Reaction Wheels Research Articles

Reaction Wheel Torque Distribution Algorithm for Enhancing the Agility of the Spacecraft using Null motion

Earth observation satellites require rapid attitude maneuvering and stringent pointing accuracy for imaging payloads. Four numbers of Reaction Wheel (RW) are usually configured in standard tetrahedral configuration for attitude manoeuvring as well as for fine pointing. The Reaction wheel maximum torque is one of the critical parameters that determine the agility of the spacecraft. Three axis attitude control torque signal is distributed to 4 Reaction wheels using standard pseudo inverse solution which minimizes the sum of the square of the individual wheel torque rather than the maximum of the individual wheel torque. The pseudo inverse solution leads to wheel saturation even when the total momentum does not reach the envelope and there by limiting the agility of the spacecraft. In this paper, new approach is adopted to optimally utilize the full capacities of RWs and thereby enhancing the agility of the spacecraft. The new algorithm is based on the null motion of the reaction wheel torque alignment matrix. The proper choice of the null vector results in equal wheel torque demand when combining with the pseudo inverse solution. The maneuver & control algorithms are integrated together with new distribution method and have been demonstrated for typical rest to rest and rate to rate maneuver.

Control of an Orbital Manipulator with Reaction Wheels for On-orbit Servicing

In on-orbit servicing missions, a spacecraft equipped with a manipulator arm grasps a client satellite. Afterwards, the momentum-dumping phase follows and the manipulator can be utilized for servicing tasks. Once the momentum has been dumped, a desired manipulator configuration and base attitude may be needed for initializing a servicing phase such as berthing. The proposed approach prioritizes the attitude maintenance of the servicer spacecraft, and reconfigures the manipulator arm with the grasped client satellite in the nullspace of the servicer's attitude. The approach utilizes the redundancy in rotational degrees of freedom, provided by reaction wheels, to decouple the manipulator reconfiguration task from the attitude of the servicer-base. The proposed controller shows convergence of the attitude and joint-level task, independent of kinematic singularities of the manipulator arm. Additionally, the problem of speed saturation of the reaction wheels is tackled by increasing the damping torques as a function of the wheel speed. Simulation results verify the effectiveness of the proposed control approach.

Adaptive Fault Tolerant Attitude Control of a Nano-Satellite with Three Magnetorquers and One Reaction Wheel

In this paper, a passive fault tolerant attitude control is investigated for a nano-satellite with three magnetorquers and one reaction wheel in the presence of actuator constraints, external disturbances, and partial loss of actuator effectiveness as unknown actuator faults. For this purpose, a variable structure control approach is employed due to its ability to deal with the partial loss of actuator effectiveness and adjusting the maximum amplitude of the control signal by a control gain. A modified sliding variable is designed based on angular velocity and attitude errors with an adaptive parameter coefficient. The dynamics equation of the adaptive parameter is extracted during the stability proof of the closed-loop system. Changing the value of this parameter changes the effect intensity of the quaternion errors on the sliding variable and causes the attitude errors to maintain within a limited range. Applying this parameter to the modified sliding variable makes the controller perform well even if the adaptive parameter is significantly reduced. Furthermore, directly using the adaptive parameter in the structure of control law makes the controller generate a chattering-free torque. Comparing the simulation results with the results of two variable structure control methods designed in previous articles shows that its performance in attitude tracking commands has improved. In addition, Monte Carlo simulations with random actuator faults are performed to show the robustness of the proposed controller in the presence of actuator constraints and external disturbances.

Posture control of one-link torque unit manipulator using reaction wheel with air resistance

Posture control of one-link torque unit manipulator using reaction wheel with air resistance

Observer Design for an Inertia Wheel Pendulum with Static Friction

A state observer design for the inertia wheel pendulum considering static friction of the actuated inertia disc is presented. The frictional force is modeled by the Stribeck effect, with two separate differential equations describing the sticking and non-sticking system, respectively. The transition between the two scenarios is in general determined by a static friction condition. Three proposed observers are designed for both the sticking and non-sticking model. Depending on the probability of the respective model given a current measurement, the more likely is selected for state estimation. The performance is demonstrated on a laboratory demonstrator, where the observers including the proposed probabilistic model selection are compared.

