Hydraulic systems are a class of typical complex nonlinear systems, which have been widely used in manufacturing, metallurgy, energy, and other industries. Nowadays, the intelligent fault diagnosis ...problem of hydraulic systems has received increasing attention for it can increase operational safety and reliability, reduce maintenance cost, and improve productivity. However, because of the high nonlinear and strong fault concealment, the fault diagnosis of hydraulic systems is still a challenging task. Besides, the data samples collected from the hydraulic system are always in different sampling rates, and the coupling relationship between the components brings difficulties to accurate data acquisition. To solve the above issues, a deep learning model with multirate data samples is proposed in this article, which can extract features from the multirate sampling data automatically without expertise, thus it is more suitable in the industrial situation. Experiment results demonstrate that the proposed method achieves high diagnostic and fault pattern recognition accuracy even when the imbalance degree of sample data is as large as 1:100. Moreover, the proposed method can increase about 10% diagnosis accuracy when compared with some state-of-the-art methods.
This paper addresses the position control of valve-controlled cylinder system employed in hydraulic excavator. Nonlinearities such as dead zone, saturation, discharge coefficient and friction existed ...in the system are highlighted during the mathematical modeling. On this basis, simulation model is established and then validated against experiments. Aim for achieving excellent position control performances, an improved particle swarm optimization (PSO) algorithm is presented to search for the optimal proportional-integral-derivative (PID) controller gains for the nonlinear hydraulic system. The proposed algorithm is a hybrid based on the standard PSO algorithm but with the addition of selection and crossover operators from genetic algorithm in order to enhance the searching efficiency. Furthermore, a nonlinear decreasing scheme for the inertia weight of the improved PSO algorithm is adopted to balance global exploration and local exploration abilities of particles. Then a co-simulation platform combining the simulation model with the improved PSO tuning based PID controller is developed. Comparisons of the improved PSO, standard PSO and Phase Margin (PM) tuning methods are carried out with three position references as step signal, ramp signal and sinusoidal wave using the co-simulation platform. The results demonstrated that the improved PSO algorithm can perform well in PID control for positioning of nonlinear hydraulic system.
•An improved PSO based PID is proposed for positioning of nonlinear hydraulic system.•Nonlinearities of hydraulic system are highlighted.•Selection and crossover operators are introduced into standard PSO algorithm.•Co-simulation platform is carried out to estimate the performance of controller.•Effectiveness of the improved PSO algorithm is validated by simulation.
Parametric uncertainty associated with unmodeled disturbance always exist in physical hydraulic systems, and complicate the advanced nonlinear controller design. In this paper, an adaptive ...compensation with a robust integral of the sign of the error (RISE) feedback is developed for high precise tracking control of hydraulic motion system. To handle both payload and hydraulic unknown parameters in one controller, a chain of integrator nonlinear system model is first derived, and an adaptive RISE controller is then proposed, in which adaptive law is synthesized to handle parametric uncertainty and RISE robust term to attenuate unmodeled disturbance. The major feature of the proposed controller is that it can theoretically guarantee asymptotic tracking performance with a continuous control input, in the presence of various parametric uncertainties and unmodeled disturbances such as unconsidered dynamics as well as external disturbances via Lyapunov analysis. However, the proposed controller takes the acceleration as a system state, which usually suffers heavy noise pollution and thus cannot be utilized directly in actual control. To solve this practical issue, in this paper, a tracking differentiator is employed to extract high-quality acceleration signal and to make the proposed controller feasible execution. The effectiveness of the proposed nonlinear controller is demonstrated via comparative experimental results.
Most recent studies on adaptive hydraulic tracking control focus on the trajectory tracking performance while the parameter convergence property is often unsatisfying. This article proposes a ...composite learning adaptive position tracking controller with improved parameter convergence for electro-hydraulic servo systems. In the composite learning, a prediction error is formulated to exploit input-output memory data, and parameter estimates are driven simultaneously by tracking and prediction errors. Practical exponential stability of the closed-loop system, which implies the convergence of both the tracking and parameter estimation error, is established by a more realizable interval-excitation condition than the stringent persistent-excitation condition. Therefore, superior trajectory tracking is obtained compared with the classical adaptive hydraulic control. Besides, the initial fluid control volumes of hydraulic systems are assumed to be unknown a priori , which enhances the generality of the proposed control approach. The abovementioned two properties are generally not achievable in prevalent approaches to adaptive hydraulic control. Moreover, noisy acceleration signals and the time derivatives of pressure signals are not needed in the proposed approach, which improves its robustness against measurement noise. Extensive experimental results verify its superiority over currently available ones.
Direct-driven electro-hydraulic systems have a wide range of applications owing to their advantages of energy-savings and relatively high control flexibilities in comparison with classic variable ...displacement pump-controlled hydraulic systems. However, the control accuracy is limited by the inherent nonlinear hydraulic dynamics. Additionally, the pump flow rate may become nonlinear at low pump speeds, causing large pressure-related flow deviations; thereby, limiting the improvement of motion control accuracy. Unfortunately, the pump flow nonlinearity has been ignored or oversimplified without effective modeling in most studies so far. To improve the control accuracy of direct-drive hydraulic systems, a high-precision control strategy must be designed to deal with the nonlinear characteristics and resolve the issue of nonlinear pump flow at low speeds. This article proposes an adaptive robust motion control strategy for a direct-driven electro-hydraulic system with adaptive pump flow rate model compensation. A backstepping integrated direct/indirect adaptive robust controller is designed to deal with the dynamic nonlinearities and uncertainties, which guarantees the stability of the entire hydraulic system. Furthermore, a parameterized polynomial fitting modeling strategy is proposed to accurately describe the nonlinear characteristics of the pump flow rate. Therefore, the uncertain parameters are adjusted in real-time, achieving satisfactory parameter estimations and model compensation for asymptotic motion tracking. Theoretical proof and comparative experiments demonstrate the advantages of the proposed control strategy with adaptive polynomial fitting model compensation for high-precision motion control.
