Dynamics and Control of Satellite Relative Motion in Proximity Operations

In this dissertation, the development of relative navigation, guidance, and control algorithms of an autonomous space rendezvous and docking system are presented. These algorithms are based on innovative formulations of the relative motion equations that are completely explicit in time. The navigation system uses an extended Kalman filter based on these formulations to estimate the relative position and velocity of the chaser vehicle with respect to the target vehicle and the chaser attitude and gyro biases. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system, along with the star tracker and gyro measurements of the chaser. The corresponding measurement models, process noise matrix, and other filter parameters are provided. The guidance and control algorithms are based on the glideslope used in the past for rendezvous and proximity operations of the Space Shuttle with other vehicles. These algorithms are used to approach, flyaround, and to depart from a target vehicle in elliptic orbits. The algorithms are general and able to translate the chaser vehicle in any direction, decelerate while approaching the target vehicle, and accelerate when moving away. Numerical nonlinear simulations that illustrate the relative navigation, attitude estimation, guidance, and control algorithm\u27s, as well as performance and accuracy are evaluated in the research study

Optimization of driving mode switching strategy for a multimode plug-in hybrid electric vehicle

Hybrid electric vehicles have become increasingly popular recently. Switching from internal combustion engine to battery as a clean source of energy is considered as a solution to reduce city pollution due to vehicle emissions. PHEV is a viable balance between the two sources of energy to achieve higher fuel economy with lower emissions. For a multimode PHEV, the car switches among three operation modes; namely electric mode, series mode, and parallel mode to maximize fuel economy based on the driving conditions. In this work, minimization of fuel consumption is used to optimize the mode switching strategy for a PHEV. The study is conducted using a reference vehicle that resembles 2014 Honda Accord Plug-in Hybrid vehicle. Global optimization with constraints using pattern search method is utilized. Starting from a switching strategy with 〖MPG〗_e = 30, optimization increased fuel economy to 〖MPG〗_e = 51.4 for a combined cycle (FTW75 and HWFET). Optimization proved to be a feasible method to improve mode switching strateg

Relative motion guidance, navigation and control for autonomous orbital rendezvous

In this paper, the dynamics of the relative motion problem in a perturbed orbital environment are exploited based on Gauss’ variational equations. The relative coordinate frame (Hill frame) is studied to describe the relative motion. A linear high fidelity model is developed to describe the relative motion. This model takes into account primary gravitational and atmospheric drag perturbations. In addition, this model is used in the design of a control, guidance, and navigation system of a chaser vehicle to approach towards and to depart from a target vehicle in proximity operations. Relative navigation uses an extended Kalman filter based on this relative model to estimate the relative position and velocity of the chaser vehicle with respect to the target vehicle and the chaser attitude and gyros biases. This filter uses the range and angle measurements of the target relative to the chaser from a simulated Light Detection and Ranging (LIDAR) system, along with the star tracker and gyro measurements of the chaser. The corresponding measurement models, process noise matrix and other filter parameters are provided. Numerical simulations are performed to assess the precision of this model with respect to the full nonlinear model.The analyses include the navigations errors, trajectory dispersions, and attitude dispersions

Dynamics and control of quadcopter using linear model predictive control approach

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory

A Model Predictive Control (MPC) approach on unit quaternion orientation based quadrotor for trajectory tracking

The objective of this paper is to introduce with a quaternion orientation based quadrotor that can be controlled by Model Predictive Control (MPC). As MPC offers promising performance in different industrial applications, quadrotor can be another suitable platform for the application of MPC. The present study consistently adopts unit quaternion approach for quadrotor orientation in order to avoid any axes overlapping problem, widely known as singularity problem whereas Euler angle orientation approach is unable to resolve so. MPC works based on the minimal cost function that includes the attitude error and consequently, the cost function requires quaternion error in order to proceed with process of MPC. Therefore, the main contribution of this study is to introduce a newly developed cost function for MPC because by definition, quaternion error is remarkably different from the attitude error of Euler angle. As a result, a unit quaternion based quadrotor with MPC can ascertain a smooth singularityfree flight that is influenced by model uncertainty. MATLAB and Simulink environment has been used to validate the cost function for quaternion by simulating several trajectories

