Control Of Hydraulic Actuator Research Articles

Adaptive Online Neural Predictive Control of Hydraulic Actuator Using FPGA Acceleration

Hydraulic actuators have recently been widely used in control systems as efficient output devices. However, high-precision control of hydraulic actuators in industrial applications remains challenging due to the conflict between controllers' complexity, especially in theoretical modeling, and their generalization abilities, including adaptability to parametric uncertainties and versatility for various working conditions. To address this issue, we propose an adaptive online neural predictive control (AONPC) scheme, which is capable of handling unmodeled nonlinearities and uncertainties with a simple structure and low demand for system modeling. Specifically, an artificial neural network (ANN) is responsible for data-driven system identification and predictive control, while upper confidence bound (UCB) algorithm is introduced for hyperparameter self-adaptation. The ANN structure and the iteration number for solving the optimization problem are determined through a simulation study. Then, to complete the whole control loop within a short and fixed tracking interval, the proposed controller is implemented on a field programmable gate array (FPGA), which can effectively improve the tracking precision. Finally, extensive experimental results on a realistic hydraulic actuator device demonstrate the superiority of the proposed controller.

Accurate Finite-Time Motion Control of Hydraulic Actuators With Event-Triggered Input

Accurate Finite-Time Motion Control of Hydraulic Actuators With Event-Triggered Input

Super-twisting based sliding mode control of hydraulic actuator without velocity state

This paper provides a novel surface design and experimental evaluation of a super-twisting algorithm (STA) based control for hydraulic cylinder actuators. The proposed integral sliding surface allows to track a sufficiently smooth reference without using the velocity state which is hardly accessible in the noisy hydraulic systems. A design methodology based on LMI’s is given, and the STA gains are designed to be adjusted by only one free parameter. The feasibility and effectiveness of the proposed control method are shown on a standard hydraulic test bench with one linear degree of freedom and passive load, where a typical motion profile is tracked with a bounded average error below 1% from the total drive effective output.

Experiment and analysis of drop-weight damping control of MR semi-active impact resistance-based hydraulic actuator

The impact vibration caused by sudden changes in the external load of hydraulic actuators reduces the service life of hydraulic components and limits the high-precision applications of hydraulic actuators. Therefore, to improve the underdamped characteristics and impact resistance of valve-controlled cylinder systems, a semi-active impact resistance control of hydraulic actuator based on magnetorheological damper (MRD) is proposed. Firstly, based on the shear force characteristics of magnetorheological fluid, a multi-stage flow channel MRD is designed, which is connected in series with the hydraulic actuator to form a hydraulic damping actuator (HDA). Meanwhile, based on the mechanical experimental data, the parameters of MRD dynamic model are identified to ensure the accuracy of MRD output force. Secondly, a drop weight impact model is established, and a sliding mode controller which can track the command current in real time is designed, so as to realize the resistance force coupling between the MRD and the hydraulic actuator for improving the impact resistance control effect. Then the dynamic performance test and impact resistance simulation program are established to verify the excellent dynamic performance and impact resistance effect of the HDA with the sliding mode control. Finally, the drop weight impact experimental platform is built. The experimental results show that under the impact with a height of 200 mm, the dynamic offset of the HDA is only −1.25 mm, and the time to return to the original position is 0.08 s, which validate the excellent performance of the proposed scheme in improving the underdamped characteristics of the valve-controlled cylinder system and the dynamic response performance of the hydraulic actuator.

Motion control of hydraulic actuators with nonlinear friction compensation: Applied to variable valve systems of diesel engine