Study and Analysis of Dual Mode Operation of Single DC Motor (Series and Separately Excitation Modes)

This paper presents a novel idea of a method to run DC series motor and then into DC separately excited mode and vice versa during operation. The purpose of this paper is to give an analysis of a real-time study performed experimentally for both series and separately excited operation of DC motor. The DC motor initially started in series mode giving high torque at a constant load in the form of an inertia wheel as starting load. The motor is then switched to separately excited DC mode with the help of switches after attaining the required number of rpm or speed. High speed with sufficient torque and good controllability is observed in separately excited DC motor mode. Eventually, this system has been proven with experimental results and proposed for numerous applications, especially where high starting torque and less speed are required and after that, high speed is required. Analyzing results with the help of MATLAB previously, a hardware-based real-time operating system has been provided. This setup can be proposed for various applications such as battery-operated DC machines especially Electric Vehicles and off-road Electric Vehicles and Solar powered applications as well.

Data-Driven Observer Design for an Inertia Wheel Pendulum with Static Friction

An indirect data-driven state observer design approach for the inertia wheel pendulum considering static friction of the actuated inertia disc is presented. The frictional forces occurring in a real laboratory setup are characterized by the Stribeck effect as well as the transition between two different dynamic behaviors, sticking and non-sticking. These switching nonlinear dynamics are identified with various machine learning methodologies in a data-driven manner, i.e., the unsupervised separation and feature clustering of measured state trajectories into two dynamic classes, and the supervised classification of a state-dependent switching condition. The identified system with the interior switching-structure of two dynamics is combined with a moving horizon estimator.

Robust Passivity-Based Control of Underactuated Systems via Neural Approximators and Bayesian Inference

Inspired by passivity-based control (PBC) techniques, we propose a data-driven approach in order to learn a neural net parameterized storage function of underactuated mechanical systems. First, the PBC problem is cast as an optimization problem that searches for point estimates of the neural net parameters. Then, we improve the robustness properties of this deterministic framework against system parameter uncertainties and measurement error by injecting techniques from Bayesian inference. In the Bayesian framework, the neural net parameters are samples drawn from a posterior distribution learned via Variational Inference. We demonstrate the performance of the deterministic and Bayesian trainings on the swing-up task of an inertia wheel pendulum in simulation and realworld experiments.

Stabilization of an Inverted Pendulum on a Nonholonomic System

In this paper we investigate the problem of stabilizing the roll dynamics of a nonholonomic system that is inspired by a Chaplygin sleigh whose center of mass is at some height above the ground. The sole actuation for the extruded Chaplygin sleigh, is via the motion of an internal reaction wheel which applies a torque in the yaw direction. This torque is used to propel the Chaplygin sleigh as well as stabilize its roll. This system is motivated by the problem of the stabilization of the roll of a fish-like underwater swimmer. The dynamics of a fish-like swimmer have been shown to be similar to that of a Chaplygin sleigh. We propose a feedback control, by considering the associated linear representation due to the action of a Koopman operator on the observables. Using the Koopman operator, a constrained optimal control problem is formulated in the lifted space which we solve using model predictive control. The approach has the advantage of being systematically generalized for increased model complexity for nonholonomic systems and actuator saturation.

Selection of Geometric Parameters of an Reaction Wheel System Positioning when Controlling the Angular Motion of a Spacecraft

Selection of Geometric Parameters of an Reaction Wheel System Positioning when Controlling the Angular Motion of a Spacecraft

Curriculum-based reinforcement learning for path tracking in an underactuated nonholonomic system

Underactuated mechanical systems with nonholonomic constraints find applications in bioinspired robotics, such as snake-like robots and more recently in fish-like aquatic robots. Animal locomotion suggests that in such bioinspired robots, gaits or cyclic changes in kinematics or shape variables lead to efficient and agile motion. Path tracking in such nonholonomic systems that are not purely kinematic can be a challenging problem. In this paper we consider the problem of path tracking by a modified Chaplygin sleigh with a ‘tail’ which is a four degree of freedom nonholonomic system, possessing a single internal reaction wheel as an actuator. We develop a curriculum based deep Reinforcement Learning (RL) optimal control approach for simultaneous velocity and path tracking for this system. The curriculum based learning approach first leads to a policy for optimal tracking of limit cycles in a reduced velocity space and then in a next step to track a path. This curriculum approach allows an RL agent to learn the ’mechanics on invariant manifolds’ of the system and can be a useful approach in the motion control of high degree of freedom robots with increasing model complexity.

