Position Loop Research Articles

Hovering Control on a Variable-Parameters Model of a Small Unmanned Helicopter Based on a Backstepping Sliding Mode Method

In order to strengthen the hovering precision of a small unmanned helicopter with a manipulator for completing a hovering operation, in this study, a double-loop control strategy of position and attitude is designed. In the position loop, a sliding mode controller is proposed. It attains high precision and strong robustness under continuous disturbance. With the manipulator continuously operating during helicopter hovering, the overall center of gravity and the moment of inertia of the system will also change. Therefore, a backstepping sliding mode controller is proposed in the attitude loop for controlling the hovering attitude of the helicopter. The high precision and strong robustness of the control system are proven. The digital simulation presents a position steady-state error of less than 2% under constant disturbance, and the hovering attitude angle fluctuation amplitude of the helicopter is less than 0.05 rad.

Droplet generation in a co-flowing microchannel under the non-uniform magnetic fields produced by an electric current loop

Micro-magnetofluidics, the study of fluid behavior under magnetic fields in microscale systems, is vital for applications like drug delivery, chemical synthesis, and lab-on-a-chip technologies. Controlling droplet size and formation frequency in these systems is challenging due to the complex interplay of magnetic forces and fluid dynamics. This study introduces a novel approach to control droplet generation in a co-flowing microchannel under a non-uniform magnetic field generated by an electric current loop. Critical parameters such as electric current intensity, continuous phase flow rate, and current loop position are systematically examined for their impact on droplet behavior. The results highlight the unique influence of the magnetic field configuration, specifically the electric current loop, in inducing a transition from dripping to jetting flow patterns with increasing current intensity, leading to larger droplets and reduced generation frequency. Additionally, a distinct behavior of droplet coalescence near the current loop, followed by re-separation, is observed when the loop is positioned downstream of the inlet. Moreover, increasing the continuous phase flow rate consistently reduced droplet size and increased generation frequency, regardless of the current loop’s position

Pre-specifiable fixed-time control for quadrotor aircraft with output constraints

For the controller design of quadrotor aircraft with six-DOF, a pre-specifiable fixed-time method combined with state constraints is researched in this paper. The 6-DOF aircraft model is divided into position loop and attitude loop through time scale decomposition method for the convenience of decoupling. Adaptive pre-specifiable fixed-time controllers for the position subsystem and attitude subsystem are proposed to ensure the desired trajectory and the desired attitude angle can be reached within a fixed-time which is independent of initial conditions. Meanwhile, the convergence time can be user-assignable in advance. Time-varying state constraints are considered in the controller design process in order to guarantee the safety of the system and prolong the life of actuator. The Barrier Lyapunov function is applied to ensure quadrotor aircraft’s output constraints are not violated. Finally, the effectiveness of the proposed controller is verified by the simulation experiment.

Process-integrated computerized numerical control: an analysis on process-machine coupling and feed scheduling

Computerized numerical controls (CNCs) have been invented for the automation of industrial processes. They are used, when the process to be automated is required to be exact and fast with repeatable quality. Originally, the use of CNCs was primarily focused on milling and drilling processes. Today, CNCs are utilized in a wide range of industrial processes due to the growing importance of automation. However, the integration of process information or adaptation to the needs of these processes to achieve advanced manufacturing with CNCs is difficult: Industrial CNCs are rather closed real-time machining systems. Today, process integration is possible, when the interaction between the process and the machine is decoupled in view of the bandwidth of machine dynamics and process dynamics. There are interfaces that allow for process-motivated control loops that are realized on top of the machine control loop (e.g. chatter control). Then, machine-integrated real-time control is not the focus. Besides, it is often possible to change desired values inside the control loop (position, velocity, acceleration) on an axes basis. In this case, adaptation to the process can be realized in each computation cycle. However, process dynamics and machine axes dynamics are generally treated separately. The same holds for extra actuators (e.g., in the spindle) for position control. This paper has two goals. First, it wants to create an understanding for different levels of process-machine coupling. Second, the problem of direct coupling of process dynamics and machine dynamics is focused. Machining systems design propositions as well as some examples for the coupling of process and machine dynamics in the CNC are given.

CDR L3 Loop Rearrangement Switches Multispecific SPE-7 IgE Antibody From Hapten to Protein Binding.