Friction force plays an important role in motion control systems. Research shows that friction force is strongly nonlinear in most applications. And the nonlinear friction force has great influence on control performance, especially in motion control systems of hydraulic actuators. To improve control performance, many model-based controllers have been developed. In the past years, LuGre model has been widely used in most hydraulic actuators. However, for systems with one-way seals whose friction force is asymmetric between instroke and outstroke stage, LuGre model is no longer suitable. The paper developed a friction force test bench and studied the transient friction force of a hydraulic actuator which includes one-way seals. Experiment results show that friction force at instroke stage is bigger than that of outstroke stage for the variable valve actuator. Based on the experiment results, a bristle direction hypothesis is proposed. The bristle of the friction surface is thought to have an initial direction. For actuators with two-way seals or without seals, the bristle is thought to be perpendicular to the friction surface. And for actuators with one-way seals, the angle between bristles and friction surface is not 90° anymore. To apply the bristle direction hypothesis to controllers, a bristle direction coefficient is introduced to LuGre model to explain asymmetric friction behaviors. The simulation results have good agreements with experiment results. Based on the improved LuGre model, a backstepping controller is developed to compensate the nonlinear friction force. The friction force and system matched uncertainty are estimated by an extended state observer. Finally, some comparative experiments are implemented to verify the advantages of the improved LuGre model. The experiment results show that the improved LuGre model can help to reduce the engine valve lift tracking errors. At outstroke stage (engine valve close), the maximum absolute errors can be reduced by 40.6% to 65.0%, and the mean absolute errors can be reduced by 21.2% to 59.4%.

Adaptive Super-twisting Sliding Mode Control of Hydraulic Servo Actuator with nonlinear features and modeling uncertainties

This study proposes a novel adaptive super-twisting sliding mode controller (ASTSMC) for hydraulic servo actuator with nonlinear features and modeling uncertainties. In the proposed method, an extended state observer (ESO) is utilized to estimate the value of lumped uncertainties. The core feature of this paper is the combination of ASTSMC with ESO to compensate disturbance in hydraulic servo actuator. Moreover, the proposed ASTSMC does not need to obtain the bound of uncertainties in advance and ensures the sliding variable and its derivative reach to zero in a finite time. In addition, the stability of the closed-loop is proved by Lyapunov theory. Simulation and experiment results demonstrate the proposed ASTSMC can effectively mitigate the lumped uncertainties and obviously improve the tracking performance.

Fault-tolerant control of a hydraulic servo actuator via adaptive dynamic programming

<abstract><p>The fault-tolerant control problem of a hydraulic servo actuator in the presence of actuator faults is studied utilizing adaptive dynamic programming. This task is challenging because of unknown system dynamics, uncertain disturbances or unmeasurable system states of such highly nonlinear systems in real applications. The aim is to achieve asymptotic tracking and actuator faults compensation by minimizing some predefined performance index. The discrete-time algebraic Riccati equation is iteratively solved by the adaptive dynamic programming approach. For practical reasons, adaptive dynamic programming techniques and fault compensation are integrated to iteratively compute an approximated optimal fault-tolerant control using real-time input/output data without any a priori knowledge of the system dynamics and unmeasurable states. As a result, a fault-tolerant control of hydraulic servo actuator is then designed based on adaptive dynamic programming via output feedback. Also, the convergence analysis of a data-driven fault-tolerant control is theoretically shown as well. Finally, intensive simulation results are given to prove the validity and merits of the developed data-driven fault-tolerant control strategy.</p></abstract>

Data-driven control of hydraulic servo actuator: An event-triggered adaptive dynamic programming approach.

Hydraulic servo actuators (HSAs) are often used in the industry in tasks that request great power, high accuracy and dynamic motion. It is well known that an HSA is a highly complex nonlinear system, and that the system parameters cannot be accurately determined due to various uncertainties, an inability to measure some parameters and disturbances. This paper considers an event-triggered learning control problem of the HSA with unknown dynamics based on adaptive dynamic programming (ADP) via output feedback. Due to increasing practical application of the control algorithm, a linear discrete model of HSA is considered and an online learning data driven controller is used, which is based on measured input and output data instead of unmeasurable states and unknown system parameters. Hence, the ADP-based data driven controller in this paper requires neither the knowledge of the HSA dynamics nor exosystem dynamics. Then, an event-based feedback strategy is introduced to the closed-loop system to save the communication resources and reduce the number of control updates. The convergence of the ADP-based control algorithm is also theoretically shown. Simulation results verify the feasibility and effectiveness of the proposed approach in solving the optimal control problem of HSAs.

Nonlinear Model Learning for Compensation and Feedforward Control of Real-World Hydraulic Actuators Using Gaussian Processes

This paper presents a robust machine learning framework for modeling and control of hydraulic actuators. We identify several important challenges concerning learning accurate models of the dynamics for real machines, including noise and uncertainty in state measurements, nonlinear effects, input delays, and data-efficiency. In particular, we propose a dual-Gaussian process (GP) model architecture to learn a surrogate dynamics model of the actuator, and showcase the accuracy of predictions against the piecewise and neural network models that have been widely used in the literature. In addition, we provide robust techniques for learning neural network inverse models and controllers by batch GP inference in an automated, seamless and computationally fast manner. Finally, we demonstrate the performance of the trained controllers in real-world feedforward and tracking control applications.

