43 research outputs found
Trajectory tracking control of a quadrotor UAV based on sliding mode active disturbance rejection control
This paper proposes a sliding mode active disturbance rejection control scheme to deal with trajectory tracking control problems for the quadrotor unmanned aerial vehicle (UAV). Firstly, the differential signal of the reference trajectory can be obtained directly by using the tracking differentiator (TD), then the design processes of the controller can be simplified. Secondly, the estimated values of the UAV's velocities, angular velocities, total disturbance can be acquired by using extended state observer (ESO), and the total disturbance of the system can be compensated in the controller in real time, then the robustness and anti-interference capability of the system can be improved. Finally, the sliding mode controller based on TD and ESO is designed, the stability of the closed-loop system is proved by Lyapunov method. Simulation results show that the control scheme proposed in this paper can make the quadrotor track the desired trajectory quickly and accurately.
 
Single chip solution for stabilization control & monocular visual servoing of small-scale quadrotor helicopter
This thesis documents the research undertaken to develop a high-performing design
of a small-scale quadrotor (four-rotor) helicopter capable of delivering the speed and
robustness required for agile motion while also featuring an autonomous visual servoing
capability within the size, weight, and power (SWaP) constraint package. The
state of the art research was reviewed, and the areas in the existing design methodologies
that can potentially be improved were identified, which included development
of a comprehensive dynamics model of quadrotor, design and construction of a performance
optimized prototype vehicle, high-performance actuator design, design of a
robust attitude stabilization controller, and a single chip solution for autonomous vision
based position control. The gaps in the current art of designing each component
were addressed individually. The outcomes of the corresponding development activities
include a high-fidelity dynamics and control model of the vehicle. The model
was developed using multi-body bond graph modeling approach to incorporate the
dynamic interactions between the frame body and propulsion system. Using an algorithmic
size, payload capacity, and flight endurance optimization approach, a quadrotor
prototype was designed and constructed. In order to conform to the optimized
geometric and performance parameters, the frame of the prototype was constructed
using printed circuit board (PCB) technology and processing power was integrated
using a single chip field programmable gate array (FPGA) technology. Furthermore, to actuate the quadrotor at a high update rate while also improving the power efficiency
of the actuation system, a ground up FPGA based brushless direct current
(BLDC) motor driver was designed using a low-loss commutation scheme and hall
effect sensors. A proportional-integral-derivative (PID) technology based closed loop
motor speed controller was also implemented in the same FPGA hardware for precise
speed control of the motors. In addition, a novel control law was formulated for robust
attitude stabilization by adopting a cascaded architecture of active disturbance rejection
control (ADRC) technology and PID control technology. Using the same single
FPGA chip to drive an on-board downward looking camera, a monocular visual servoing
solution was developed to integrate an autonomous position control feature with
the quadrotor. Accordingly, a numerically simple relative position estimation technique
was implemented in FPGA hardware that relies on a passive landmark/target
for 3-D position estimation.
The functionality and effectiveness of the synthesized design were evaluated by
performance benchmarking experiments conducted on each individual component as
well as on the complete system constructed from these components. It was observed
that the proposed small-scale quadrotor, even though just 43 cm in diameter, can lift
434 gm of payload while operating for 18 min. Among the ground up designed components,
the FPGA based motor driver demonstrated a maximum of 4% improvement in
the power consumption and at the same time can handle a command update at a rate
of 16 kHz. The cascaded attitude stabilization controller can asymptotically stabilize
the vehicle within 426 ms of the command update. Robust control performance under
stochastic wind gusts is also observed from the stabilization controller. Finally, the
single chip FPGA based monocular visual servoing solution can estimate pose information
at the camera rate of 37 fps and accordingly the quadrotor can autonomously
climb/descend and/or hover over a passive target
Geometric Active Disturbance Rejection Control for Autonomous Rotorcraft in Complex Atmospheric Environment
This dissertation presents several novel robust tracking control schemes of rotorcraft unmanned aerial vehicles under realistic atmospheric turbulence. To achieve fast converging and stable performance of the rotorcraft control scheme, a new H\ {o}lder-continuous differentiator, similar to the super-twisting algorithm used in the second-order sliding model control scheme, is proposed with guaranteed fast finite-time stability. Unlike the super-twisting algorithm, which uses a sliding-mode structure to achieve finite-time stability, the proposed differentiator maintains its fast finite-time stability with H\ {o}lder continuity, theoretically eliminating the harmful chattering phenomenon in practical control applications. Perturbation and noise robustness analyses are conducted for the proposed differentiator. The dissertation formulates the rotorcraft tracking control and disturbance estimation problems separately. The rotorcraft aerial vehicle is modeled as a rigid body with control inputs that actuate all degrees of freedom of rotational motion and only one degree of freedom of translational motion. The motion of the aircraft is globally represented on \TSE, which is the tangent bundle of the special Euclidean group \SE. The translational