In this paper, an output feedback nonlinear control is proposed for a hydraulic system with mismatched modeling uncertainties in which an extended state observer (ESO) and a nonlinear robust ...controller are synthesized via the backstepping method. The ESO is designed to estimate not only the unmeasured system states but also the modeling uncertainties. The nonlinear robust controller is designed to stabilize the closed-loop system. The proposed controller accounts for not only the nonlinearities (e.g., nonlinear flow features of servovalve), but also the modeling uncertainties (e.g., parameter derivations and unmodeled dynamics). Furthermore, the controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy, while achieving asymptotic tracking performance in the absence of time-varying uncertainties, which is very important for high-accuracy tracking control of hydraulic servo systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategy.
Variable speed pumped storage (VSPS) unit has various operation modes and it is often required by the dispatcher to convert rapidly and frequently between these modes. Unlike conventional units, ...however, VSPS is controlled by both excitation and hydraulic system, and control of them is independent of each other. The mismatch between the rapid electromagnetic response of the former and the relatively slow mechanical response of the latter could result in unfavorable transients or even conversion failure. Hence, coordination controls between excitation and hydraulic system during mode conversion is a meaningful topic but has seldom been investigated. To this end, the electromechanical transient model of VSPS considering the excitation dynamics of the converter is first established. Then, a multistage soft coordination control strategy is proposed in this article. By applying this strategy, the soft and smooth mode conversion of VSPS is achieved with favorable dynamic performances during the complete conversion process. And finally, simulation and experimental results verified the effectiveness of the strategy.
The problem of localizing two leaks using only flow rate and pressure measurements at the boundaries of a pipeline, and under steady-state flow conditions, is ill-posed due to the undetermined nature ...of the inverse problem, which involves two coupled equations with four unknowns associated with the presence of the leaks: two emitter coefficients and two locations. Therefore, attempting to solve this problem using any method without imposing additional constraints leads to an unbounded solution space, which contains solutions that may be physically meaningless. In this article, we propose a four-algorithm method that incorporates both spatial and hydraulic constraints to filter out physically infeasible solutions. The proposed method is based on Monte Carlo simulations, which use input data from hydraulic instruments installed at the boundaries of the pipeline, as well as random values with predefined probabilities that are bounded by the hydraulic-spatial constraints. The outputs of the method are probability distributions for the four unknowns. To demonstrate the feasibility of the method, results obtained through simulations and experimental testing on a test bed are presented.
•A four-algorithm method based on Monte Carlo simulations to localize two leaks in a pipeline.•The method incorporates spatial and hydraulic constraints to eliminate physically infeasible localization estimations.•Tests results using both synthetic and experimental data from a test bed.
Most of the existing control methods for servo systems driven by hydraulic actuators have been developed by using a backstepping scheme and assuming that all system states (including internal ...hydraulic signals) are measurable. In this paper, we propose a new control design method for high-order servo systems with hydraulic actuator dynamics, where the backstepping scheme is avoided and only the system output (e.g., motion displacement) is required for the control implementation. For this purpose, the system model is first transformed into a canonical form, where the unknown dynamics in the system are lumped as one term. Then, we introduce a simple robust unknown dynamics estimator (UDE) that has only one tuning parameter but achieves exponential error convergence to accommodate the lumped uncertainties. Therefore, the function approximators (e.g., neural network and fuzzy systems) can be avoided, leading to reduced computational costs, simpler parameter tuning, and improved convergence as compared to backstepping methods. Extensive simulations and experiments based on a realistic test rig are conducted to show the efficacy of the proposed control.
This paper presents an active disturbance rejection adaptive control scheme via full state feedback for motion control of hydraulic servo systems subjected to both parametric uncertainties and ...uncertain nonlinearities. The proposed controller is derived by effectively integrating adaptive control with extended state observer via backstepping method. The adaptive law is synthesized to handle parametric uncertainties and the remaining uncertainties are estimated by the extended state observer and then compensated in a feedforward way. The unique features of the proposed controller are that not only the matched uncertainties but also unmatched uncertainties are estimated by constructing two extended state observers, and the parameter adaptation law is driven by both tracking errors and state estimation errors. Since the majority of parametric uncertainties can be reduced by the parameter adaptation, the task of the extended state observer is much alleviated. Consequently, high-gain feedback is avoided and improved tracking performance can be expected. The proposed controller theoretically achieves an asymptotic tracking performance in the presence of parametric uncertainties and constant disturbances. In addition, prescribed transient tracking performance and final tracking accuracy can also be guaranteed when existing time-variant uncertain nonlinearities. Comparative experimental results are obtained to verify the high tracking performance nature of the proposed control strategy.
