Hydraulic Position Servo Research Articles

Analysis of Pressure Impact Characteristics of a Hydraulic Position Servo System Based on Series Servo Valves

As one of the causes of system vibration and noise, pressure impact is always undesired. Analysis of pressure impact characteristics of a hydraulic position servo system based on a two-stage series servo valve is carried out to reduce the system impact. The influence of factors such as system flow rate, additional servo valve opening gain, external load, and system overflow pressure on the system pressure impact is analyzed. The results show that the series servo valve scheme can bring down the peak impact pressure at the inlet of the hydraulic cylinder by 8%~11% when the system flow rate or overflow pressure is low to a certain extent. In most other cases, the suppression effect of the impact peak pressure is unapparent. The impact pressure overshoot is always decreased accompanied by an easier trend to overflow for the system. At last, another new idea of application promotion with higher reliability and adaptability is proposed.

Adaptive neural network-based sliding mode control for a hydraulic rotary drive joint

Hydraulic system has specific nonlinear and unknown modeling characteristics, realizing precise tracking control is a very challenging task. In this study, a sliding mode controller based on an adaptive higher-order neural network is proposed for realizing precise position-tracking control of a hydraulic rotary drive joint. First, the structural design and working principle of the target joint are introduced, and the mathematical model of the corresponding valve-controlled hydraulic position servo system is developed. Then, the adaptive neural network algorithm and sliding mode control are effectively combined. Based on the measurement information obtained from the control process, the feedback error is used to adaptively approximate the control parameters and realize online adjustment of the controller output. Finally, the parameter identification and position tracking of the system are validated, and the results indicate that the proposed strategy exhibits a 20% improvement in position-tracking control compared to the conventional sliding mode control methods.

Hydraulic System Modeling with Recurrent Neural Network for the Faster Than Real-Time Simulation

Depending on the task of a decision-support system, the underlying computer simulation can be carried out in real time or faster than real time. The required high simulation speed is a major obstacle in employing the more advanced simulation models. The work addresses the question of the recurrent neural network (RNN) usage for the faster than real-time simulation of hydraulic systems. Mathematical models of such systems are computationally expensive for numerical integration due to their high non-linearity and numerical stiffness. In this paper, a mathematical-based simulation model has been created using an experimentally verified mathematical model of a hydraulic position servo system (HPS). A RNN of the NARX architecture has been developed, trained and tested on the training data produced by the mathematical-based simulation model. A preprocessing technique has been developed and applied to the training data in order to speed-up the training and simulation processes. The obtained results for the first time show that the employment of the RNN together with the developed preprocessing technique ensures the simulation speed-up of the complex hydraulic system at the expense of a small accuracy decrease. In the considered case of the HPS, a simulation speed-up of factor 4.8 has been obtained.

A novel haptic interface and universal control strategy for International Thermonuclear Experimental Reactor (ITER) welding/machining assembly robot

Abstract This paper proposes a universal control strategy and novel haptic interface for the International Thermonuclear Experimental Reactor (ITER) welding/machining robot. The developed method implements a reliable position control and sense between the human and the robot as well as between the robot and the task environment in which provides highly accurate position control based on joystick inputs with real-time haptic capabilities. The proposed control structure has the characteristics of a universal technique independent of the actual control algorithm and it can be applied with other suitable control methods as a real-time control strategy. One of the contributions of this paper is that the proposed control method combines a directed random search method and real-time simulation to develop an intelligent controller in which each generation of parameters is tested on-line by the real-time simulator before being applied to the real process. The controller was evaluated on a hydraulic position servo system where the simulator of the hydraulic system was built based on Markov chain Monte Carlo (MCMC) method. A Particle Swarm Optimization (PSO) algorithm combined with the foraging behavior of E. coli bacteria was utilized as the directed random search engine. PSO is influenced by the simulation of social behavior in which each individual agent of the possible solution population, benefits from its history and its interactions with other agents within the population. This sharing of knowledge helps facilitate faster convergence to an optimal solution. From the other side, the effect of Bacterial Foraging Optimization (BFO) of E. coli is that the agent is making a decision to which position to move. The agent does this with attention to the previous data stored in the memory as the best past position. These selection behaviors of particles help to avoid poor foraging and improve foraging strategies. In conclusion, the proposed control and haptic strategy allows the operator to be kinetically plugged into the work environment and simultaneously provides force feedback sense with high controllability without neglecting the system dynamics.

