A high accuracy modeling scheme for dynamic systems: spacecraft reaction wheel model

Reaction wheels are crucial actuators in spacecraft attitude control subsystem (ACS). The precise modeling of reaction wheels is of fundamental need in spacecraft ACS for design, analysis, simulation, and fault diagnosis applications. The complex nature of the reaction wheel leads to modeling difficulties utilizing the conventional modeling schemes. Additionally, the absence of reaction wheel providers’ parameters is crucial for triggering a new modeling scheme. The Radial Basis Function Neural Network (RBFNN) has an efficient architecture, alluring generalization properties, invulnerability against noise, and amazing training capabilities. This research proposes a promising modeling scheme for the spacecraft reaction wheel utilizing RBFNN and an improved variant of the Quantum Behaved Particle Swarm Optimization (QPSO). The problem of enhancing the network parameters of the RBFNN at the training phase is formed as a nonlinear constrained optimization problem. Thus, it is proposed to efficiently resolve utilizing an enhanced version of QPSO with mutation strategy (EQPSO-2M). The proposed technique is compared with the conventional QPSO algorithm and different variants of PSO algorithms. Evaluation criteria rely upon convergence speed, mean best fitness value, stability, and the number of successful runs that has been utilized to assess the proposed approach. A non-parametric test is utilized to decide the critical contrast between the results of the proposed algorithm compared with different algorithms. The simulation results demonstrated that the training of the proposed RBFNN-based reaction wheel model with enhanced parameters by EQPSO-2M algorithm furnishes a superior prediction accuracy went with effective network architecture.

Influences on Pregnant Women’s and Health Care Professionals’ Behaviour Regarding Maternal Vaccinations: A Qualitative Interview Study

The uptake of maternal influenza and pertussis vaccinations is often suboptimal. This study explores the factors influencing pregnant women’s and health care professionals’ (HCPs) behaviour regarding maternal vaccinations (MVs). Pregnant/recently pregnant women, midwives, pharmacists and general practice staff in Waikato, New Zealand, were interviewed. The analysis used the behaviour change wheel model. Interviews of 18 women and 35 HCPs revealed knowledge about MVs varied with knowledge deficiencies hindering the uptake, particularly for influenza vaccination. HCPs, especially midwives, were key in raising women’s awareness of MVs. Experience with vaccinating, hospital work (for midwives) and training increased HCPs’ knowledge and proactivity about MVs. A “woman’s choice” philosophy saw midwives typically encouraging women to seek information and make their own decision. Women’s decisions were generally based on knowledge, beliefs, HCPs’ emphasis and their perceived risk, with little apparent influence from friends, family, or online or promotional material. General practice’s concentration on children’s vaccination and minimal antenatal contact limited proactivity with MVs. Busyness and prioritisation appeared to affect HCPs’ proactivity. Multi-pronged interventions targeting HCPs and pregnant women and increasing MV access are needed. All HCPs seeing pregnant women should be well-informed about MVs, including how to identify and address women’s questions or concerns about MVs to optimise uptake.

Research on Matching Characteristics of Wind Turbine and Generator for Small H-shaped Vertical Axis Wind Turbine

Based on the small H-shaped vertical axis wind wheel model (NACA0016), a CFD wind wheel model was constructed. Based on the principle of moving grid, the grid division of the CFD wind wheel model is completed by using GAMBIT software, and the boundary conditions such as the inlet boundary and the outlet boundary are set reasonably. Then, the turbulence model and the couple algorithm are used to carry out transient simulation calculations, and finally the aerodynamic parameter curves of the two-dimensional CFD wind wheel model are obtained. Based on this, the matching characteristics of the wind turbine and generator of the small H-shaped vertical axis wind turbine are studied. The research results show as follows: when the incoming wind speeds change in range of (2 m/s, 12 m/s), and the power characteristic curve and torque characteristic curve of the generator wind wheel are respectively overlap the best power curve and best torque of the generator, the matching characteristics of the small H-shaped vertical axis wind turbine rotor and generator are optimal, which provides reference for carrying out related research.