Force Tracking Impedance Control of Hydraulic Series Elastic Actuators Interacting with Unknown Environment

Force tracking control for hydraulic series elastic actuators (SEAs) is the demand in robots interacting with the surrounding world. However, the inherent nonlinearities and uncertainties of the hydraulic system, as well as the unknown environment, make it difficult to achieve precise contact force control of hydraulic SEAs. Therefore, in this study, force tracking impedance control of hydraulic SEAs is developed considering interaction with an unknown environment in which the force tracking performance can be guaranteed in theory. Based on the typical force tracking impedance frame, the force tracking performance is improved by introducing backstepping control into the inner position controller to deal with the high-order nonlinear dynamics of the hydraulic SEA. In addition, the environment parameters are also estimated online by the adaptive method. Finally, comparative simulation is conducted with different interacting environments, which verifies the advantages of the proposed method.

Controller-extensible hybrid simulation platform for viscoelastically damped frame structures based on Matlab-Opensees frameworks

Most of hybrid simulation platforms (HSPs) that use OpenSees for structural hybrid testing research are developed based on OpenFresco framework software. Although OpenFresco is mature and reliable, it can only communicate with specific hydraulic servo actuator control systems, which limits the diversity and flexibility of HSP development. Matlab has powerful independent development functions, and has a wide range of communication interface advantages with many finite element software and actuator control systems. Therefore, Matlab can be used as the communication medium between OpenSees and actuator control system in this study. Firstly, the controller-extensible HSP based on Matlab-OpenSees frameworks is developed. Then, the core establishment details of HSP, including core architecture, hardware system, and DELTA-Matlab-OpenSees system, are analyzed and described in detail. Next, the dynamic loading tests on the spring components are carried out when the HSP is subjected to continuously changing working conditions in the wide frequency domain and displacement amplitude domain. The comparative analysis results on the target displacement curve and the measured displacement curve verify the accuracy and robustness of the inner control loop of HSP. Next, the hybrid tests on a three-story reinforced concrete frame structure with linear springs are implemented under different seismic wave excitations. The comparative research on the hybrid test results and time-history analysis results verifies the accuracy and robustness of the developed HSP (outer control loop) in this study. Lastly, on this basis, a series of hybrid tests on viscoelastically damped frame structures are conducted under different seismic wave excitations. The test results truly reveal the control rule on the seismic response of reinforced concrete frame structures affected by viscoelastic dampers.

High-Frequency Position Servo Control of Hydraulic Actuator with Valve Dynamic Compensation

Hydraulic actuators play an important role in various industries. In the last decades, to improve system performance, some advanced control methods have been developed. Backstepping control, which can deal with the system nonlinearities, is widely used in hydraulic system motion control. This paper focuses on the high-frequency position servo control of hydraulic systems with proportional valves. In backstepping controllers, valve dynamics are usually ignored due to difficulty of controller implementation. In this paper, valve dynamics of the proportional valve were decoupled into phase delay and amplitude delay. The valve dynamics are compensated without increasing the system order. The phase delay is compensated by desired engine valve lifts transformation. For amplitude delay, the paper proposes a compensation strategy based on the integral flow error. By introducing the feedback of the integral flow error to the backstepping controller, the system has faster dynamic responses. Besides, the controller also synthesized proportional valve dead-zone and system uncertainties. The comparative experiment results show that the controller with integral flow compensation can improve engine valve lift tracking precision both in steady and transient conditions.