Adaptive control of hydraulic position servo system using output feedback

Due to the properties such as small size-to-power ratio, large force output capability and fast response, the hydraulic position servo system is widely used in industrial automation fields. High-pr...

Intelligent method for tuning H2 PID controller of water hydraulic manipulator of CFETR blanket maintenances

Purpose – The purpose of this paper is to investigate an intelligent control for water hydraulic position servo system which is intent to be used in remote control robot for fusion reactor. The dynamic model of water hydraulic servo control system is built and proportional–integral–derivative (PID) controller is used. Design/methodology/approach – PID control is the most common control algorithm used in industry and has been a conventional tool used to operate closed-loop control system; however, it is very difficult to achieve high accuracy and fast response by using the traditional way to tune its perimeters. To improve the control performance, optimization algorithm can be applied to search the best parameters of PID. This paper presents a search algorithm using particle swarm with H2 control standards objective function to optimize PID parameters. Findings – By comparing simulation and mock-up experiments’ results from different control methods, the particle swarm optimization algorithm presents better performance and is more effective for tuning PID parameters. Originality/value – This paper presents an effective way to ensure safety and efficiency for remote handling maintenances of China Fusion Engineering Test Reactor.

Control System Design of Anti-rolling Tank Swing Bench Using BP Neural Network PID Based on LabVIEW

The anti-rolling tank swing bench is a typical hydraulic position servo system. Its function is to simulate the ship roll motion and to verify the performance of the anti-rolling tank. Generally, the PID control method can achieve an ideal control effect. But the uncertainties, such as the couplings and the nonlinearty of the swing bench, make it difficult to establish the precise mathematical model of system. During experiments, the different disturbance torques are generated according to the different dimension scales of the anti-rolling tanks. Changes of the natural characteristics of the system are caused by changes of load, and the fixed parameters of PID controller are difficult to continue to ensure a good control effect. In order to reduce the influences caused by the factors mentioned above, a BP neural network PID control system based on virtual instrument LabVIEW is designed. By simulating the responses of the system in real time control, the verification tests using actual system are avoided. Finally, the experiments of swing bench are carried out. The results show that the controller can ensure the control accuracy and stability. The parameters tuning process efficiency is improved. The operation is convenient. The data acquisition process is simple and practical.

New method to improve dynamic stiffness of electro-hydraulic servo systems

Most current researches working on improving stiffness focus on the application of control theories. But controller in closed-loop hydraulic control system takes effect only after the controlled position is deviated, so the control action is lagged. Thus dynamic performance against force disturbance and dynamic load stiffness can’t be improved evidently by advanced control algorithms. In this paper, the elementary principle of maintaining piston position unchanged under sudden external force load change by charging additional oil is analyzed. On this basis, the conception of raising dynamic stiffness of electro hydraulic position servo system by flow feedforward compensation is put forward. And a scheme using double servo valves to realize flow feedforward compensation is presented, in which another fast response servo valve is added to the regular electro hydraulic servo system and specially utilized to compensate the compressed oil volume caused by load impact in time. The two valves are arranged in parallel to control the cylinder jointly. Furthermore, the model of flow compensation is derived, by which the product of the amplitude and width of the valve’s pulse command signal can be calculated. And determination rules of the amplitude and width of pulse signal are concluded by analysis and simulations. Using the proposed scheme, simulations and experiments at different positions with different force changes are conducted. The simulation and experimental results show that the system dynamic performance against load force impact is largely improved with decreased maximal dynamic position deviation and shortened settling time. That is, system dynamic load stiffness is evidently raised. This paper proposes a new method which can effectively improve the dynamic stiffness of electro-hydraulic servo systems.

