Effect of Prone Position Ventilation in Patients with Severe Craniocerebral Injury Complicated with Pulmonary Infection

Objective:To investigate the effects of prone ventilation in patients with severe traumatic brain injury combined with pulmonary infection.Methods:A total of 100 patients with severe traumatic brain injury combined with pulmonary infection in the hospital were randomly divided into a prone ventilation group and a conventional ventilation group,with 50 patients in each group.The Glasgow Coma Scale(GCS)score,APACHE II score,sputum culture results,oxygenation indicators,and prognosis were compared between the two groups.Data were processed using SPSS 25.0 statistical software,and t-tests and chi-square tests were used to compare continuous and categorical variables,respectively.Results:The experimental group showed better oxygenation indicators,a lower positive rate of sputum cultures,and reduced intracranial pressure compared to the control group(all P<0.05).Multivariate Cox regression analysis indicated that GCS score,APACHE II score,and prone ventilation were independent risk factors affecting patient prognosis(all P<0.05).Conclusion:Prone ventilation can improve oxygenation,reduce the risk of pulmonary infection,and decrease intracranial pressure in patients with severe traumatic brain injury combined with pulmonary infection,thereby improving patient prognosis.GCS score and APACHE II score can serve as important indicators for prognostic evaluation.

Coupled Dynamics and Integrated Control for Position and Attitude Motions of Spacecraft:A Survey

Inspired by the integrated guidance and control design for endo-atmospheric aircraft,the integrated position and attitude control of spacecraft has attracted increasing attention and gradually induced a wide variety of study results in last over two decades,fully incorporating control requirements and actuator characteristics of space missions.This paper presents a novel and comprehensive survey to the coupled position and attitude motions of spacecraft from the perspective of dynamics and control.To this end,a systematic analysis is firstly conducted in details to show the position and attitude mutual couplings of spacecraft.Particularly,in terms of the time discrepancy between spacecraft position and attitude motions,space missions can be categorized into two types:space proximity operation and space orbital maneuver.Based on this classification,the studies on the coupled dynamic modeling and the integrated control design for position and attitude motions of spacecraft are sequentially summarized and analyzed.On the one hand,various coupled position and dynamic formulations of spacecraft based on various mathematical tools are reviewed and compared from five aspects,including mission applicability,modeling simplicity,physical clearance,information matching and expansibility.On the other hand,the development of the integrated position and attitude control of spacecraft is analyzed for two space missions,and especially,five distinctive development trends are captured for space operation missions.Finally,insightful prospects on future development of the integrated position and attitude control technology of spacecraft are proposed,pointing out current primary technical issues and possible feasible solutions.

Nonlinear Control of Magnetically Coupled Rodless Cylinder Position Servo System

Magnetically coupled rodless cylinders are widely used in the coordinate positioning of mechanical arms,electro-static paintings,and other industrial applications.However,they exhibit strong nonlinear characteristics,which lead to low servo control accuracy.In this study,a mass-flow equation through the valve port was derived to improve the control performance,considering the characteristics of the dynamics and throttle-hole flow.Subsequently,a fric-tion model combining static,viscous,and Coulomb friction with a zero-velocity interval was proposed.In addition,energy and dynamic models were set for the experimental investigation of the magnetically coupled rodless cylin-der.A nonlinear mathematical model for the position of the magnetically coupled rodless cylinder was proposed.An incremental PID controller was designed for the magnetically coupled rodless cylinder to control this system,and the PID parameters were adjusted online using RBF neural network.The response results of the PID parameters based on the RBF neural network were compared with those of the traditional incremental PID control,which proved the superiority of the optimization control algorithm of the incremental PID parameters based on the RBF neural network servo control system.The experimental results of this model were compared with the simulation results.The average error between the established model and the actual system was 0.005175054(m),which was approximately 2.588%of the total travel length,demonstrating the accuracy of the theoretical model.

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Criteria Selecting Knowledge Base in the FuzzyController of the Electrohydraulic Position Control System

Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.

Impedance force control for position controlled robotic manipulators under the constraint of unknown environments

A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to generate the virtual reference trajectory for the target impedance model that is driven by the force error to produce command position. By following the command position trajectory the robotic manipulator can follow the unknown constraint surface while keeping an acceptable force error in a manner depicted by the target impedance model. Computer simulation on a 3 linked planar manipulator and experimental studies on an Adept 3, an SCARA type robotic manipulator, are conducted to verify the force tracking capability of the proposed control strategy.

