Analysis of Hydraulic Press Servo System Based on Robust Controller

The electro-hydraulic proportional position servo system is a kind of highly non-linear and time-varying system as well as parameter uncertainties. It is often difficult to achieve satisfactory control results with the traditional control methods. Considering that the adaptive neural network PID control method has the characteristics of online learning and adjustment PID control parameters adaptively, this paper puts forward to adopt BP-PID control method for the position servo control of electro-hydraulic proportional system. An online adaptive BP-PID controller is designed. The simulation model of the system is established based on Simulink platform. The step response and Sinusoidal tracking characteristics are researched for electro-hydraulic proportional position servo system by using traditional PID and BP-PID control algorithms through simulations and experiments. The results show that BP-PID has a strong ability of online learning and self-tuning PID parameters. Compared with the traditional PID control method, the BP-PID control has strong self-adaptability and robustness, and can significantly improve the step response speed and tracking control precision.

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.

This paper uses a particle swarm optimization (PSO) algorithm, an adaptive weighted PSO (AWPSO) algorithm, and a genetic algorithm (GA) to determine the optimal proportional-integral-derivative controller’s parameters of a hydraulic position control system. A typical hydraulic servo system has been selected as an application. The mathematical model of this hydraulic servo system which comprises the most relevant dynamics and nonlinear effects is considered. The model simulates the behavior of a REXROTH servo valve and includes the nonlinearities of friction forces, valve dynamics, oil compressibility, and load influence. The performance indices, which have been used in the optimization process, are integral absolute error, integral square error and integral time absolute error. The proposed controller is implemented on the simulation model to identify the best method for tuning the controller. Compared with GA and AWPSO results, the PSO method has been found to be more efficient and robust in improving the step response of a position control for hydraulic systems in terms of settling time, maximum overshoot and undershoot.

Aiming at electro-hydraulic servo control system, the simulation model of fault self healing is studied and combine artificial immune system to self-healing for the purpose of making the electro-hydraulic servo control system feel their own status in the engineering applications. Some components faults and early breakdown can be recognized by using communication and coordination between its components status information of each part. Through the self-healing strategy, realize the fault self-healing of the system. The simulation model of electro-hydraulic servo system is established through AMESim software and the common faults of electro hydraulic servo system are simulated and analyzed. According to the fault and the system structure, the fault self healing strategy of electro-hydraulic servo system based on immune principle is designed. The simulation results show the feasibility and effectiveness of the system.

Theoretical models of hydraulic pump-motor and electro-hydraulic servo control systems of hydraulic pumps were established and the system transfer function was derived In view of bad dynamic property, small damp, long transient time, low precision, nonlinearity and etc existing in the speed control system of Hydraulic Pump-Motor, a controller based on PID Neural Network was designed. The simulation results showed that the PID Neural Network controller has better dynamic property, load disturbance adaptability , robustness and cranking ability than traditional PID controller.

This study utilizes the direct neural control (DNC) based on back propagation neural networks (BPN) with specialized learning architecture applied to control the position of a cylinder rod in an electro-hydraulic servo system (EHSS). The proposed neural controls without the specified reference model use a tangent hyperbolic function as the activation function, and the back propagation error is approximated by a linear combination of error and error’s differential. The hydraulic cylinder subjected to varied load is also proposed. The simulation and experiment results reveal that the proposed neural controller is available to position control with high convergent speed, and enhances the adaptability and stability in varied load condition.KeywordsElectro-hydraulic servo systemPosition controlNeural networksBack propagation

Tele-operated bilateral hydraulic servo system with master-slave robot at the core can be complex manipulated in uncertain or extreme environment (such as space, seabed, radialization, battlefield, etc.). In this paper, it mainly researches control a force feedback bilateral master-slave servo system which is composed of electro-hydraulic servo system. In a tele-operated master-slave system, the master plays as a reference input device to the slave as well as a force feedback device. In order to feel a force fed back from the slave by the operator, a problem called back-drivability must be solved which an actuator in a hydraulic servo-system cannot be operated freely by manual means. As a practical solution to this problem, a driving method of actuator is proposed that a force sensor is used to attach the actuator. Furthermore, as an application of the sense of force proposed, a bilateral master-slave system is constructed which is composed of electro-hydraulic control system. Experimental results are given and shown that the “sense of force” can be fed by operator sensitively.

