Altitude Control Research Articles

Reliability analysis of phased mission systems based on generalized stochastic Petri nets under mixed uncertainty

Phased mission systems (PMS) are widely applied across diverse industrial systems. Technological advancements in these systems have markedly improved their performance. However, fault characteristics such as uncertainty and common cause failure (CCF) frequently emerge during failures, which significantly raises new challenges in reliability analysis. A novel system reliability analysis framework is proposed to address the mixed uncertainty and CCF in PMS. Specifically, a hybrid modeling approach that combines dynamic fault trees and generalized stochastic Petri nets (GSPN) is employed to accurately model PMS containing CCF. This approach integrates predicates and assertions from GSPN to define four reusable sub-Petri net models at different hierarchical levels, including module, phase, CCF, and overall mission levels. Furthermore, interval theory is incorporated into the framework to manage imprecise component lifetime data. For uncertainty quantification, a synergistic approach combining genetic algorithm and Monte Carlo simulation is utilized. Additionally, a simplified approach is introduced to reduce the complexity of computing the reliability boundary values of PMS. Finally, the proposed method is applied to conduct reliability analysis of a phased altitude and orbit control system. The analysis results validate its effectiveness and applicability in addressing the mixed uncertainty and CCF of PMS.

Adaptive Sliding Mode Control of Quadrotor System with Elastic Load Connection of Unknown Mass

During quadrotor load transport, the cable’s elasticity exacerbates load fluctuations, which may result in platform instability or a potential crash. This paper introduced a model of the connecting cable as a spring-damper system and established the dynamic model of the suspension system based on Newton’s law. Nonsingular fast terminal sliding mode control (NFTSMC) was employed for attitude, position, and anti-swing controller design. Adaptive controllers were integrated into altitude control to address uncertainties related to load mass and cable length. The inclusion of an anti-swing controller into the position control loop effectively dampens load oscillations while ensuring accurate position tracking. Numerical simulations demonstrated that the proposed controller outperforms both the energy-based controller and the conventional linear sliding mode controller.

A High Performance Nonlinear Longitudinal Controller for Fixed-Wing UAVs Based on Fuzzy-Guaranteed Cost Control

Unmanned aerial vehicles (UAVs) have garnered more attention across various industries in recent years, leading to significant development in their design and application globally. Due to the high coupling between UAV states, model uncertainties, and various disturbances, precise longitudinal control of UAVs remains a significant research challenge. Oriented for the speed and altitude control of an electrical-powered fixed-wing UAV, this paper introduces a new control strategy based on the fuzzy guaranteed cost control (F-GCC) technique, which results in a nonlinear longitudinal state feedback control law with strict stability criterion, effectively addressing the issue of state coupling. Moreover, the strategy also includes a thrust estimation model of the electrical propulsion system to significantly reduce the nonlinearity, simplifying the controller design while effectively preserving tracking control performance. Through numerical validation, the UAV longitudinal nonlinear controller designed using the F-GCC technique offers better transient response and stronger robustness than the traditional linear and ADRC controllers.

Pitch angle and altitude control for unmanned helicopter based on new approximation-free control.

This article introduces an enhanced non-approximated control technique for the pitch and altitude control systems of unmanned helicopters. It takes into account unpredictable external disturbances and system dynamics. The integration of prescribed performance control into unmanned helicopter systems significantly improves the transient and steady-state response capabilities. This approach avoids the computational complexities often associated with neural networks and fuzzy control methods. By avoiding the need for function approximation, which can introduce inaccuracies and computational overhead, the controller design process is streamlined. This method's simplicity and ability to handle unknown disturbances make it highly suitable for real-world implementation, where robustness and efficiency are paramount. Finally, simulations are conducted to showcase the improved transient and steady-state response capabilities achieved by the proposed approach.

Design of an Optimal Allocator for Power Consumption Minimization in Hexarotor Drone Control Systems

This paper presents an allocator design that considers the power consumption of rotors in the attitude and altitude control system of a hexarotor drone. Based on the power consumption model, the proposed method computes the thrust force that minimizes the total power consumption of the rotor while satisfying the control force constraints required by the controller. To obtain the rotor power consumption model, we conducted experiments on the rotor characteristics using the motors and electronic speed controllers used in the drones. Finally, numerical simulations were performed using the obtained power consumption models to compare the rotor power consumption of the proposed method with that of the conventional method, quantitatively evaluating the effectiveness of the proposed method.