The monoclonal IgE antibody SPE-7 was originally raised against a 2,4-dinitrophenyl (DNP) target. Through its ability to adopt multiple conformations, the antibody is capable of binding to a diverse range of small haptens and large proteins. The present study examines a dataset of experimentally determined crystal structures of the SPE-7 antibody to gain insight into the mechanisms that contribute to its multispecificity. With the emergence of more and more therapeutic antibodies against a huge repertoire of different targets, our research could be of great interest for future drug development. We are able to discriminate between the different paratope-binding states in the conformational ensembles obtained by enhanced sampling molecular dynamics simulations, and to calculate their transition timescales and state probabilities. Furthermore, we describe the key residues responsible for discriminating between the different binding capacities and identify a tryptophan in a central position of the CDR L3 loop as the residue of greatest interest. The overall dynamics of the paratope appear to be mainly influenced by the CDR L3 and CDR L1 loops.

Modelling and control of the lower hook mechanism for fishing net weaving machine based on active disturbance rejection controller

Abstract The lower hook mechanism of the fishing net weaving machine has significant impact on its weaving velocity and net quality. This study incorporated a multi-motor based lower hook mechanism, which is driven by multi-motors instead of mechanical cams. Compared with the traditional lower hook mechanism, the multi-motor based lower hook mechanism has the advantages of fewer mechanical wear and faster running speed. However, the working condition of the lower hook mechanism places a very high demand on its following accuracy and resistance to disturbance, so the servo motor should be highly accurate and highly robust. The commonly used controller of the servo motor is three closed loop proportion-integral (PI) controller. In this paper, we modelled and experimentally verified the multi-motor based lower hook mechanism, and rebuilt the servo motor controller by replacing the position loop PI and speed loop PI of the three closed loop PI controller with position-velocity joint active disturbance rejection controller. Simulations suggest that the active disturbance rejection controller performs better on both following accuracy and resistance to disturbance compared with the traditional PI controller in the application of lower hook mechanism.

Adaptive dynamic programming–based fault-tolerant control of multi-UAV formation system

With the increasing utilization of unmanned aerial vehicle (UAV) swarms in civilian and military field applications, it is crucial to eliminate the potential impacts of UAV faults on task completion and efficiency. To address this issue, the present paper investigates a fault-tolerant control scheme based on the adaptive dynamic programming (ADP) method and fault observer. The whole closed-loop system is composed of a position loop and an attitude loop. An ADP-based position-tracking controller is established with an improved cost function that can simultaneously represent actuator faults, control inputs, and tracking errors. In addition, a single-layer critic neural network is constructed to estimate the cost function and approximate control inputs. In the process of adjusting the weights of the neural network, a unique adjustment method combining policy gradient and prioritized experience replay is adopted to improve the data usage efficiency and speed up the weight convergence. Furthermore, a sliding mode–based attitude controller is utilized for the inner-loop attitude subsystem. The significant feature of this scheme is that it has the ability to self-learn and self-adapt. A Lyapunov stability analysis is performed to verify whether the signals are uniformly ultimately bounded. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed scheme.

PARALLEL PLATFORM CONTROLLER BASED ON ADAPTIVE DIFFERENCE ALGORITHM – PART 2

There are two main approaches to motion control on parallel platforms: joint space control and workspace control. Joint space control is an easy-to-implement semi-closed-loop strategy, but its control effect could be better. The workspace control is to obtain the real-time position of the parallel platform through the forward solution and close the speed and position loop of the parallel platform in the workspace. This paper uses a Model Predictive Controller (MPC) to control the parallel platform with workspace control as the research goal. The loss function is constructed based on the swarm intelligence optimization idea, and the adaptive difference algorithm is used to optimize the parameters of MPC. This part uses MATLAB to perform simulation experiments to complete the S-shaped velocity trajectory planning algorithm. In addition, the control effect of MPC and position-loop PI controller in a robust disturbance environment is compared. Experiments show that MPC has the advantages of low energy consumption and high control accuracy.