Data-driven control of hydraulic servo actuator based on adaptive dynamic programming

<p style='text-indent:20px;'>The hydraulic servo actuators (HSA) are often used in the industry in tasks that request great powers, high accuracy and dynamic motion. It is well known that HSA is a highly complex nonlinear system, and that the system parameters cannot be accurately determined due to various uncertainties, inability to measure some parameters, and disturbances. This paper considers control problem of the HSA with unknown dynamics, based on adaptive dynamic programming via output feedback. Due to increasing practical application of the control algorithm, a linear discrete model of HSA is considered and an online learning data-driven controller is used, which is based on measured input and output data instead of unmeasurable states and unknown system parameters. Hence, the ADP based data-driven controller in this paper requires neither the knowledge of the HSA dynamics nor exosystem dynamics. The convergence of the ADP based control algorithm is also theoretically shown. Simulation results verify the feasibility and effectiveness of the proposed approach in solving the optimal control problem of HSA.</p>

Integral Nonsingular Terminal Sliding Mode Control of Hydraulic Servo Actuator Based on Extended State Observer

Hydraulic servo actuator always suffers from various disturbance and uncertainties, which makes it difficult to design a higher performance controller. In this paper, an integral nonsingular terminal sliding mode controller based on extended state observer (ESO-INTSM) is proposed to improve the robust performance of hydraulic servo actuator. The ESO is designed to estimate not only the parametric uncertainties but also the model disturbance. Based on the observed states of ESO, the proposed controllers could enable hydraulic servo actuator to track the desired motion trajectories. The stability of the synthesized controller is proved via Lyapunov analysis, which is very important for high-accuracy tracking control of hydraulic servo actuator. Simulation and experimental results demonstrate that the proposed control strategy can effectively attenuate the adverse influence caused by the uncertainties and apparently improve the tracking accuracy.

A dynamic electrically driven soft valve for control of soft hydraulic actuators

Regulation systems for fluid-driven soft robots predominantly consist of inflexible and bulky components. These rigid structures considerably limit the adaptability and mobility of these robots. Soft valves in various forms for fluidic actuators have been developed, primarily fluidically or electrically driven. However, fluidic soft valves require external pressure sources that limit robot locomotion. State-of-the-art electrostatic valves are unable to modulate pressure beyond 3.5 kPa with a sufficient flow rate (>6 mL⋅min-1). In this work, we present an electrically powered soft valve for hydraulic actuators with mesoscale channels based on a different class of ultrahigh-power density dynamic dielectric elastomer actuators. The dynamic dielectric elastomer actuators (DEAs) are actuated at 500 Hz or above. These DEAs generate 300% higher blocked force compared with the dynamic DEAs in previous works and their loaded power density reaches 290 W⋅kg-1 at operating conditions. The soft valves are developed with compact (7 mm tall) and lightweight (0.35 g) dynamic DEAs, and they allow effective control of up to 51 kPa of pressure and a 40 mL⋅min-1 flow rate with a response time less than 0.1 s. The valves can also tune flow rates based on their driving voltages. Using the DEA soft valves, we demonstrate control of hydraulic actuators of different volumes and achieve independent control of multiple actuators powered by a single pressure source. This compact and lightweight DEA valve is capable of unprecedented electrical control of hydraulic actuators, showing the potential for future onboard motion control of soft fluid-driven robots.

Open Loop Position Control of Soft Hydraulic Actuators for Minimally Invasive Surgery

Minimally invasive surgery (MIS) presents many constraints on the design of robotic devices that can assist medical staff with a procedure. The limitations of conventional, rigid robotic devices have sparked interest in soft robotic devices for medical applications. However, problems still remain with the force exertion and positioning capabilities of soft robotic actuators, in conjunction with size restrictions necessary for MIS. In this article we present hydraulically actuated soft actuators that demonstrate highly repeatable open loop positioning and the ability to exert significant forces in the context of MIS. Open loop position control is achieved by changing the actuator volume, which causes contraction. In one degree of freedom (DOF) configurations, root mean square error (RMSE) values of 0.471 mm, 1.506 mm, and 0.350 mm were recorded for a single actuator against gravity, a single actuator with a pulley, and a horizontal antagonistic configuration, respectively. Hysteresis values of 0.711 mm, 0.958 mm, and 0.515 mm were reported in these experiments. In addition, different numbers of soft actuators were used in configurations two and three DOFs to demonstrate position control. When deactivated, the soft actuators are low-profile and flexible as they are constructed from thin films. As such, a robot with a deployable structure and three soft actuators was constructed. The robot is therefore able to reversibly transition from low to high volume and stiffness, which has potential applications in MIS. A user successfully controlled the deployable robot in a circle tracing task.