Adaptive Backstepping Slide Mode Control of Pneumatic Position Servo System

With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental performance, as compared with some existing methods. results show that the designed controller can achieve better tracking

Position Control of a Flexible Manipulator Using a New Nonlinear Self-Tuning PID Controller

In this paper, a new nonlinear self-tuning PID controller(NSPIDC) is proposed to control the joint position and link deflection of a flexible-link manipulator(FLM) while it is subjected to carry different payloads. Since, payload is a critical parameter of the FLM whose variation greatly influences the controller performance. The proposed controller guarantees stability under change in payload by attenuating the non-modeled higher order dynamics using a new nonlinear autoregressive moving average with exogenous-input(NARMAX) model of the FLM. The parameters of the FLM are identified on-line using recursive least square(RLS) algorithm and using minimum variance control(MVC) laws the control parameters are updated in real-time. This proposed NSPID controller has been implemented in real-time on an experimental set-up. The joint tracking and link deflection performances of the proposed adaptive controller are compared with that of a popular direct adaptive controller(DAC). From the obtained results, it is confirmed that the proposed controller exhibits improved performance over the DAC both in terms of accurate position tracking and quick damping of link deflections when subjected to variable payloads.

Design and Reliability Analysis of DP-3 Dynamic Positioning Control Architecture

As the exploration and exploitation of oil and gas proliferate throughout deepwater area, the requirements on the reliability of dynamic positioning system become increasingly stringent. The control objective ensuring safety operation at deep water will not be met by a single controller for dynamic positioning. In order to increase the availability and reliability of dynamic positioning control system, the triple redundancy hardware and software control architectures were designed and developed according to the safe specifications of DP-3 classification notation for dynamically positioned ships and rigs. The hardware redundant configuration takes the form of triple-redundant hot standby configuration including three identical operator stations and three real-time control computers which connect each other through dual networks. The function of motion control and redundancy management of control computers were implemented by software on the real-time operating system VxWorks. The software realization of task loose synchronization, majority voting and fault detection were presented in details. A hierarchical software architecture was planed during the development of software, consisting of application layer, real-time layer and physical layer. The behavior of the DP-3 dynamic positioning control system was modeled by a Markov model to analyze its reliability. The effects of variation in parameters on the reliability measures were investigated. The time domain dynamic simulation was carried out on a deepwater drilling rig to prove the feasibility of the proposed control architecture

Flow Control for a Two-Stage Proportional Valve with Hydraulic Position Feedback

The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor valve.Essentially,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load pressure.The flow fluctuation severely restricts the application of the Valvistor valve.In this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow valve.The mathematical model of this valve is established and linearized.Fuzzy proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control system.The feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main orifice.The results show that inference with BPNN can obtain the flow data fast and accurately.With the flow control method,the flow can keep at the set point when the pressure differential across the main orifice changes.The flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow valve.For the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes abruptly.The performances of hysteresis,linearity and bandwidth are in a high range.The linear mathematical model can be verified and the assumptions in the system modeling is reasonable.

Position Control Optimization of Aerodynamic Brake Device for High-speed Trains

The aerodynamic braking is a clean and non-adhesion braking, and can be used to provide extra braking force during high-speed emergency braking. The research of aerodynamic braking has attracted more and more attentions in recent years. However, most researchers in this field focus on aerodynamic effects and seldom on issues of position control of the aerodynamic braking board. The purpose of this paper is to explore position control optimization of the braking board in an aerodynamic braking prototype. The mathematical models of the hydraulic drive unit in the aerodynamic braking system are analyzed in detail, and the simulation models are established. Three control functions--constant, linear, and quadratic--are explored. Two kinds of criteria, including the position steady-state error and the acceleration of the piston rod, are used to evaluate system performance. Simulation results show that the position steady state-error is reduced from around 12-2 mm by applying a linear instead of a constant function, while the acceleration is reduced from 25,71-3.70 m/s2 with a quadratic control function. Use of the quadratic control function is shown to improve system performance. Experimental results obtained by measuring the position response of the piston rod on a test-bench also suggest a reduced position error and smooth movement of the piston rod. This implies that the acceleration is smaller when using the quadratic function, thus verifying the effectiveness of control schemes to improve to system performance. This paper proposes an effective and easily implemented control scheme that improves the position response of hydraulic cylinders during position control.