Radial Basis Function Neural Network and Feedforward Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor

A composite control strategy is proposed to improve the position-tracking performance and anti-interference capabilities of permanent magnet synchronous motors (PMSMs). This strategy integrates an active disturbance rejection controller (ADRC) and a radial basis function neural network (RBFNN) with feedforward control. Initially, the flexibility and robustness of the ADRC are utilized in the position loop control. Subsequently, the parameters of the extended state observer (ESO) within the ADRC are optimized, benefiting from the fast convergence speed and optimal approximation provided by the RBFNN. To further enhance the dynamic tracking performance, a differential feedforward link is introduced between the desired speed and the output signal. The simulation and experimental results demonstrate that when the expected electrical angle inputs are sinusoidal and pulse signals, the incorporation of the feedforward link and the adjustment of parameters in the ADRC lead to improved position-tracking capabilities and greater adaptability to load disturbances.

Adaptive super-twisted sliding mode trajectory tracking control for quadrotor UAV with prescribed performance based on finite-time disturbance observer

This study proposes a finite-time disturbed observer-based prescribed performance adaptive super-twisted sliding mode trajectory tracking control scheme for quadrotor UAV. Based on the super-twisted sliding mode algorithm, adaptive control, finite-time theory, and prescribed performance control, this scheme aims to achieve stable tracking of a quadrotor UAV along a defined trajectory. This is achieved even when faced with challenges such as modeling uncertainty, external uncertainty, and complex interference environments. Firstly, the coupling between the channels and the disturbance effects are unified as the aggregate disturbance. To address the issue of the adverse impact of aggregate disturbance on system performance, a new finite-time disturbance observer is developed to estimate the overall disturbance. The observer can effectively eliminate the negative effects of the aggregate disturbance without considering the disturbed boundary conditions during the design process. Secondly, the disturbance estimation information and the adaptive super-twisted algorithm are used to construct the adaptive super-twisted sliding mode controllers for the position and attitude loops, respectively. Then, a prescribed performance control is designed to predefined the time for the position loop to effectively suppress the deleterious effects of interference. This ensures that the position system can quickly meet the prescribed tracking requirements. Finally, the stability of the designed trajectory tracking control system is demonstrated using the Lyapunov theorem. Numerical simulation results verify the effectiveness and superiority of the proposed controller.

Disturbance observer based fixed-time tracking control for unmanned aerial helicopters

In this paper, a fixed-time tracking control scheme based on the fixed-time disturbance observer is proposed for a 6-DOF unmanned aerial helicopter (UAH) with flight path constraints and composite disturbances. The composite disturbances are composed of external disturbances and system uncertainties. By using the hyperbolic tangent function, an improved disturbance observer is developed to estimate composite disturbances. Furthermore, a fixed-time back-stepping control method is employed for the position and attitude loops, which enables the UAH to track the expected path within the flight path constraints. Simulation results are given to demonstrate the effectiveness and advantages of the proposed scheme.

Effect of Strain Relief Loop Position on the RF-Induced Heating of Active Implantable Medical Devices at 1.5-T MRI

Effect of Strain Relief Loop Position on the RF-Induced Heating of Active Implantable Medical Devices at 1.5-T MRI

Safe tracking control for unmanned autonomous helicopter under actuator faults and outside disturbances

This paper considers the problem on tracking control for the medium-scale unmanned autonomous helicopter (UAH) system under external disturbances, actuator faults, and full state constraints. In comparison with existing results, this paper does not only consider asymmetric state constraints but also jointly take the faults and disturbances into account on the UAH system, estimating and compensating for them separately, which can effectively enhance the tracking performance. First, the dynamics of nonlinear UAH system is divided into the position subsystem and the attitude one. Second, an improved barrier Lyapunov function (BLF) is constructed to handle the problem of asymmetric state constraints. Third, in order to estimate the external disturbances and actuator faults, two coupled generalized proportional integral observers (GPIOs) and two fault estimators are designed, respectively. Fourth, based on above estimations, improved BLFs, and backstepping method, two tracking control laws for the position and attitude loops are presented and an overall closed-loop system is established. Then, a sufficient condition ensuring uniform boundedness of tracking and estimation errors is derived. Finally, some simulating results demonstrate the effectiveness and advantage of the proposed control scheme.