In order to solve the engineering application problems of the traditional variable pump pressure system driven by valve control or asynchronous motor associated with the rising temperature, complex structure etc, which could results in oil pollution resulted from leaking, low efficiency, and poor pressure retaining accuracy due to time-varying, nonlinear and hysteresis of the hydraulic power chuck. The unstable clamping force would cause machining error of parts. On the basis of analyzing the mathematical model of motor, power mechanism, execution mechanism and pressure sensor, the transfer function of direct drive pump controlled electric hydraulic pressure servo control system is derived, and a clamping force controller based on adaptive fuzzy PID control principle is proposed. The fuzzy rules and inference methods are used to tune the PID parameters online, and thus the flow rate of system is adjusted in real time to keep the clamping force constant. The effectiveness and feasibility of the proposed control method are verified with simulation and experiment. The results show that the fuzzy PID controller has a better dynamic performance and robustness than traditional PID controller, at the same time, the system has the fast response and no overshoot. This kind of system can completely meet the requirements on accuracy and stability of the clamping force in the machining process, especially for machining thin-walled parts.

APPLICATION OF OPTIMAL-TUNING PID CONTROL TO INDUSTRIAL HYDRAULIC SYSTEMS

Fault occurrence can be embodied by the physical parameter variations of the hydraulic servo system. Faults can, therefore, be diagnosed according to the model coefficient variations of the hydraulic servo system. This paper proposes an approach for fault diagnosis based on the unscented Kalman filter (UKF) with a mathematical model of the hydraulic servo system. The mathematical model is established using the dynamic equations of the hydraulic servo system. Based on the fault mechanism analysis results, several important system model parameters that can separately represent different faults in different components of the hydraulic servo system are chosen. Discrete state space equations are derived from the dynamic equations. The UKF algorithm is used to estimate the important system model parameters of the hydraulic servo system by utilizing the discretized state space model. According to the variations of these model parameters, the fault modes and locations of the hydraulic servo system can be diagnosed and isolated. Two types of faults, namely, abrupt fault in servovalve gain and slow wear fault in hydraulic cylinder piston, which cannot be directly detected from the system output, are introduced individually to the hydraulic servo system in this work. By comparing with the extended Kalman Filter, three different experimental cases are used to validate the effectiveness of the UKF for hydraulic servo system fault diagnosis.

This paper is concerned with the problem of predictive function control (PFC) for a class of hydraulic vibration servo control systems. Our aim is to design a new advanced control strategy such that the control system can track trajectory in a fast and accurate way. For this end, the mathematical model of the hydraulic vibration servo control system is firstly studied. By analyzing the nonlinear, time-varying, and model structure uncertainty features of the objects, the desired control strategy is presented based on PFC. Finally, the simulation results show that our proposed method is effective and can be used to improve the tracking speed, accuracy, and robustness.

To mitigate the significant impact of system nonlinearities, time-varying parameters, and external load disturbances on the output force of hydraulic servo systems in active hydraulic suspensions for engineering vehicles, this study proposes a beetle swarm optimization (BSO)-optimized extended state observer (ESO)-based sliding mode control (SMC) strategy. A comprehensive mathematical model of the hydraulic servo system is established, and an ESO-based SMC controller is designed, taking into account the coupled effects of chamber pressure dynamics and external loads on the uncertain output force. The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov stability theory. The effectiveness of the proposed control strategy is verified through both numerical simulations and experimental tests. For step inputs of 5000 N and 8000 N, overshoot is significantly reduced compared with the conventional proportional–integral–derivative control and the standard extended state observer-based sliding mode control, while the settling time is shortened by more than 65% in simulations and up to 75% in experiments. Under sinusoidal force excitations at frequencies of 0.5 Hz, 1 Hz, and 2 Hz, the maximum tracking error, mean error, and standard deviation of the tracking error are substantially reduced, with the maximum error reduction exceeding 90%. These results demonstrate that the proposed method achieves high-precision force tracking under external disturbances and pronounced system uncertainties, providing an effective solution for force control of hydraulic servo systems in active suspension applications for engineering vehicles.