Controller Tuning and Robustness Testing of Attitude Control Laws for a CubeSat Mission

The purpose of this project was to create a test environment that can be used to test different controllers and their robustness. In this report, the equations of motion were derived using kinematics, with attitude quaternions, and spacecraft dynamics, with angular velocity and acceleration. The equations were combined and placed into the form of a linearized state-space equation. The different control methods being investigated, Linear Quadratic Regulator (LQR) for the reaction wheel model, and the Bdot with bias controller, were explained and the block diagram for each was shown. To setup the test, the tolerances for the roll, pitch, and yaw, and their rates, were taken from the mission requirement for the ESSENCE mission. The attitude tolerance being ±0.5deg and the angular rates requirement being ±0.05deg/s. Then the test setup was further explained. The test is broken up into different scripts and steps: 1. Main run function for simulation. Initializes simulation parameters. 2. Build state-space equation and calculate constant gain matrix. 3. Randomize initial conditions and pass onto simulation. 4. Post-processing and plot generation. 5. Statistics generation. This robust testing environment was used to test 5 different controllers for the reaction wheel model. Each controller was tested for 200 different simulations, in which the initial attitude, initial angular rates, and the center of mass were randomized. The first controller was successful for 198/200 simulations, where the only failure came from over-saturating the reaction wheels. The next three controllers had a perfect record and were successful for all 200 simulations each. The last controller, had only 71 successful simulations in the set, and a sample of one of the failed simulations was further investigated to see how it failed.

Controller Tuning and Robustness Testing of Attitude Control Laws for a CubeSat Mission

The purpose of this project was to create a test environment that can be used to test different controllers and their robustness. In this report, the equations of motion were derived using kinematics, with attitude quaternions, and spacecraft dynamics, with angular velocity and acceleration. The equations were combined and placed into the form of a linearized state-space equation. The different control methods being investigated, Linear Quadratic Regulator (LQR) for the reaction wheel model, and the Bdot with bias controller, were explained and the block diagram for each was shown. To setup the test, the tolerances for the roll, pitch, and yaw, and their rates, were taken from the mission requirement for the ESSENCE mission. The attitude tolerance being ±0.5deg and the angular rates requirement being ±0.05deg/s. Then the test setup was further explained. The test is broken up into different scripts and steps: 1. Main run function for simulation. Initializes simulation parameters. 2. Build state-space equation and calculate constant gain matrix. 3. Randomize initial conditions and pass onto simulation. 4. Post-processing and plot generation. 5. Statistics generation. This robust testing environment was used to test 5 different controllers for the reaction wheel model. Each controller was tested for 200 different simulations, in which the initial attitude, initial angular rates, and the center of mass were randomized. The first controller was successful for 198/200 simulations, where the only failure came from over-saturating the reaction wheels. The next three controllers had a perfect record and were successful for all 200 simulations each. The last controller, had only 71 successful simulations in the set, and a sample of one of the failed simulations was further investigated to see how it failed.

Vietnam’s Healthcare System Decentralization: how well does it respond to global health crises such as Covid-19 pandemic?

This article discussed Vietnam’s ongoing efforts to decentralize the health system and its fitness to respond to global health crises as presented through the Covid-19 pandemic. We used a general review and expert’s perspective to explore the topic. We found that the healthcare system in Vietnam continued to decentralize from a pyramid to a wheel model. This system shifts away from a stratified technical hierarchy of higher- and lower-level health units (pyramid model) to a system in which quality healthcare is equally expected among all health units (wheel model). This decentralization has delivered more quality healthcare facilities, greater freedom for patients to choose services at any level, a more competitive environment among hospitals to improve quality, and reductions in excess capacity burden at higher levels. It has also enabled the transformation from a patient-based traditional healthcare model into a patient-centered care system. However, this decentralization takes time and requires long-term political, financial commitment, and a working partnership among key stakeholders. This perspective provides Vietnam’s experience of the decentralization of the healthcare system that may be considered as a useful example for other countries to strategically think of and to shape their future system within their own socio-political context.