PARALLEL PLATFORM CONTROLLER BASED ON ADAPTIVE DIFFERENCE ALGORITHM – PART 1

There are two main approaches to motion control on parallel platforms: joint space control and workspace control. Joint space control is an easy-to-implement semi-closed-loop strategy, but its control effect could be better. The workspace control is to obtain the real-time position of the parallel platform through the forward solution and close the speed and position loop of the parallel platform in the workspace. This paper uses a model predictive controller (MPC) to control the parallel platform with workspace control as the research goal. The loss function is constructed based on the swarm intelligence optimization idea, and the adaptive difference algorithm is used to optimize the parameters of MPC. This part details the research background and the algorithm design process. Then, the MPC algorithm is implemented on the upper computer using C++, and the physical test is implemented. The test results show that the controller has a good control effect on the physical platform.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

Recent advances in molecular modeling using deep learning can revolutionize our understanding of dynamic protein structures. NMR is particularly well-suited for determining dynamic features of biomolecular structures. The conventional process for determining biomolecular structures from experimental NMR data involves its representation as conformation-dependent restraints, followed by generation of structural models guided by these spatial restraints. Here we describe an alternative approach: generating a distribution of realistic protein conformational models using artificial intelligence-(AI-) based methods and then selecting the sets of conformers that best explain the experimental data. We applied this conformational selection approach to redetermine the solution NMR structure of the enzyme Gaussia luciferase. First, we generated a diverse set of conformer models using AlphaFold2 (AF2) with an enhanced sampling protocol. The models that best-fit NOESY and chemical shift data were then selected with a Bayesian scoring metric. The resulting models include features of both the published NMR structure and the standard AF2 model generated without enhanced sampling. This "AlphaFold-NMR" protocol also generated an alternative "open" conformational state that fits nearly as well to the overall NMR data but accounts for some NOESY data that is not consistent with first "closed" conformational state; while other NOESY data consistent with this second state are not consistent with the first conformational state. The structure of this "open" structural state differs from that of the "closed" state primarily by the position of a thumb-shaped loop between α-helices H5 and H6, revealing a cryptic surface pocket. These alternative conformational states of Gluc are supported by "double recall" analysis of NOESY data and AF2 models. Additional structural states are also indicated by backbone chemical shift data indicating partially-disordered conformations for the C-terminal segment. Considered as a multistate ensemble, these multiple states of Gluc together fit the NOESY and chemical shift data better than the "restraint-based" NMR structure and provide novel insights into its structure-dynamic-function relationships. This study demonstrates the potential of AI-based modeling with enhanced sampling to generate conformational ensembles followed by conformer selection with experimental data as an alternative to conventional restraint satisfaction protocols for protein NMR structure determination.

Hyphal editing of the conserved premature stop codon in CHE1 is stimulated by oxidative stress in Fusarium graminearum

Although genome-wide A-to-I editing mediated by adenosine-deaminase-acting-on-tRNA (ADAT) occurs during sexual reproduction in the presence of stage-specific cofactors, RNA editing is not known to occur during vegetative growth in filamentous fungi. Here we identified 33 A-to-I RNA editing events in vegetative hyphae of Fusarium graminearum and functionally characterized one conserved hyphal-editing site. Similar to ADAT-mediated editing during sexual reproduction, majority of hyphal-editing sites are in coding sequences and nonsynonymous, and have strong preference for U at -1 position and hairpin loops. Editing at TA437G, one of the hyphal-specific editing sites, is a premature stop codon correction (PSC) event that enables CHE1 gene to encode a full-length zinc fingertranscription factor. Manual annotations showed that this PSC site is conserved in CHE1 orthologs from closely-related Fusarium species. Whereas the che1 deletion and CHE1TAA (G438 to A) mutants had no detectable phenotype, the CHE1TGG (A437 to G) mutant was defective in hyphal growth, conidiation, sexual reproduction, and plant infection. However, the CHE1TGG mutant was increased in tolerance against oxidative stress and editing of TA437G in CHE1 was stimulated by H2O2 treatment in F. graminearum. These results indicate that fixation of the premature stop codon in CHE1 has a fitness cost on normal hyphal growth and reproduction but provides a benefit to tolerance against oxidative stress. Taken together, A-to-I editing events, although rare (not genome-wide), occur during vegetative growth and editing in CHE1 plays a role in response to oxidative stress in F. graminearum and likely in other fungal pathogens.