Output feedback backstepping control of hydraulic actuators with valve dynamics compensation

Valve dynamics play an important role in the high-dynamic tracking performance of hydraulic systems. However, how to effectively compensate them remains an issue. From the frequency-domain analysis, it is recognized that the core effect of valve dynamics is the phase lag within the frequency range of interest. In this paper, a time-delay model which does not increase the entire system order is innovatively proposed to approximate the valve dynamics. As a result, the “explosion of complexity” in the backstepping control could be greatly alleviated. By introducing an auxiliary signal and incorporating a concept of desired-trajectory-based feedforward compensation, a practical output feedback backstepping controller is proposed for the motion control of a hydraulic actuator with integration of a robust delay compensating feedback and an extended state observer (ESO). The constructed ESO provides the estimates of both unmeasurable states and matched uncertainty, which ensures that the proposed controller only uses the output information and improves the system robustness. In addition, the valve dynamics are effectively compensated by the robust delay compensating feedback which contains a finite integral of past control values. The Lyapunov-based closed-loop system stability analysis using a Lyapunov-Krasovskii functional revealed that a uniformly ultimately bounded tracking performance is guaranteed by the proposed controller. Comparative experiments were conducted to verify the effectiveness of the proposed control strategy.

Control of the Test Rig for Spring Stiffness Measurement with Hydraulic Integrated Actuator and Computer Vision

The paper deals with the control of the test rig for measurement of the stiffness of the spring. The test rig is equipped with integrated hydraulic actuator and multilayer control system with computer vision to automate the testing process and to increase the safety of the operating staff during the testing. The integrated hydraulic actuator allows to control the piston velocity and position and to produce the force needed for the spring compression and stiffness measurement. It has an integrated manifold with four proportional flow control valves connected as the full hydraulic resistance bridge. Each control valve is controlled separately using the input signal. That makes it possible to realize different connections and control strategies of the hydraulic cylinder using the different control algorithms. The hydraulic circuit was modelled and simulated, and the achieved simulation results are presented in the paper. The test rig is controlled using the microprocessor control system and is it equipped by different transducers – position transducer, pressure transducers and force transducer to be able to collect data important for the stiffness characteristic evaluation. The upper level of the control system is created by the vision control system. The goal of the implementation of the machine vision is to decrease the number of the manual operations done by the technician by the spring testing and to extend the automatic testing cycle of the automatic computer vision-controlled movement of the actuator at the beginning of the testing cycle and finally to increase the safety of the operating staff. The structure and functionality of the designed control system, experimentally obtained results and evaluated stiffness characteristic of the tested spring are presented in the following chapters.

Feedforward and repetitive control of a servo piezo-mechanical hydraulic actuator

In this paper a hybrid actuator is proposed. The hybrid actuator consists of a piezo-mechanical structure and a hydraulic ratio displacement. Particular attention is paid to a liquid spring model of the displacement ratio which represents the hydraulic part of the mechanism to control an intake and exhaust valve of a combustion engine. The whole mechanism is controlled using a cascade repetitive control to track a periodic signal combined with a proportional derivative (PD) regulator and a feedforward action. Measured results are shown.

Low-delay Admittance Control of Hydraulic Series Elastic Actuator for Safe Human-Robot Collaboration

Current industrial manufacturing standards highlight safe human-robot collaboration. Therefore, compliance solutions, whether passive or active, are necessary. In this regard, series elastic actuators (SEAs) have attracted extensive interest for applications in industrial robotics owing to the low output impedance of these actuators, which can enhance interaction safety. Although considerable efforts have been expended to improve the control accuracy of SEAs, the time delay in impedance/admittance control has remained an unexplored problem. The use of filters in conventional methods can result in large time delay and considerable amplitude errors that degrade the performance and increase the risk of injury. This study resolves this problem by developing a method for low-delay admittance control of hydraulic SEAs. An external force observer (EFO)-based admittance scheme is first formulated. Thereafter, adaptive time series (ATS) compensators are introduced to improve position control and EFO. Based on the improved position controller and the ATS-based EFO (ATS-EFO), a novel low-delay admittance control scheme is developed. The proposed method only uses the load mass and spring stiffness information, thereby facilitating its application. Simulation experiments are performed to demonstrate the SEA control performance on position tracking, external force estimation, and stiffness tracking. The results confirm that the time delay and the amplitude error in these tests are significantly reduced by the proposed method.