Study of Hydraulic Servo System Based on Fuzzy Sliding Mode Algorithm

Based on the situation that the hydraulic position servo system is easily influenced by the external interference and the parameters of which are different with time-varying, the fuzzy control can soften the buffeting and the sliding algorithm has no the same problems as the hydraulic position servo system, a brandly-new fuzzy sliding control algorithm is designed. In the simulation process, within the parameters of simulated time-varying and outside strong interference, the results show that the hydraulic servo system based on fuzzy sliding mode control algorithm has a greater resistance to internal and external interference and time-varying parameters.

Adaptive Fuzzy Sliding Mode Control of Asymmetrical Hydraulic Cylinder Based on DSP

An adaptive fuzzy sliding mode control strategy is designed to solve the problem of nonlinear, disturbances and uncertain parameters in asymmetric hydraulic cylinder position servo control system. Variable parameters and external disturbances of the system are identified by adaptive function. Meanwhile fuzzy exponential velocity reaching law is introduced to reduce the chatting phenomenon. Simulation results show the system dynamic performance is improved, the chattering phenomenon which caused by traditional sliding mode variable structure is weakened and the proposed algorithm is feasible. The algorithm control experiment of asymmetric hydraulic cylinder was done on the DSP28335 hardware platform. The experiment proves the effectiveness of the algorithm and achieves a good control result.

Fault Diagnosis in a Hydraulic Position Servo System Using RBF Neural Network

Considering the nonlinear, time-varying and ripple coupling properties in the hydraulic servo system, a two-stage Radial Basis Function (RBF) neural network model is proposed to realize the failure detection and fault localization. The first-stage RBF neural network is adopted as a failure observer to realize the failure detection. The trained RBF observer, working concurrently with the actual system, accepts the input voltage signal to the servo valve and the measurements of the ram displacements, rebuilds the system states, and estimates accurately the output of the system. By comparing the estimated outputs with the actual measurements, the residual signal is generated and then analyzed to report the occurrence of faults. The second-stage RBF neural network can locate the fault occurring through the residual and net parameters of the first-stage RBF observer. Considering the slow convergence speed of the K-means clustering algorithm, an improved K-means clustering algorithm and a self-adaptive adjustment algorithm of learning rate are presented, which obtain the optimum learning rate by adjusting self-adaptive factor to guarantee the stability of the process and to quicken the convergence. The experimental results demonstrate that the two-stage RBF neural network model is effective in detecting and localizing the failure of the hydraulic position servo system.

Hardware-in-the-loop environment for servo system controller design, tuning and testing

The paper analyses the possibility to replace the hydraulic and mechanical parts of a hydraulic position servo with a real-time simulation model. The aim is to test the controller hardware against the simulation model that includes the dynamics of the servo system as well as the feedback sensors and amplifier card. The requirements caused by this hardware-in-the-loop (HIL) approach are analyzed. A special attention is paid to the correct modeling of incremental encoders that are widely used as a feedback sensor. Experimental results show that there is no remarkable difference between the responses of the real system and HIL model and so the HIL model can replace the real system.

On-line trained neural controllers for nonlinear hydraulic system

This paper studies the problem to control the nonlinear dynamic model of an hydraulic servo system using neural networks. Hydraulic position servo systems are commonly used in industry. This kind of systems is nonlinear in nature and generally difficult to control. The ordinary linear constant gain controller will cause overshoot or even loss of system stability. Artificial neural networks (ANNs) are essentially adaptive systems able to learn how to perform complex tasks, and therefore, neurocontrol techniques are able to overcome many of the difficulties that conventional control techniques suffer when dealing with nonlinear plants or plants with unknown structure. The Direct Adaptive Neurocontrol approach is used in this application where learning is essentially performed on-line using the plant output error. Simulation results show that the proposed approach provides more accurate, robust, and efficient adaptive control for the nonlinear hydraulic system when compared to the traditionally used control methods.