A novel control strategy of Fuzzy-Immune PID based on PSO is proposed in this paper. The strategy learns from the immune feedback principle of biological immune system and takes advantage of the good approaching ability of fuzzy control to achieve nonlinear function of the immune controller, and then the PSO algorithm is used to optimize parameters of PID controller and immune controller. Apply the strategy into the hydraulic AGC control system of rolling mills with characteristics of high nonlinearity, time-varying and time-delay. The simulation results indicate that this strategy has strong adaptability to the transformation of the system parameters and has advantages of low overshoot, short adjusting time, strong anti-disturbance ability and great robustness.

The Direct Drive Volume Control (DDVC) Electro-hydraulic Servo System is a new Electro-hydraulic Servo System. It has the advantages of flexibility of AC servo motor control and high power of hydraulic servo system. Compared with the traditional electro-hydraulic servo system, the DDVC system is efficient, miniaturized integrated, convenient operated and economical. It has been used in many domains, and made great economic benefits. So it is widely considered to be one of the most important developing directions of the hydraulic control system. It will be widely used in more and more areas in the future. With the development of its application, how to improve the trajectory tracking precision of the DDVC system in low velocity motions becomes more important in the field. So that, the level of the low velocity characteristic impacted the system become to an important subject. In this paper, the mathematical mode of AC asynchronism motor Direct Torque Control was established, and the simulation mode was built. In addition, the idealized model of the DDVC system which based on united simulation of AMEsim/Simulink was established, simulation was executed. In order to make the research available, the low velocity characteristic of the DDVC system was also analyzed, and the low velocity characteristic simulation model was built. Computer simulation validated that the friction, the leakage and the mechanical losses are seriously influenced the system performance when the system working on the low velocity mode.

This study addresses the common issues of slow dynamic response and significant hysteresis in nonlinear electro-hydraulic systems, with a particular focus on optimizing the control performance of shotcrete robots operating under complex working conditions. The electro-hydraulic proportional control system was first designed and mathematically modeled. Based on input–output data collected under actual operating conditions of the shotcrete manipulator, signal preprocessing was performed using a wavelet soft-threshold denoising algorithm. Subsequently, system parameters were identified using a particle swarm optimization (PSO) algorithm enhanced by least squares estimation, resulting in a high-accuracy system transfer function. To overcome the limited robustness of traditional PID controllers under strong nonlinearities, as well as the real-time computational burden of standalone model predictive control (MPC), a dual-loop control strategy was proposed—employing PID feedback as the inner loop and MPC as the outer loop—to optimize and simulate the electro-hydraulic system. Experimental validation was conducted on a six-degree-of-freedom shotcrete robot platform through extension and rotational motion control tests of the robotic boom. Results show that, compared to conventional PID control, the proposed PID–MPC approach significantly improved system responsiveness and tracking accuracy. Specifically, in the extension test, the maximum tracking error decreased from 0.13 m/s to 0.04 m/s, and the maximum settling time was reduced from 3.0 s to 0.45 s; in the rotational test, the maximum tracking error dropped from 8°/s to 4°/s, and the maximum settling time shortened from 2.6 s to 0.8 s. This study offers a practical and effective solution for accurate modeling and high-performance control of complex electro-hydraulic systems, providing a solid theoretical foundation for the development and engineering application of intelligent and efficient shotcrete equipment.