Motor Imagery and Error Related Potential Induced Position Control of a Robotic Arm

The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.

Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators

A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.

Portable Dynamic Positioning Control System on A Barge in Short-Crested Waves Using the Neural Network Algorithm

This paper develops a nonlinear mathematical model to simulate the dynamic motion behavior of the barge equipped with the portable outboard Dynamic Positioning （DP） system in short-crested waves. The self-tuning Proportional- Derivative （PD） controller based on the neural network algorithm is applied to control the thrusters for optimal adjustment of the barge position in waves. In addition to the wave, the current, the wind and the nonlinear drift force are also considered in the calculations. The time domain simulations for the six-degree-of-freedom motions of the barge with the DP system are solved by the 4th order Runge-Kutta method which can compromise the efficiency and the accuracy of the simulations. The technique of the portable alternative DP system developed here can serve as a practical tool to assist those ships without being equipped with the DP facility while the dynamic positioning missions are needed.

Adaptive Observer Based Backstepping Controller Design for Dynamic Ship Positioning

Modified adaptive observer based backstepping control system for dynamic positioning of ship is proposed. As an improvement, the adaptive observer takes the first-order wave frequency model and the bias term which represent the slowly varying environmental disturbances and the unmodeled dynamics. Thus, the wave-frequency motions are filtered out, and only the reconstructed low-frequency motions are sent as inputs of the controller. Furthermore, as the ship dynamics parameters are unknown, the adaptive estimation law is designed for both the unknown ship dynamics and the unmeasured state variables. Based on the estimated states and parameters, backstepping controller considering the integral action is designed. Global exponential stability （GES） for the total system is proved using Lyapunov direct method. Simulation results show a good performance of the observer and control system.

Two-mode intelligent coordinating control of position for the welding positioner

A new intelligent control method for welding positioner is proposed. Applying an improved fuzzy controller and a variable PID controller, a two-mode intelligent coordinating controller ( TMICC ) is designed on basis of fuzzy logic and rules. The simulation and experimental results show that this control system can obtain better dynamic and static characteristics.

Nonlinear observer-controller design for dynamic positioning of ships

The main focus is nonlinear model-based dynamic positioning (DP) control system design. A nonlinear uniform global exponential stability (UGES) observer produces noise-free estimates of the position, the slowly varying environmental disturbances and the velocity, which are used in a proportional-derivative (PD) + feedforward control law. The stability of this observer-controller system is proved by introducing a specific nonlinear cascaded system. The simulation results have successfully demonstrated the performance of designed DP control system.

Virtual Reality Simulation of Fuzzy-logic Control during Underwater Dynamic Positioning

In this paper, graphical-user-interface （GUI） software for simulation and fuzzy-logic control of a remotely operated vehicle （ROV） using MATLABTM GUI Designing Environment is proposed. The proposed ROV＇s GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative （PID） and sliding-mode controller （SMC） systematically and interactively. External disturbance such as sea current can he added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.

Model Predictive Controller Design for the Dynamic Positioning System of a Semi-submersible Platform

This paper researches how to apply the advanced control technology of model predictive control （MPC） to the design of the dynamic positioning system （DPS） of a semi-submersible platform. First, a linear low-frequency motion model with three degrees of freedom was established in the context of a semi-submersible platform. Second, a model predictive controller was designed based on a model which took the constraints of the system into account. Third, simulation was carried out to demonstrate the feasibility of the controller. The results show that the model predictive controller has good performance and good at dealing with the constraints or the system.

H~∞ Theory and its Application to the Position of Rolling Mill Control System

The controller designed according to classical or modern control theory will not satisfy the performance requirements when the controlled object in industrial field can not be described by exact mathematical model or the disturbance of the controlled system. In order to make the controlled system stable and having good performance, H∞ control theory was put forward to solve this practical problem. Taking the position of a rolling mill as the controlled object, it was rectified by optimal engineering way. Then, three different plans were put forward according to Bang-Bang control, LQ control and H∞ control, respectively. The result of the simulation shows that the controller designed according to H∞ method whose robust performance and ability to restrain colors disturbance is satisfactory.