and attitude control schemes track the desired position and attitude on \SE. The disturbance estimation problem is formulated as an extended states observer on \TSE. Next, two rotorcraft control schemes on \SE with disturbance rejection mechanisms are presented. The proposed disturbance rejection control systems comprise two parts: an extended states observer for disturbance estimation and a tracking control scheme containing the disturbance rejection term to track the trajectory. The first disturbance rejection control scheme comprises an exponentially stable extended states observer and an asymptotically stable tracking control scheme. The second system comprises a fast finite-time stable extended state observer and a fast finite-time stable tracking control scheme. The fast finite-time stable extended state observer uses the \textup{H\ {o}}lder-continuous differentiator to estimate the resultant external disturbance force and disturbance torque acting on the vehicle. It ensures stable convergence of disturbance estimation errors in finite time when the disturbances are constant. Software-in-the-loop simulation is carried out for the active disturbance rejection control scheme with an open-source autopilot and a physics-based simulation tool. The simulation utilizes simulated wind gusts, propeller aerodynamics, actuator limitation, and measurement noise to validate the disturbance rejection control systems in a simulated environment with high fidelity. Two sets of flight experiments are conducted to investigate the autonomous rotorcraft flight control performance under turbulent income flows. A wind tunnel composed of fan arrays is involved in both experiments to provide different turbulent incoming flows by adjusting the duty of individual fans. The first set of experiments conducts income flow measurements for wind tunnel calibration. For the turbulent flows generated by different fan configurations, their steady velocity field and unsteady turbulence characteristics are measured by a pressure scanner and hot-wire anemometer. The second set of experiments involves flight tests of a rotorcraft within the turbulent environment measured and calibrated in the first experiment set. The proposed extended states observer is implemented onto a rotorcraft by customizing an open-source autopilot software. With this implementation, the flight control performance of the proposed disturbance rejection control schemes is presented and compared with the autopilot without customization. The experimental results show that the proposed disturbance rejection control scheme enhanced by the disturbance estimation schem
Cascaded control for balancing an inverted pendulum on a flying quadrotor
SUMMARYThis paper is focused on the flying inverted pendulum problem, i.e., how to balance a pendulum on a flying quadrotor. After analyzing the system dynamics, a three loop cascade control strategy is proposed based on active disturbance rejection control (ADRC). Both the pendulum balancing and the trajectory tracking of the flying quadrotor are implemented by using the proposed control strategy. A simulation platform of 3D mechanical systems is deployed to verify the control performance and robustness of the proposed strategy, including a comparison with a Linear Quadratic Controller (LQR). Finally, a real quadrotor is flying with a pendulum to demonstrate the proposed method that can keep the system at equilibrium and show strong robustness against disturbances.</jats:p
Fuzzy Gain-Scheduling PID for UAV Position and Altitude Controllers
Unmanned aerial vehicle (UAV) applications have evolved to a wide range of fields in the last decade. One of the main challenges in autonomous tasks is the UAV stability during maneuvers. Thus, attitude and position control play a crucial role in stabilizing the vehicle in the desired orientation and path. Many control techniques have been developed for this. However, proportional integral derivative (PID) controllers are often used due their structure and efficiency. Despite PID’s good performance, different requirements may be present at different mission stages. The main contribution of this research work is the development of a novel strategy based on a fuzzy-gain scheduling mechanism to adjust the PID controller to stabilize both position and altitude. This control strategy must be effective, simple, and robust to uncertainties and external disturbances. The Robot Operating System (ROS) integrates the proposed system and the flight control unit. The obtained results showed that the proposed approach was successfully applied to the trajectory tracking and revealed a good performance compared to conventional PID and in the presence of noises. In the tests, the position controller was only affected when the altitude error was higher, with an error of 2% lower.publishedVersio
A Metaheuristic Optimization Using Explosion Method On A Hybrid Pd2-Lqr Quadcopter Controller
The popularity of the rotorcraft type UAV, the quadrotor, has grown rapidly in
recent years due to its advantages and capability to perform various applications such
as environment monitoring, surveillance, and inspection. However, the quadrotor’s
dynamics are highly nonlinear and underactuated since it has 6 DOF that need to be
controlled by only 4 actuators. Besides, it is also crucial that the controller’s gains are
tuned appropriately since it can affect the quadrotor’s performance. This study aims to
develop an effective optimal control technique to control and stabilize the quadrotor's
altitude and attitude motion. A simulation-based experiment in MATLAB/Simulink
environment was conducted to test and verify the proposed algorithm and controller
performance. The mathematical model of the quadrotor was derived based on the
Newton-Euler approach and linearized using a small angle approximation. In this
study, a Hybrid PD2-LQR controller was proposed for quadrotor control and
stabilization. Conventionally, the controller’s gains were tuned using the trial-anderror
method. The problem with this method was that it very time-consuming, and the
control designer could never tell which gains are the optimal solution for the controller.
