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Art of electronics

We describe a prototype 75 g micro quadrotor with onboard attitude estimation and control that operates autonomously with an external localization system The motivation for designing quadrotors at this scale comes from two observations First, the agility of the robot increases with a reduction in size, a fact that is supported by experimental results in this paper Second, smaller robots are able to operate in tight formations in constrained, indoor environments We describe the hardware and software used to operate the vehicle as well our dynamic model We also discuss the aerodynamics of vertical flight and the contribution of ground effect to the vehicle performance Finally, we discuss architecture and algorithms to coordinate a team of these quadrotors, and provide experimental results for a team of 20 micro quadrotors

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Towards a swarm of agile micro quadrotors

In this paper, the problem of sensitivity reduction by feedback is formulated as an optimization problem and separated from the problem of stabilization. Stable feedback schemes obtainable from a given plant are parameterized. Salient properties of sensitivity reducing schemes are derived, and it is shown that plant uncertainty reduces the ability of feedback to reduce sensitivity. The theory is developed for input-output systems in a general setting of Banach algebras, and then specialized to a class of multivariable, time-invariant systems characterized by n × n matrices of H? frequency response functions, either with or without zeros in the right half-plane. The approach is based on the use of a weighted seminorm on the algebra of operators to measure sensitivity, and on the concept of an approximate inverse. Approximate invertibility of the plant is shown to be a necessary and sufficient condition for sensitivity reduction. An indicator of approximate invertibility, called a measure of singularity, is introduced. The measure of singularity of a linear time-invariant plant is shown to be determined by the location of its right half-plane zeros. In the absence of plant uncertainty, the sensitivity to output disturbances can be reduced to an optimal value approaching the singularity measure. In particular, if there are no right half-plane zeros, sensitivity can be made arbitrarily small. The feedback schemes used in the optimization of sensitiviiy resemble the lead-lag networks of classical control design. Some of their properties, and methods of constructing them in special cases are presented.

Feedback and Optimal Sensitivity: Model Reference Transformations, Multiplicative Seminorms, and Approximate Inverses

This book, by two of the key people who have developed rigorous methods in the arena of Intelligent Control, provides a long-awaited overall perspective that unifies nonlinear network approximators and adaptive control techniques. The focus of the book is continuous-time adaptive systems. The text consists of eight chapters. Some of the topics discussed include: approximation theory; approximation structures used in Intelligent Control; methods for formulating parametric models; extensions to nonlinear control architectures; control of nonlinear scalar systems; an all-purpose theory of adaptive approximation-based control for general nonlinear systems; and applications to controls design for fixed-wing aircraft. Exercises and design problems at the end of each chapter magnify the usefulness of this book. Intuitive clarity of exposition and mathematical rigor are extremely well-balanced to provide a book that can be used to introduce these concepts to a graduate student class or to industry engineers, and yet also satisfy the most demanding of theoreticians.

Adaptive Approximation Based Control-Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches-[Book review; J. A. Farrell and M. M. Polycarpou]

In this paper, the trajectory tracking control problem of a six-degree of freedom (6-DOF) quadrotor unmanned aerial vehicle (UAV) with input saturation is studied. Applying a hierarchical control structure, a priori-bounded control thrust and the desired orientations are derived to stabilize the translational subsystem without singularities. By using a backstepping approach with a Nussbaum function, a priori-bounded control torque for the rotational subsystem is designed to track the desired orientations generated by the translational subsystem. With the proposed control scheme, the latent singularities in the attitude extraction process caused by saturation nonlinearities are avoided, and globally uniformly ultimately bounded (UUB) stability of the closed-loop system is achieved. The tracking error bound is further determined which can be made arbitrarily small by tuning certain control gains. Numerical simulation results are provided to show the effectiveness of the proposed control scheme.

