Nonlinear control and synchronization of multiple Lagrangian systems with application to tethered formation flight spacecraft

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 217-228).This dissertation focuses on the synchronization of multiple dynamical systems using contraction theory, with applications to cooperative control of multi-agent systems and synchronization of interconnected dynamics such as tethered formation flight. Inspired by stable combinations of biological systems, contraction nonlinear stability theory provides a systematic method to reduce arbitrarily complex systems into simpler elements. One application of oscillation synchronization is a fully decentralized nonlinear control law, which eliminates the need for any inter-satellite communications. We use contraction theory to prove that a nonlinear control law stabilizing a single-tethered spacecraft can also stabilize arbitrarily large circular arrays of tethered spacecraft, as well as a three-spacecraft inline configuration. The convergence result is global and exponential due to the nature of contraction analysis. The proposed decentralized control strategy is further extended to robust adaptive control in order to account for model uncertainties. Numerical simulations and experimental results validate the exponential stability of the tethered formation arrays by implementing a tracking control law derived from the reduced dynamics.(cont.) This thesis also presents a new synchronization framework that can be directly applied to cooperative control of autonomous aerospace vehicles and oscillation synchronization in robotic manipulation and locomotion. We construct a dynamical network of multiple Lagrangian systems by adding diffusive couplings to otherwise freely moving or flying vehicles. The proposed tracking control law synchronizes an arbitrary number of robots into a common trajectory with global exponential convergence. The proposed control law is much simpler than earlier work in terms of both the computational load and the required signals. Furthermore, in contrast with earlier work which used simple double integrator models, the proposed method permits highly nonlinear systems and is further extended to adaptive synchronization, partial-joint coupling, and concurrent synchronization. Another contribution of the dissertation is a novel nonlinear control approach for underactuated tethered formation flight spacecraft. This is motivated by a controllability analysis that indicates that both array resizing and spin-up are fully controllable by the reaction wheels and the tether motor. This work reports the first propellant-free underactuated control results for tethered formation flight.(cont.) We also fulfill the potential of the proposed strategy by providing a new momentum dumping method. This dissertation work has evolved based on the research philosophy of balancing theoretical work with practicality, aiming at physically intuitive algorithms that can be directly implemented in real systems. In order to validate the effectiveness of the decentralized control and estimation framework, a new suite of hardware has been designed and added to the SPHERES (Synchronize Position Hold Engage and Reorient Experimental Satellite) testbed. Such recent improvements described in this dissertation include a new tether reel mechanism, a force-torque sensor and an air-bearing carriage with a reaction wheel. This thesis also introduces a novel relative attitude estimator, in which a series of Kalman filters incorporate the gyro, force-torque sensor and ultrasound ranging measurements. The closed-loop control experiments can be viewed at ...by Soon-Jo Chung.Sc.D

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

A neural network-based inversion method of a feedback linearization controller applied to a hydraulic actuator

In this work, we use a neural network as a substitute for the traditional analytic functions employed as an inversion set in feedback linearization control algorithms applied to hydraulic actuators. Although very efective and with strong stability guarantees, feedback linearization control depends on parameters that are difcult to determine, requiring large amounts of experimental efort to be identifed accurately. On the other hands, neural networks require little efort regarding parameter identifcation, but pose signifcant hindrances to the development of solid stability analyses and/or to the processing capabilities of the control hardware. Here, we combine these techniques to control the positioning of a hydraulic actuator, without requiring extensive identifcation procedures nor losing stability guarantees for the closed-loop system, at reasonable computing demands. The efectiveness of the proposed method is verifed both theoretically and by means of experimental results

Development of Robust Control Laws for Disturbance Rejection in Rotorcraft UAVs

Inherent stability inside the flight envelope must be guaranteed in order to safely introduce private and commercial UAV systems into the national airspace. The rejection of unknown external wind disturbances offers a challenging task due to the limited available information about the unpredictable and turbulent characteristics of the wind. This thesis focuses on the design, development and implementation of robust control algorithms for disturbance rejection in rotorcraft UAVs. The main focus is the rejection of external disturbances caused by wind influences. Four control algorithms are developed in an effort to mitigate wind effects: baseline nonlinear dynamic inversion (NLDI), a wind rejection extension for the NLDI, NLDI with adaptive artificial neural networks (ANN) augmentation, and NLDI with L1 adaptive control augmentation. A simulation environment is applied to evaluate the performance of these control algorithms under external wind conditions using a Monte Carlo analysis. Outdoor flight test results are presented for the implementation of the baseline NLDI, NLDI augmented with adaptive ANN and NLDI augmented with L1 adaptive control algorithms in a DJI F330 Flamewheel quadrotor UAV system. A set of metrics is applied to compare and evaluate the overall performance of the developed control algorithms under external wind disturbances. The obtained results show that the extended NLDI exhibits undesired characteristics while the augmentation of the baseline NLDI control law with adaptive ANN and L1 output-feedback adaptive control improve the robustness of the translational and rotational dynamics of a rotorcraft UAV in the presence of wind disturbances

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Dynamic modeling and control of a Quadrotor using linear and nonlinear approaches

With the huge advancements in miniature sensors, actuators and processors depending mainly on the Micro and Nano-Electro-Mechanical-Systems (MEMS/NEMS), many researches are now focusing on developing miniature flying vehicles to be used in both research and commercial applications. This thesis work presents a detailed mathematical model for a Vertical Takeo ff and Landing (VTOL) type Unmanned Aerial Vehicle(UAV) known as the quadrotor. The nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method, the formulated model is detailed including aerodynamic effects and rotor dynamics that are omitted in many literature. The motion of the quadrotor can be divided into two subsystems; a rotational subsystem (attitude and heading) and a translational subsystem (altitude and x and y motion). Although the quadrotor is a 6 DOF underactuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is underactuated. The derivation of the mathematical model is followed by the development of four control approaches to control the altitude, attitude, heading and position of the quadrotor in space. The fi rst approach is based on the linear Proportional-Derivative-Integral (PID) controller. The second control approach is based on the nonlinear Sliding Mode Controller (SMC). The third developed controller is a nonlinear Backstepping controller while the fourth is a Gain Scheduling based PID controller. The parameters and gains of the forementioned controllers were tuned using Genetic Algorithm (GA) technique to improve the systems dynamic response. Simulation based experiments were conducted to evaluate and compare the performance of the four developed control techniques in terms of dynamic performance, stability and the effect of possible disturbances

Control and safety of fully actuated and underactuated nonlinear systems: from adaptation to robustness to optimality

The state-of-the-art quadratic program-based control Lyapunov-control barrier function (QP-CLBF) is a powerful control approach to balance safety and stability in a pointwise optimal fashion. However, under this approach, modeling inaccuracies may degrade the performance of closed-loop systems and cause a violation of safety-critical constraints. This thesis extends the recently-developed QP-CLBF through the derivation of five novel robust quadratic program-based adaptive control approaches for fully actuated and underactuated nonlinear systems with a view toward adapting to unknown parameters, being robust to unmodeled dynamics and disturbances, ensuring the system remains in safe sets and being optimal with respect in a pointwise fashion. Simulation and quantitative results demonstrate the superiority of proposed approaches over the baseline methods.Ph.D

Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance