Search

The rotor-bearing system is widely used in various high-end electro-hydraulic equipment, which provides specific support, rotation, and other integral functions. However, the fluctuating working conditions of the rotor-bearing system will cause more significant disordered fluctuations in the measured signals. This article proposes a new algorithm called multiscale deep graph convolutional networks (MS-DGCNs) to alleviate this problem. The designed MS-DGCNs algorithm combines a new multiscale intra-class fine coarse-grained processing and multiscale graph convolution kernels. Accordingly, an intelligent fault diagnosis method based on MS-DGCNs for the rotor-bearing system under fluctuating conditions is designed to learn more feature representations and accuracy. First, a sliding window is employed to divide the collected vibration signals into a series of subsignals. The multiscale signal processing is performed to obtain different degrees of the fine-coarse time series. Then, a graph convolution with the multiscale convolution kernel is designed. Finally, the soft-max classifier is combined for intelligent fault diagnosis. The experimental results of the double-span rotor-bearing system under fluctuating conditions well demonstrate that the method has the higher accuracy and generalization. [ABSTRACT FROM AUTHOR]

Uncertainties, especially mismatched uncertainties, pose great challenges to high accuracy tracking controller design for mechanical servosystems. In this article, a novel recursive robust integral of the sign of the error (RISE) control method is proposed for mechanical servosystems with mismatched uncertainties. In the controller development, two auxiliary error signals are introduced into the recursive backstepping design framework, and then, RISE feedbacks are synthesized to eliminate the matched and mismatcheduncertainties simultaneously. Moreover, to reduce the design conservatism, an adaptive recursive RISE control law is also developed for mechanical servosystems suffering from both parametric uncertainties and unmodeled disturbances, in which desired-trajectory-based adaptation law is synthesized to achieve compensation for parametric uncertainties. The proposed control methods can theoretically achieve remarkable asymptotic tracking performance with zero steady-state error in spite of matched and mismatched time-variant uncertainties. The proposed controllers are applied to an actual hydraulic servosystem and comparative experiments are performed to verify their effectiveness. [ABSTRACT FROM AUTHOR]

Velocity signal is difficult to obtain in practical electrohydraulic servomechanisms. Even though it can be approximately derived via numerical differentiation on position measurement, the strong noise effect will greatly deteriorate the achievable control performance. Hence, how to design a high-performance tracking controller without velocity measurement is of practical significance. In this paper, a practical adaptive tracking controller without velocity measurement is proposed for electrohydraulic servomechanisms. To estimate the unmeasurable velocity signal, an extended state observer (ESO) that also provides an estimate of the mismatched disturbance is constructed. The ESO uses the unknown parameter estimates updated by a novel adaptive law, which only depends on the actual position and desired trajectory. Moreover, the matched parametric uncertainty is also handled by online parameter adaptation and the matched disturbance is suppressed via a robust control law. The proposed ESO-based adaptive controller theoretically achieves an excellent asymptotic tracking performance when time-invariant modeling uncertainties exist. In the presence of time-variant modeling uncertainties, guaranteed transient performance and prescribed final tracking accuracy can also be achieved. The proposed control strategy bridges the gap between the adaptive control and disturbance observer-based control without using the velocity signal and preserves the performance results of both control methods while overcoming their practical performance limitations. Comparative experiments are performed on an actual servovalve-controlled double-rod hydraulic actuator to verify the superiority of the proposed control strategy. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

A desired compensation adaptive controller is proposed in this paper for precision motion control of electro-hydraulic servo systems, with consideration of the nonlinearity, modeling uncertainty, and especially the severe measurement noise arising from actual state feedbacks and deteriorating the control performance significantly. To alleviate the noise, actual states in the model-based compensation design are replaced with corresponding desired values. Considering that the general hydraulic system model contains unmatched modeling uncertainties (e.g., unmodeled nonlinear friction), an innovative approach to construct the desired values of the intermediate state variables is proposed in backstepping design procedure. It is then applied especially to the load pressure state, which appears in the system in a nonlinear way, and the discontinuous sign function is approximated by a continuous function to facilitate the controller design. As a result, the adaptive compensation and the regressor in the proposed controller depend on the desired trajectory and online parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance is expected. Theoretical analysis reveals that the proposed controller can guarantee a prescribed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. Moreover, it can guarantee the asymptotic tracking performance when subjected to parametric uncertainties only. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

This paper concerns high-accuracy tracking control for hydraulic actuators with nonlinear friction compensation. Typically, LuGre model-based friction compensation has been widely employed in sundry industrial servomechanisms. However, due to the piecewise continuous property, it is difficult to be integrated with backstepping design, which needs the time derivation of the employed friction model. Hence, nonlinear model-based hydraulic control rarely sets foot in friction compensation with nondifferentiable friction models, such as LuGre model, Stribeck effects, although they can give excellent friction description and prediction. In this paper, a novel continuously differentiable nonlinear friction model is first derived by modifying the traditional piecewise continuous LuGre model, then an adaptive backstepping controller is proposed for precise tracking control of hydraulic systems to handle parametric uncertainties along with nonlinear friction compensation. In the formulated nonlinear hydraulic system model, friction parameters, servovalve null shift, and orifice-type internal leakage are all uniformly considered in the proposed controller. The controller theoretically guarantees asymptotic tracking performance in the presence of parametric uncertainties, and the robustness against unconsidered dynamics, as well as external disturbances, is also ensured via Lyapunov analysis. The effectiveness of the proposed controller is demonstrated via comparative experimental results. [ABSTRACT FROM PUBLISHER]