Novel viscoelastic vibration isolating methods in space technology: A review

In the space application, various dynamic loads are applied during the launching and onboard phase. Satellites undergo various dynamic loads during separation from spacecraft and due to self- excited vibration or engine cut off during the launch phase. These loads generate random vibrations which can lead to malfunction of components. Viscoelastic materials are generally used in reducing thermal stresses, hence keeping the system closer to optimal working temperature. Viscoelastic materials are generally classified as fluids with high viscosity which enhances the effects of vibration absorption and isolation. This is done by the virtue of incompressibility of fluids. Novel materials, viz., air, oil, water, etc., are generally a popular choice due to efficient working couple with cost effectiveness. Viscoelastic materials have an advantage of being a passive isolator and hence they have excellent energy dissipation capacity to reduce micro vibration. The major materials such as rubber, elastomer, cork, foam and laminates in the form of pads or sheets are kept under the heavy equipment, heavy audio setup and delivery items. However, among all other materials, a novel material sorbothane pad has shown more promising application with better performance. It can be concluded that the isolation system consisting of a sorbothane pad can effectively reduce the micro-vibrations of the reaction wheel in the spacecraft and camera set up to enhance the image quality.

Magnetic spacecraft attitude stabilization with two torquers

Magnetic control has been used successfully for momentum management and attitude control when pointing precision requirements are loose. Typically, such systems are constructed using configurations of magnetic coils oriented in a way to provide command authority by varying the magnetic moment about all three body axes. Although magnetic control actuators and related systems are typically robust and not as prone to failure when compared to reaction wheels or thrusters, it is of interest to see if coarse 3-axis attitude pointing can be achieved with the loss of control about one of the 3 axes of magnetic moment actuation. These types of cases could occur during the normal life of the spacecraft or could also occur intentionally on very small satellites where space is limited, so any control modes that could prolong the life of a damaged satellite or intentionally underactuated satellite would be useful for some missions. This paper demonstrates the feasibility of 3-axis pointing of spacecraft using only two axes of magnetic moment actuation using linear time varying analysis to provide sufficient conditions for controllability. The paper then develops an LQR-based controller for these two torquer cases. Finally, the paper concludes with simulations that indicate it is feasible to control with only two axes of magnetic moment, although with the expected increased time to achieve targeted attitudes and reduced disturbance rejection.

DEVELOPMENT OF INTELLIGENT SELF-BALANCING E-BIKE USING MACHINE LEARNING

The self-driving autonomous cars is becoming an increasingly popular concept all around the world but the area of self-driving two wheelers is still under developed. For developing countries like India, two wheelers are affordable than cars for most of the population. The project aims at developing intelligent self-balancing bike using artificial intelligence because the major problem in developing an autonomous bike is in the area of balancing. Even though there are many working mechanisms available for self-balancing of bike, the implementation of AI will be an edge over others from the point of computational power requirement and the programming complexity incurred. A prototype of the bike was developed with reaction wheel mechanism for self-balancing. The mechanism was fully controlled by AI by preventing the need of explicit programming for balancing which was the earlier technique used in self-balancing bike. Reinforcement learning, a type of machine learning technique is adopted for this purpose. The policy gradient algorithm was used to make the bike learn by itself for balancing. Even though the AI algorithm worked well in the virtual environment (balancing a cart-pole) it fails in the real environment. (i.e. it fails to balance the bike). It is because of the noisy data from the sensor, which gives inaccurate information about the orientation of the bike. The noise in the data is due to the vibration of the body when the reaction wheel rotates. This could be solved if the AI is fed with accurate information about the orientation of the vehicle.

Kalman filter identification method for micro-vibration transfer paths of satellites

Micro-vibrations on-board a satellite have degrading effects on the performance of certain payloads like observation cameras. The major sources of vibrations include momentum wheels, solar array drives, other rotary mechanical equipment, etc. These vibrations result in loss of the pointing precision and image quality of the payload through intricate transfer paths. To improve the accuracy of a satellite system with many vibration sources and complex transfer paths, it is necessary to determine the main transfer path of vibration. In this study, a path identification method is proposed and applied to the transfer system from the momentum wheel to the camera mount. First, the observer/Kalman filter identification (OKID) algorithm is used to acquire the state-space equation of each path subsystem. Then, the subsystem order is obtained based on the slope of the singular entropy increment. In the next phase, combined with the measured disturbance force of the momentum wheel, the displacement response of the target point is predicted. Finally, the dominant transfer path of vibration is achieved by calculating the vibration contribution of each path to the response point. The results indicate that the dominant transfer path is the axial path of the horizontal momentum wheel, which contributes to the vibration of the camera mount at most. Effective vibration reduction measures should be taken to this path to suppress the vibration signal. In comparing the identified displacement response with the finite element response of the camera mount under different noise conditions, the correlation coefficients are >0.85, which proves the accuracy and anti-noise capability of the identification method.