Therefore, an optimization algorithm based on the explosion method called REA was
proposed and implemented on the proposed Hybrid PD2-LQR control structure. A
comparative study with 8 well-known algorithms, PSO, ABC, GA, DE, MVO, MFO,
FA, and STOA, was performed to evaluate the performance of the proposed algorithm.
Similarly, the proposed controller was evaluated by a comparative study with 6
conventional controllers, PD, PID, LQR, Hybrid P-LQR, Hybrid PD-LQR, and Hybrid PD2-LQR. The findings show that the REA could perform well in exploiting the global
optimum and exploring the search space. The convergence speed of the REA was also
faster than other algorithms. Similarly, for the controller, the findings show that the
REA-based Hybrid PD2-LQR controller has a faster rise time with a shorter settling
time than the conventional controllers, while there was no overshoot and steady-state
error produced. On average, the rise time, settling time, overshoot, steady-state error
and RMSE was improved by 95%, 95.3%, 100%, 100%, and 43.5% respectively for
roll and pitch motion, while 96.5%, 96.5%, 100%, 97.2%, and 47.3% respectively for
yaw motion. For altitude motion, the rise time, settling time, overshoot, and steadystate
error were improved by 84.5%, 85.5%, 100%, and 100%, respectively. The
RMSE for altitude motion was not improved but still could be accepted since the
difference with the conventional controllers was not too much. Therefore, based on
these findings, it could be concluded that the proposed REA-based Hybrid PD2-LQR
controller was the best among the tested controller and suited for controlling and
stabilizing the quadrotor’s altitude and attitude motion since it could significantly
improve the performance of the quadrotor’s response
The Borea project: a quadrotor uav cradle-to-grave design for space gnc prototyping and testing
Unmanned Aerial Vehicles (UAVs) and, more specifically, n-copters have come to prominence in the last decade
due to their several applications. Also, in the automatic control research community UAVs have drawn great attention, since their non-linear and under-actuated nature making them suitable for testing a wide range of control
architectures and algorithms. In this paper, prominent theoretical aspects, simulations, and experimental results of the Borea project are presented. The Borea project aims at testing space guidance, navigation, and control (GNC) algorithms leveraging a simplified, rapidly prototypable, low-cost, and easy-to-test quadrotor platform. More precisely, one of the main project objectives consists in testing Moon and Mars planetary landing algorithms, thanks to the similitude, in the command authority and the landing approach, between n-copters and spacecraft; during the propulsive landing phase. Indeed, both n-copters and spacecraft can provide a thrust vector characterized by constant direction and adjustable magnitude. This similitude approach makes it possible to anticipate issues and avoid failures such as those that occurred in the Schiaparelli Mars Lander. To this aim, the complete control unit design, and the UAV plant electro-mechanical prototyping were addressed; so far. Specifically, the control unit was designed within the framework of the Embedded Model Control (EMC) methodology. The EMC design, based on an internal model, also includes the uncertainties as disturbances to be estimated and actively rejected. The Borea UAV has been endowed with a control system leveraging a wide range of automatic control concepts, ranging from modelling, identification, and linear and non-linear control laws, to deal with its position, velocity, and attitude regulation. To sum up, all these results were achieved by means of a properly structured cradle-to-grave design process which, starting from the simultaneous plant modelling and prototyping, ended up with a complete flight tests campaign. Most notably, the testing process involved intensive numerical simulations as well as multi-stage hardware/plant tests and models validation. From the control perspective, the several developed controllers were tuned and tested, via proper simulations and on-purpose flight tests, aiming at validating, from time to time, specific functionalities and control performances. Finally, some results coming from high-fidelity simulations, the hardware and model testing, and in-flight operations are provided to underline the most relevant aspects of the Borea plant and the control
unit performance