Fixed‐Time State Observer‐Based Robust Adaptive Neural Fault‐Tolerant Control for a Quadrotor Unmanned Aerial Vehicle

ABSTRACTThis paper presents a fixed‐time state observer‐based robust adaptive neural fault‐tolerant control (RANFTC) for attitude and altitude tracking and control of quadrotor unmanned aerial vehicles (UAVs), considering multiple actuator faults, parametric uncertainty, and unknown external disturbances simultaneously. A novel fixed‐time state error estimation based on sliding mode observer is designed, which is independent of initial conditions. A proportional–integral–derivative (PID) based sliding mode control (SMC) is proposed to handle actuator faults and unknown disturbances in combination with the fixed‐time observer within the fault‐tolerant control (FTC) design scheme. The radial basis function neural network (RBFNN) is employed with the controller to approximate the uncertain parameters of the system. Furthermore, two new adaptive laws are designed to estimate the sudden actuator fault and the unknown upper bound of disturbances independently. Implementing these estimation schemes avoids overestimation, enhances the robustness of the presented controller, and substantially eliminates the control chattering problem. By applying the Lyapunov stability concept, the suggested control strategy guarantees that the states of the quadrotor UAV converge to the origin in a finite time. Finally, simulation studies are conducted to demonstrate the tracking performance and highlight the effectiveness of the proposed FTC design compared to the existing FTC methods.

High-Altitude Inflatable Kites and Their Role in Atmospheric Boundary Layer Research

AbstractKites have been used as weather sensing solutions for over 250 years. The fact that they are simpler to operate and train on than alternative aerial systems, their ability to keep station at a fixed point for a long term, simplified altitude control, and the ease of retrieving their payload attribute to their growing appeal in atmospheric research. NASA, Toyota, and the School of Mechanical and Aerospace Engineering Oklahoma State University are active in developing and deploying high-altitude inflatable kite systems for atmospheric boundary layer (ABL) research—crucial to advancing the accuracy of weather forecasting. Improvements in kite design, as well as instrumentation and supporting infrastructure, are key to further accelerating the use of kites in atmospheric research. The work underway by these researchers is intended to be a deliberate step in the evolutionary development of these beneficial systems.

Seasonal and geographic viability of high altitude balloon navigation

Control of the geographic location of high-altitude balloons has been desired for decades due to the cost and simplicity of the systems. These balloon systems rely on variations in wind direction with altitude so that when a balloon changes height, it also changes the direction of its horizontal motion. An altitude control system can thus also control the horizontal position by transitioning to a wind layer with favorable winds. The system’s ability to navigate successfully thus relies on the existence of certain wind conditions. In this paper, we explore how the ability of a balloon to station-keep varies based on the geographic location and season. We used spatially and temporally variant ERA5 wind data with a tree-search-based algorithm to traverse potential trajectories, and we selected the altitude transitions that maximize time within 50 km of a target. The simulation’s outputs show large variations in success across both latitude and season. Midlatitudes are particularly challenging for station-keeping, while lower latitudes are more favorable. Summer is typically more favorable than winter. This demonstrates that for all balloon systems, the ability to station-keep is highly variant and not universally possible.

Case Study of Along-Track Separation Maintenance of Distributed Synthetic Aperture Radar Systems in Low Earth Orbits

Parasitic SAR formation can be flown at low altitude using smaller satellites and adding potential to conventional SAR mission From the orbital point of view, the main issue is related to the differential aerodynamic drag, which rapidly disrupts the formation. In this ambit, this paper proposes a case study of an along-track distributed parasitic receiver flying in formation with PLATiNO-1. Formation maintenance is the core contribution, highlighting how the active control of both altitude and in-plane anomalies leads to an unfeasible ΔV. Then, the active control of the altitude around the nominal value, which naturally controls anomaly shift, is proposed, modeled, and applied to the presented case study. It is shown that the annual ΔV can be reduced to the m/s range.