Reliability Modeling and Analysis of Multi-Degradation of Momentum Wheel Based on Copula Function

The momentum wheel is a key component of the satellite attitude control system and has a direct impact on the reliability and overall life of the satellite. The momentum wheel has the characteristics of a high reliability, long life, and complex failure mechanics, which leads to expensive maintenance and a low reliability of the test sample. Therefore, it is challenge to implement an accelerated life test. The traditional life data statistical method has great difficulty in solving the reliability analysis of the momentum wheel. A reliability calculation method based on copula function for multi-degradation is proposed. Firstly, the key factors affecting the reliability of the momentum wheel are analyzed, and the lubricant residual quantity and current are selected as the degradation quantity. Secondly, the wiener process is used to model the degradation of a single degradation quantity, and the edge distribution function of the momentum wheel reliability is obtained. Considering that the correlation between multiple degradation quantities has a non-negligible influence on the reliability analysis result, the copula function is introduced to describe the correlation, and the edge distributions are fused to obtain the joint distribution function of the momentum wheel reliability.

Planar Formation Control of a School of Robotic Fish: Theory and Experiments

This paper presents a nonlinear control design for the stabilization of parallel and circular motion in a school of robotic fish actuated with internal reaction wheels. The closed-loop swimming dynamics of the fish robots are represented by the canonical Chaplygin sleigh. They exchange relative state information according to a connected, undirected communication graph to form a system of coupled, nonlinear, second-order oscillators. Prior work on collective motion of constant-speed, self-propelled particles serves as the foundation of our approach. However, unlike a self-propelled particle, the fish robots follow limit-cycle dynamics to sustain periodic flapping for forward motion with time-varying speed. Parallel and circular motions are achieved in an average sense without feedback linearization of the agents’ dynamics. Implementation of the proposed parallel formation control law on an actual school of soft robotic fish is described, including system identification experiments to identify motor dynamics and the design of a motor torque-tracking controller to follow the formation torque control. Experimental results demonstrate a school of four robotic fish achieving parallel formations starting from random initial conditions.

Experimental investigation of microvibrations induced by reaction wheels on earth observation satellite

The evaluation of microvibrations effect is crucial for the success of remote sensing missions. The moving parts on the satellite such as reaction wheels can create microvibrations disturbances, which cause degradation of image quality. In our paper we present an experimental investigation methodology for on-ground quantification of wheel noise disturbance transmitted through the structure to the payload. This assessment was carried out for the ALSAT-1B satellite integrating a medium resolution payload. The angular motion along imager bore sight was measured using accelerometers and verified against image quality and mission requirement. The on ground experimental methodology suggests that the effect of microvibrations on a camera can be verified directly.

Integrated Anti-Windup Fault-Tolerant Control Architecture for Optimized Satellite Attitude Stabilization

This article presents the development of an anti-windup (AW) compensator architecture for nanosatellite systems. The design addresses the problem of fault-tolerant control (FTC) for attitude stabilization subject to actuator saturation, actuator faults, and multiple disturbances. In many practical applications, certain physical limitations in the actuator design often mean that actuator saturation is mostly unaccounted for. Based on the ESTCube-2 nanosatellite model with reaction wheels (RWs), an integrated AW–FTC architecture is designed for an optimized attitude control system. The AW compensator is formulated using the linear matrix inequality (LMI) and computed to generate an augmented solution that is appended to the linear control system. The AW compensator in the architecture is designed with suitable parameters and effective controller gain values. The AW–FTC acts on the RW momentum as control input with the observed torque response, thereby ensuring an asymptotically stable system. Simulation results are presented to demonstrate the effectiveness of this approach with finite-time stabilization under actuator faults and saturation conditions.

Distributed liquid crystal reflectivity control device network for momentum wheel unloading

AbstractMomentum wheels are widely used in spacecraft attitude control. However, in the space far‐away from the Earth, it is difficult for the wheels to realize unloading to maintain their control ability because of the dependance of fuel. Reflectivity control devices (RCDs) become a possible solution for fuel‐free space attitude control by generating controllable solar radiation pressure (SRP) torque. However, the control ability of RCDs is limited because the torques they produce are rather small. To combine the advantages of both the momentum wheels and the RCDs, in this paper, an attitude control scheme utilizing momentum wheels as actuators and an RCD network for unloading is proposed. Firstly, the physical composition, force model, torque model, and principles of the distributed RCD network are given. After that, a stable and reliable unloading control method based on the envelope analysis is provided. Also, a three‐axis stabilized solar sail is utilized as an example to show to control system design. Numerical simulation proved that the momentum unloading for wheels can be realized safely and efficiently.