motions tested, the sinusoidal flapping motion generated the highest lift force, but a smoothed triangular motion was able to generate lift significantly more efficiently under load. The optimal flapping motion was successfully determined for three flapping wings, and was found to increase the loaded efficiency of the wings by an average of 31% over a sinusoidal flapping motion. The determined optimal motion was almost identical for the three tested wings, and was found to strongly resemble the flapping motion of insects These findings demonstrate that significant improvements in the performance of passive flapping wings can be achieved by relatively minor variations of the flapping motion. This increased understanding will ideally lead to more efficient flapping wing MAVs with higher payloads, longer flight times, and improved performance

Unsteady Fluid Physics and Surrogate Modeling of Low Reynolds Number, Flapping Airfoils

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76621/1/AIAA-2008-3821-671.pd