Dynamics modeling and nonlinear attitude controller design for a rocket-type unmanned aerial vehicle

This paper presents an altitude and attitude control system for a newly designed rocket-type unmanned aerial vehicle (UAV) propelled by a gimbal-based coaxial rotor system (GCRS) enabling thrust vector control (TVC). The GCRS is the only means of actuation available to control the UAV’s orientation, and the flight dynamics identify the primary control difficulty as the highly nonlinear and tightly coupled control distribution problem. To address this, the study presents detailed derivations of attitude flight dynamics and a control strategy to track the desired attitude trajectory. First, a Proportional-Integral-Derivative (PID) control algorithm is developed based on the formulation of linear matrix inequality (LMI) to ensure robust stability and performance. Second, an optimization algorithm using the Levenberg–Marquardt (LM) method is introduced to solve the nonlinear inverse mapping problem between the control law and the actual actuator outputs, addressing the nonlinear coupled control input distribution problem of the GCRS. In summary, the main contribution is the proposal of a new TVC UAV system based on GCRS. The PID control algorithm and LM algorithm were designed to solve the distribution problem of the actuation model and confirm altitude and attitude tracking missions. Finally, to validate the flight properties of the rocket-type UAV and the performance of the proposed control algorithm, several numerical simulations were conducted. The results indicate that the tightly coupled control input nonlinear inverse problem was successfully solved, and the proposed control algorithm achieved effective attitude stabilization even in the presence of disturbances.

Nonlinear prescribed performance sliding mode control of hypersonic vehicles

SummaryThis paper addresses the adaptive saturation prescribed performance control problem for air‐breathing hypersonic vehicles with parameter uncertainties and unknown external disturbances. First of all, different from the traditional performance function, a novel class of performance functions is presented without the initial state information, which does not require to reset parameters even if the initial velocity and altitude change. To ensure the successful design of the velocity controller and altitude controller, the constrained errors are transformed into the unconstrained errors by the projection technique. Secondly, the adaptive neural network and the sliding mode control techniques are combined to design the adaptive neural network sliding mode controllers, which guarantee that the velocity and altitude tracking errors can respectively approach the predetermined regions within the identical preset finite time. Finally, the effectiveness of the designed controllers is verified by an example with comparisons.

An Advanced IBVS-Flatness Approach for Real-Time Quadrotor Navigation: A Full Control Scheme in the Image Plane

This article presents an innovative method for planning and tracking the trajectory in the image plane for the visual control of a quadrotor. The community of researchers working on 2D control widely recognizes this challenge as complex, because a trajectory defined in image space can lead to unpredictable movements of the robot in Cartesian space. While researchers have addressed this problem for mobile robots, quadrotors continue to face significant challenges. To tackle this issue, the adopted approach involves considering the separation of altitude control from the other variables, thus reducing the workspace. Furthermore, the movements of the quadrotor (pitch, roll, and yaw) are interdependent. Consequently, the connection between the inputs and outputs cannot be reversed. The task complexity becomes significant. To address this issue, we propose the following scenario: When the quadrotor is equipped with a downward-facing camera, flying at high altitude is sensible to spot a target. However, to minimize disturbances and conserve energy, the quadrotor needs to descend in altitude. This can result in the target being lost. The solution to this problem is a new methodology based on the principle of differential flatness, allowing the separation of altitude control from the other variables. The system first detects the target at high altitude, then plots a trajectory in the image coordinate system between the acquired image and the desired image. It is crucial to emphasize that this step is performed offline, ensuring that the image processing time does not affect the control frequency. Through the proposed trajectory planning, complying with the constraints of differential flatness, the quadrotor can follow the imposed dynamics. To ensure the tracking of the target while following the generated trajectory, the proposed control law takes the form of an Image Based Visual Servoing (IBVS) scheme. We validated this method using the RVCTOOLS environment in MATLAB. The DJI Phantom 1 quadrotor served as a testbed to evaluate, under real conditions, the effectiveness of the proposed control law. We specifically designed an electronic card to transfer calculated commands to the DJI Phantom 1 control joystick via Bluetooth. This card integrates a PIC18F2520 microcontroller, a DAC8564 digital-to-analogue converter, and an RN42 Bluetooth module. The experimental results demonstrate the effectiveness of this method, ensuring the precise tracking of the target as well as the accurate tracking of the path generated in the image coordinate system.