COMPARISON OF WATER AND OIL HYDRAULIC POSITION SERVOS

So far not very much research has been done and not many experimental results are available on water hydraulic position servos. In this paper the feasibility of a design method similar to that used in oil hydraulic position servos is studied in water hydraulics. The P-controller water hydraulic position servo cylinder is designed in the way well known from oil hydraulics. The P-controller is used because it is simple, widely in use and good for comparison.The design process, theoretical equations and experimental results are presented. The variation rate in the position accuracy, settling time and dynamic behavior with different steps is shown. The specifications arrived at position accuracy, settling time and dynamics for the water hydraulic position servo system are compared with the oil hydraulic specifications. The applicability of the design method and the parameter approximations used in the P-controlled water hydraulic position servos is discussed.

Technical note Sliding mode control for a class of hydraulic position servo

The present paper discusses a sliding mode control method suitable for controlling a hydraulic position servo with a flexible load. Due to the requirements of the control system, the reference model is designed for the case of a flexible load. The core of sliding mode control is switching surfaces which are specially defined for the system according to the mathematical model and control goal. A novel algorithm is developed, and the simulated and experimental results of the control system are shown. The results show the extremely good robustness of the proposed method.

High-Accuracy Car Level Compensation Device for a Hydraulic Elevator. Stabilization using Estimated Acceleration Feedback.

The objective of this study is to improve the servo stiffness and stability of the high-accuracy car level compensation device in a hydraulic elevator, which is used to reduce the car position fluctuation caused by passengers getting on or Off. The previous compensation device is composed of an electro hydraulic position servo system. In order to enhance this system, an observer is introduced to estimate the car acceleration, and a pseudo-acceleration feedback control is applied. The performance of the modified compensation device is examined by carrying our stability analysis and an experiment, and it is shown that the proposed control method halves the position fluctuation and quarters the settling time compared to the previous method.

Development of fuzzy state controller and its application to a hydraulic position servo

By combining control theory and fuzzy set theory, a new kind of state controller is proposed. Full order feedback and membership functions, which utilize the experience of experts, are used in the design of the state controller which we call a fuzzy state controller. Hydraulic position servos with a nonsymmetrical cylinder are commonly used in industry. This kind of system is nonlinear in nature and generally difficult to control. For different ending position, moving direction, strokes, and load the system dynamics is totally different. Once the above-mentioned parameters of the system are known, it is relatively straightforward to tune the gains of state controller to obtain good dynamic response. But when these parameters change, especially in case of the load, using the same gains will cause overshoot or even loss of system stability. Adaptive control is not applicable in this case due to the complexity of the algorithm, its rate of convergence, and the fast response characteristic of the system. The fuzzy state controller has been successfully applied to a hydraulic position servo. The system shows excellent robustness against variations of system parameters.

Fuzzy state controller and its application in hydraulic position servo

By combining control theory and fuzzy set theory, a new kind of state controller is proposed. The ideas of time optimal set point control and membership function are used in the design of the state controller which we call fuzzy state controller (FSC). The FSC has been applied for the postion control of a hydraulic servo. The control effects of ordinary state controller and FSC are compared for different strokes. The experimental results confirm that FSC is much more robust than the state controller when the piston stroke is changed.

Design of Robust Two-Degree-of-Freedom Controllers for Position Servos Using H-Infinity Theory

Linear feedback controllers for position servos are designed using the structured singular value optimization (Doyle's μ-synthesis) method. The method produces a two-degree-of-freedom controller, including both the feedback and the prefilter, which is ‘performance robust’, in the sense that the closed-loop system is guaranteed to meet performance specifications in the presence of unmodelled dynamics. A detailed design of a low-order controller for a hydraulic position servo, including numerical non-linear simulation results, is presented.

Design of Robust Controllers for Position Servos Using H-Infinity Theory

Linear feedback controllers for position servos are designed using a frequency domain optimization method based on H∞ theory. This method aims to produce a low-order controller which is ‘robust’, in the sense that the closed-loop system is guaranteed to meet performance objectives in the presence of unmodelled dynamics. A detailed design of a controller for a hydraulic position servo, including experimental results, is presented.