Trajectory tracking control of a 6-DOF quadrotor UAV with input saturation via backstepping

This paper presents the development of a generic OBD device and its working with different vehicles based on OBD-TT standards like Land Rover Defender This device shows the real time vehicle system status, including vehicle speed, engine RPM, throttle position, battery voltage, engine coolant temperature etc and the diagnostic trouble codes (DTCs) for different vehicles The software has also been indigenously developed which is used as interface between user and the ECU of the vehicle This device helps the user to understand the vehicle status and check malfunctions by indicating the Diagnostic Trouble Codes (DTCs) This generic device can prove as an easy to use, battery free device that drives power from the vehicle battery and is easily connected to the PC using USB port

Development of an On-Board Diagnostic (OBD) kit for troubleshooting of compliant vehicles

In this paper, we proposed a neural-network-based adaptive controller to adapt against unknown, possibly time varying, external disturbances for a quadrotor UAV. The proposed algorithm can estimate uncertain forces, which occurs when ying in narrow areas, near walls and/or other surfaces, so that the controller can maintain satisfactory position tracking performance despite these disturbances. A proof for stability with the proposed algorithm is provided. Experimental results show that, with the proposed NN based adaptation algorithm, position tracking performance of quadrotor UAV shows satisfactory improvement in presence of external disturbances.

Adaptive Control for a VTOL UAV Operating Near a Wall

A This paper presents a position tracking control system for a shape memory alloy (SMA) actuator using neural network (NN) feedforward and robust integral of signum of error (RISE) feedback. Nonlinear control of SMA actuators is difficult due to model uncertainties and unknown disturbances. Discontinuous control techniques such as sliding mode control have conventionally been used to achieve asymptotic tracking in the presence of model uncertainties. However, such discontinuous controllers usually result in increased power loss due to high frequency switching. With the recent development of the continuous RISE feedback control, semi-global asymptotic tracking can be achieved. Furthermore, the NN-RISE control leads to better tracking performance and lower power losses caused by input signal switching/chattering when compared to discontinuous controllers. In order to apply the NN-RISE, a state-space model of the SMA actuator is derived, which has been overlooked in many previous works, using Taylor series expansion and exploiting the nature of SMA dynamics. Experimental results show that the proposed control system works well even in the absence of an accurate model of the SMA actuator.

Adaptive control of a shape memory alloy actuator using neural-network feedforward and RISE feedback

This paper discusses the development of a customizable FPGA based system for implementing control algorithms on an Unmanned Ground Vehicle (UGV) and its 5 Degree of Freedom (DOF) manipulator. The compact RIO-9012 is used as a controller which is a reconfigurable embedded control and acquisition system using LabVIEW as the programming platform. The developed system enables the control of UGV and its manipulator using a remote joystick controller via Wi-Fi communication. Apart from Joystick, the system can also be controlled optionally using a keyboard. Accuracy of Joystick control has been enhanced by using point to point mapping technique. A user friendly GUI has been developed to view live video feedback obtained from the onboard cameras to control the UGV accordingly. Different features of UGV like path tracker (tracks its path on Google Maps), variable speed modes, battery indicator, camera switch and selector etc. are also managed in the GUI. The system has been developed so that, in future, it can easily be extended to a fully autonomous system.

Development of FPGA-based system for control of an Unmanned Ground Vehicle with 5-DOF robotic arm

In this work, we apply an adaptive observer for estimating the thrust generated by the individual rotors of a quadrotor UAV with uncertain actuator parameters, using a linear dynamic model of the system. In most of the previous works, the implementation of quadrotor control is based on the assumption of a known static relationship between the voltage signal to the motors and the thrust generated by the actuator-propeller assembly. However, due to variations in this voltage-to-thrust relationship, this approach may lead to undesirable results in practice. Feedback of the quadrotor thrust in the control system can provide more robustness to the system. In the absence of accurate knowledge of the actuator parameters, we use an adaptive observer for thrust estimation in this work. An adaptive observer is an algorithm for joint estimation of states and unknown parameters of a dynamical system. We use the adaptive Luenberger observer using two different cost functions, and apply a genetic algorithm to select the design parameters of the observer. We use low- and higher-order models for the actuator with the adaptive observer, and compare their performance. The results show that the estimates from the adaptive observer used with a low-order actuator model match the thrust values obtained from measurements with good accuracy.

Asad Ullah Awan

Papers

Development of an On-Board Diagnostic (OBD) kit for troubleshooting of compliant vehicles

Adaptive Control for a VTOL UAV Operating Near a Wall

Adaptive control of a shape memory alloy actuator using neural-network feedforward and RISE feedback

Development of FPGA-based system for control of an Unmanned Ground Vehicle with 5-DOF robotic arm

Thrust estimation of quadrotor UAV using adaptive observer