Nonlinear Attitude and Altitude Trajectory Tracking Control of a Bicopter UAV in Geometric Framework

In this paper, we deal with a Bicopter drone that has two thrusters and two tilting servos. Both the position and attitude dynamics of Bicopter are globally expressed on the Special Euclidean group SE3. A simple control allocation method is proposed to map between the control wrench and actuator inputs for the Bicopter. A geometric nonlinear attitude and altitude tracking controller is developed for the Bicopter and the asymptotic stability analysis is performed using the Lyapunov method for the closed-loop nonlinear system. The performance of the proposed altitude and attitude stabilization controller is validated through experimental hardware developed in-house. The attitude controller performance is validated through simulations and shown to be comparable against an linear matrix inequality-based control law.

Autonomous Agricultural Drone with Sprinkling System

The quadcopter is one of the most widely used varieties of Unmanned Aerial Vehicles, or UAVs. This paper aims to build a drone with autonomous navigation capabilities. A sprinkling system was installed over the quadrotor to spray the desired fertilizers in the given area. The process of creating a quadrotor using a mechatronic design methodology—which considers the design of mechanical, electrical, software, and control components simultaneously—is explained in the article. The simulation findings for pitch and roll altitude control are also presented in the study. The investigation's findings include suggestions for choosing motors, propellers, batteries, and electrical speed controls wisely so that anyone with a desire might construct one by themselves.

A Separation Modeling Method for Morphing QUAV: Analytical Solutions for Constraint Forces Under Deformation

Abstract A morphing quadrotor unmanned aerial vehicle (QUAV) possesses the remarkable ability to alter its shape, enabling it to navigate through gaps smaller than its wingspan. However, these deformations result in changes to the system's center of gravity and moment of inertia, necessitating real-time computation of each state's variations. To address this challenge, we propose a dynamic modeling approach based on the Udwadia−Kalaba (U-K) method. The morphing QUAV is divided into three separate subsystems, with the dynamic modeling for each subsystem conducted independently. Subsequently, the QUAV's deformation states and inherent structure are introduced in the form of constraints, and the constrained forces are derived using the U-K equation. By combining these analytical solutions, the model of the QUAV under continuous deformation is obtained. This approach effectively simplifies the modeling computations caused by changes in the system's center of gravity and moment of inertia during deformation. A control approach is proposed to achieve attitude stabilization and altitude control for the morphing QUAV. Ultimately, the stable motion of the morphing QUAV is validated through numerical simulations.

Disturbance rejection control of the agricultural quadrotor based on adaptive neural network

In order to solve the problem of stability of agricultural quadrotor working, its controller designing is the first priority. Therefore, this paper makes an attempt to use the Radial Basis Function (RBF) neural network adaptive method combined with sliding mode control to control its height channel. Validation of the efficacy of the RBF neural network in control is conducted through simulation experiments utilizing quadrotor parameters. The application of the method to the control of agricultural quadrotor has laid a theoretical foundation. At the same time, through simulation experiments, it is concluded in theory that the RBF neural network can have a good prediction and elimination effect on the interference during the flight, and the change of the time constant will not affect the control effect of the aircraft. Notably, abrupt changes in time constant indicate UAV motor malfunction. Simulation results affirm the efficacy of the proposed control method in regulating UAV altitude and addressing sudden faults. Real-world experimentation (vegetable field including bean, pepper, eggplant, tomoto, etc.) reveals that even when UAV propellers sustain damage to a certain extent, altitude control and hover capabilities remain intact. These findings provide a solid groundwork for subsequent altitude control endeavors in agricultural quadrotor operations, while also offering innovative avenues for advancing the field.