DYNAMICS AND CONTROL OF MINI AERIAL VEHICLE USING MODEL PREDICTIVE CONTROL

Nowadays Mini Aerial Vehicles (MAVs) are popular in many areas such as aerial photography, inspection, surveillance and search and rescue missions in complex and dangerous environments due to their low cost, small size, superior mobility, and hover capability. Multifarious applications of MAVs inspire researchers to concentrate on different types of controllers like linear, nonlinear or learning-based. The attention of this work is to design a robust controller and to develop an accurate mathematical model of Quadrotor, a type of MAV as it behaves roughly in uncertain environments. Quadrotor is an under-actuated and highly nonlinear system with six degrees of freedom (DOF). The mathematical model of quadrotor is derived based on Newton-Euler method that includes aerodynamic drag and moment that are sometimes overlooked in literatures. For higher precision modelling, model uncertainties are also included in the system. In addition, the kinematic model is derived utilizing Euler angles and Quaternion methods. Quaternion approach has the advantage of singularity free orientation while Euler angles are easy to visualize. This work investigates the performance of three different controllers which includes Proportional-Integral-Derivative (PID), Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC) based on several performance evaluation factors. PID offers fast response to the system comparing to other controllers although choosing proper gain is challenging for PID. However, it cannot handle directly under-actuated system and due to the fact, some states are required to be decoupled. LQR ensures fast response and can deal with Multiple Input Multiple Output (MIMO) system at the same time. The main drawback of the LQR controller is its incapability of dealing with steady-state error. Conversely, MPC has the functionalities of dealing with MIMO system with constraints and uncertainties while other controllers fail. The performance of the controllers are presented based on tracking accuracy using Root Mean Square Error (RMSE) method and control stability using control input norm method. MATLAB and Simulink environment is considered to carry out the simulations. Based on simulated experiments, it is found that MPC could track the trajectories more accurately with stable control effort comparing to PID controllers and LQR

Trajectory tracking of quaternion based quadrotor using model predictive control

The aim of this paper is to introduce the trajectory tracking with a quaternion based quadrotor operation using model predictive con-trol (MPC). Since the efficacy of MPC on a system under noise and disturbance has been distinguished, it is a fair and successful attempt to apply MPC on the quaternion based quadrotor, which is a quite well-known system with uncertainties during operation. Quaternion approaches singularity-free orientation that is advantageous to design any trajectory for quadrotor wherein roll or pitch angle reaches at 90o. As a quaternion, with its four-tuple characteristics that incorporate vector elements, is different from Euler-angle orientation, a new cost function has been developed for the respective MPC controller. In order to achieve singularity-free ori-entations and abate the model infidelity of the system, the quaternion and MPC algorithm have been incorporated for quadrotor flight. Simulation based results elucidate the success of trajectory tracking of quaternion based dynamics of quadrotor using MPC approach

Guidance solutions for multiple vehicle assembly

This paper exploits the guidance algorithms to assembly multiple vehicle in close proximity. The objective is to move each vehicle in the assembly to its final location. The guidance laws are determined such that, each vehicle should attract to the others on long distances and avoid collision with them in short distances. These laws are based on Lyapunov’s second method that utilize the potential function theory to insure the stability of the assembly process. Numerical investigations were performed for different configurations of the assembly. The proposed algorithms may prove useful for future mission applications such as satellite formation flying, structures assembly in space and mobile robots control

Relative motion guidance, navigation and control for autonomous spacecraft rendezvous

In this paper, the development of guidance, navigation, and control algorithms of an autonomous space rendezvous and docking system are presented. These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. The navigation system uses an extended Kalman filter based on Tschauner-Hempel equations to estimate the relative position and velocity of the chaser vehicle with respect to the target vehicle. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system. The corresponding measurement models, process noise matrix and other filter parameters are provided. The guidance and control algorithms are based on the glideslope used in the past for rendezvous and proximity operations of the Space Shuttle with other vehicles. These algorithms are used to approach, flyaround, and to depart form a target vehicle in elliptic orbits. The algorithms are general and able to transfer the chaser vehicle in any direction, decelerate while approaching the target vehicle, and accelerate when moving away. Numerical nonlinear simulations that illustrate the relative navigation, guidance, and control algorithms performance and accuracy are evaluated in the current paper

Relative motion and autonomous rendezvous in Keplerian elliptic orbits

In this paper, the analytical closed-form solution of the Tschauner-Hempel equations that are used for rendezvous in elliptic orbits are studied and exploited. The solution is based on a state transition matrix that is completely explicit in time. Autonomous guidance algorithms to approach, to flyaround, and to depart from a target vehicle in elliptic orbits are exploited based on that solution. The algorithms are general and able to translate the chaser vehicle in any direction, decelerate while approaching the target vehicle, and accelerate when moving away. These guidance algorithms are based on the glideslope used in the past for rendezvous and proximity operations of the Space Shuttle with other vehicles. The algorithms are applied to the problem of terminal rendezvous near any Keplerian elliptic orbit in a Newtonian gravitational field showing the effects of target orbit eccentricity on the relative motion. These algorithms extend and generalize previously published solutions. Numerical simulations confirm the brevity and accuracy of the general solutions developed in the current paper