Data‐driven adaptive control design for active stabilization of stratospheric airship imaging platform: A characteristic model approach

AbstractIn response to the problem of disturbance in the imaging equipment of stratospheric airships, this study designs a vibration isolation and stability system for carrying imaging equipment. The system mainly consists of microprocessor, gimbal, voice coil motor(VCM) and rubber ring. By using adaptive control law based on characteristic model to control the double closed control loop of the motor composed of position loop and speed loop, the camera deflection caused by disturbance is effectively eliminated. Furthermore, in vertical vibration suppression, the adaptive control law based on the characteristic model is also applied to the double closed control loop of the voice coil motor, which removes most of the vertical vibration and realizes active vibration isolation. The passive isolation of the system is completed by rubber rings. The experimental results show that the vibration isolation and stabilization system have good performance in complex disturbance environments, effectively stabilizing the imaging equipment.

Adaptive Formation Tracking Control of Multiple Vertical Takeoff and Landing UAVs With Bearing-Only Measurements.

This article studies the leader-following formation tracking control problem of multiple vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) subject to uncertain parameters, in which the target formation configuration is defined by using the interneighbors' bearing vectors. An adaptive formation control algorithm with bearing-only measurements is proposed under a hierarchical control framework. More specifically, a saturated adaptive distributed control force is developed in the position loop with bearing-only measurements. Since the bearing vectors with respect to the neighbors can be directly measured by low-cost onboard cameras, the proposed formation algorithm can be implemented without interagent communication. Subsequently, in the attitude loop, an adaptive hybrid control scheme via two modified Rodrigues parameters (MRPs) sets is proposed, which achieves the command attitude tracking globally and also avoids the unwinding problem of MRPs. Based on the Lyapunov stability analysis and hybrid theory, we prove that the overall closed-loop error system is globally asymptotically stable. Finally, we provide a numerical example to demonstrate the effectiveness of the proposed control algorithm.

Multivariable Iterative Learning Control Design for Precision Control of Flexible Feed Drives.

Advancements in machining technology demand higher speeds and precision, necessitating improved control systems in equipment like CNC machine tools. Due to lead errors, structural vibrations, and thermal deformation, commercial CNC controllers commonly use rotary encoders in the motor side to close the position loop, aiming to prevent insufficient stability and premature wear and damage of components. This paper introduces a multivariable iterative learning control (MILC) method tailored for flexible feed drive systems, focusing on enhancing dynamic positioning accuracy. The MILC employs error data from both the motor and table sides, enhancing precision by injecting compensation commands into both the reference trajectory and control command through a norm-optimization process. This method effectively mitigates conflicts between feedback control (FBC) and traditional iterative learning control (ILC) in flexible structures, achieving smaller tracking errors in the table side. The performance and efficacy of the MILC system are experimentally validated on an industrial biaxial CNC machine tool, demonstrating its potential for precision control in modern machining equipment.

Radiographic Recognition of Mental Nerve for Secured Dental Implant Placement by Cone-Beam Computed Tomography in Mosul City Population.

The study aims to estimate precisely the different levels of mental loop and foramina in the Mosul population of Nineveh governorate in Iraq. It is a cross-sectional study of a previously saved database in the cone-beam computed tomography device. The study sample was 357 patients selected randomly from the database of patients at the Oral Radiology Unit at the Maxillofacial Department in Al-Salam Teaching Hospital. The study variables are mental foramen (MF) position, shape, radiograph appearance, and mental loop presence and direction. The results show that the age group from 19 to 30 years shows the highest percentage (40.1%). Females show more than half of the cases (59.7%). The MF position's highest percentage is shown in 2 areas with the slight differences. These are the long axis of first premolar and the area between first premolar and second premolar (42.6%, 40.9). According to shape variation round shapes are the uppermost percent (53.8%). More than 60% of cases (66.1%) show continuity with the inferior alveolar canal and 50% show no loop presence, and the mental nerve leaves the foramen in a perpendicular direction. In conclusion localization of the MF, nerve, and its loop precisely in both horizontal and vertical directions, both hard and soft tissues in a continuous view. Before arranging any surgical procedure, anatomic markers are crucial. To reduce the danger of harm to the foramen region, the authors thus advised cone-beam computed tomography before scheduling implant surgery, particularly in the mental region of the jaw.