Genetic Diversity and Selection Signatures in Economically Important Traits of Ethiopian Indigenous Cattle Breed as a Base for Dairy Cattle Genetic Improvement: A Review

The aim of this paper was to review the genetic diversities and selection signatures in economical important traits of Ethiopian indigenous cattle. This allows obtaining rapid genetic gain, predicting genomic potential and developing conservation strategies. A genetic variation among Ethiopian breeds ranging from 0.1 to 4.55% and a within variation of 95.45 to 99.9% was reported by various scholars. About 3.51% differentiation between Boran and Fogera from Begait and 2.82% differentiation of Boran from Fogera and Begait was reported. Even though the observed and expected heterozygosity values among Ethiopian cattle population was lower, research reports shown considerably higher values ranging from 0.638±0.015 in Boran and 0.714±0.022 in Raya-Azebo to 0.700± 0.014 in Ambo and 0.735±0.017 in Sheko. Genes responsible for heat tolerance, control of metabolic disease, immunity genes, high altitude and low altitude adaptation were reported in Ethiopian cattle breeds. In African indicus and European taurian cattle different genes responsible for milk production, milk fat yield and synthesis and milk composition, were reported. Genes associated with milk traits; fertility and reproduction genes were also reported in Ethiopian cattle. The presence of high within breed variation in Ethiopian cattle creates favorable conditions for further improvement through selection. Beyond identifying candidate potential genes, a detailed study targeting genomic prediction of milk yield and genomic inbreeding had better be done, which allows getting information to optimize and speed up the breeding programs and genetic improvement.

Precision Landing of Unmanned Aerial Vehicle under Wind Disturbance Using Derivative Sliding Mode Nonlinear Disturbance Observer-Based Control Method

Unmanned aerial vehicles (UAVs) are extensively employed in civilian and military applications because of their excellent maneuverability. Achieving fully autonomous quadrotor flight and precision landing on a wireless charging station in the presence of wind disturbance has become a crucial research topic. This paper presents a composite control technique for UAV altitude and attitude tracking in harsh environments, i.e., wind disturbance. A composite controller was developed based on nonlinear disturbance observer (NDOB) control theory to allow the UAV to land in the presence of random external wind disturbances and ground effects. The NDOB estimated the unknown wind disturbance, and the estimation was fed into the derivative sliding mode nonlinear disturbance observer-based control (DSMNDOBC), allowing the UAV to perform autonomous precision landing. Two loop designs were applied: the inner loop for stabilization and the outer loop for altitude tracking. The quadrotor model dynamics and the proposed controller, DSMNDOBC, were simulated employing MATLAB/Simulink®, and the results were compared with the one obtained by the proportional derivative (PD) controller and the sliding mode controller (SMC). The simulation results indicated that the DSMNDOBC has superior altitude and attitude control compared to the PD and SMC controllers and better disturbance estimation and attenuation performance.

Dynamic Modeling and Altitude Control for Flying Cars Based on Active Disturbance Rejection Control

Flying cars offer huge advantages due to their deformable structure, which can adapt to external environments and mission requirements. They represent a novel system that can realize vertical takeoff and landing. However, the structure of a flying car is complicated, placing higher requirements on modeling accuracy and control effectiveness. Thus, in this paper, a dynamic model of a flying car is proposed by combining a car body, motor, and propellers. Then, a double-loop controller based on active disturbance rejection control is proposed to accurately control its flight altitude. Utilizing the extended state observer, external wind and other disturbances are regarded as an extended state, which can be dynamically observed and compensated to significantly improve tracking accuracy. The effectiveness of the proposed controller is validated through detailed simulations and flight experiments. The proposed controller significantly improves control accuracy and disturbance rejection capability.

Coordinated transportation of tethered multi-rotor UAVs based on differential graphical games

This paper investigates the stability control of the tethered multi-rotor unmanned aerial vehicles (T-MRUAVs) system in cargo delivery, where precise payload trajectory control is deemed unnecessary, with a focus on enhancing controller simplicity and robustness. To achieve this objective, it is imperative to employ an optimal formation tracking control, ensuring not only the symmetrical positioning of UAVs concerning the payload but also the achievement of distributed optimal solutions. Therefore, a formation tracking control strategy based on differential graphical games is designed to ensure optimized performance metrics and minimized suspended load swing. The designed control framework includes an outer loop and an inner loop control, which respectively achieve formation tracking and attitude stability. In addition to maintaining equilibrium states, each UAV is required to track the desired trajectory. Consequently, the formation tracking control consists of a gravity compensation term at the equilibrium point and a formation tracking control term based on differential graphical games. Then, a PID control strategy is displayed for the inner loop control, and the altitude control adopts feedback linearization. Finally, numerical simulations have validated the effectiveness of the designed algorithm.