Modeling and Robust Discrete-Time Sliding Mode Control Design for a Fluid Power Electrohydraulic Actuator (EHA) System

In this paper, a fault detection, identification and estimation approach has been developed for the condition monitoring of the electro-hydraulic actuator (EHA) system using the multiple-model (MM) estimation algorithm. The MM estimation algorithm makes use of the extended Kalman filter (EKF) technique to generate estimates of states and key physical parameters, which are related to faults in the EHA system. The proposed fault detection and identification (FDI) is formulated as a hybrid interacting multiple-model estimation scheme. The interaction scheme between multiple models is introduced into the MM estimation algorithm to yield more robust detection and estimation. Estimates of the key physical parameters in the EHA system are assessed against baseline values and fused with the FDI results for higher level monitoring purposes. Two parameters of interests, namely torque motor equivalent resistance and the effective bulk modulus are investigated for the EHA system condition monitoring purpose. The simulation results highlight the considerable potential of the proposed technique for achieving improved condition monitoring of the EHA system.

Motion control applications are widely applied in the industrial field with the assistance of electro-hydraulic actuator (EHA) system. EHA system is well known to be disclosed to the parameter variations, disturbances and uncertainties which are affected by the changes in the operating conditions such as friction, internal and external leakage. The complexity and nonlinear characteristic of the EHA system leads to a great challenge for controller development and system modelling. The performance of the utilized controller can be improved in order to achieve its best capability. In this paper, the basic knowledge in optimization of the proportional-integral-derivative (PID) controller through Gradient Descent (GD) and Particle Swarm Optimization (PSO) techniques are discussed. The PID parameters obtained through Ziegler-Nichols (ZN) tuning method has been optimized by using the GD method and is compared with PSO optimization technique via MATLAB/Simulink software. The findings show significant improvement in positioning tracking performance when the developed optimization technique is applied. Therefore, the issues degrading the EHA system performance have been reduced.

Exoskeleton robots have been developed in various fields and are divided into electric and hydraulic exoskeletons according to the actuator type. In the case of hydraulic robots, because a unidirectional pump is applied, there are limitations to the wearer’s walking. In addition, robot systems are complicated, because a directional control valve is required to change the direction of the actuator. To solve these problems, we designed the electro-hydraulic actuator (EHA) system which has both the hydraulic and electric advantages. The EHA system consists of a hydraulic bidirectional pump, a motor, a hydraulic cylinder, and various valves. For the development of the piston pump, we analyzed the gait cycle and considered the flow rate and pulsation rate. In order to reduce the size and weight of the EHA system, the valves were made from one manifold, and the hydraulic circuit was simplified. We verified that the developed EHA system is applicable to robots through position and force control experiments. Because the hydraulic system is nonlinear, we designed a sliding mode control (SMC) and compared it with the proportional integral derivative (PID) controller.

Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling technique has proven to be able to model various nonlinear systems. The objective of this paper is to obtain an ANFIS model from EHA system stimulus-response data. The prediction ability of ANFIS is also tested using limited data set for model training. Results show that ANFIS model is able to estimate nonlinear EHA system with high precision, even when training data provided is limited.

A draw wire sensor is considered as a contact measurement method. It is normally used to measure the speed and position of a system. A draw wire sensor is convenient especially when a low cost solution and a small sensor dimension are desired. The objective of this paper is to describe the application of draw wire sensor in control tracking of electro hydraulic actuator system. This research started with the modelling of electro hydraulic actuator system by using system identification approach. During the data taking process, an experiment is conducted using electro hydraulic actuator test bed. A draw wire sensor is attached to the load of electro hydraulic actuator system to measure the output displacement when the system is injected with the desired input signal. Draw wire sensor is measuring the output displacement in millimeters and then the signal is converted to voltage reading regarding to the given input signal. The input and output signal is collected and is used in system identification technique to obtain the best mathematical model that can represent the electro hydraulic actuator system. Once a model is obtained, a Self Tuning Controller (STC) with Generalize Minimum Variance Control (GMVC) strategy is designed to control the tracking performance of the electro hydraulic actuator system. The designed controller is tested in simulation and experiment mode. Then, the output result from both modes is compared. The results show that the output performance from both modes are almost similar. Thus, this research had shown that a draw wire sensor has a significant role in capturing an accurate output data from electro hydraulic actuator system even with or without the controller.

Electro-hydraulic servo actuation system is a mechanical, electrical and hydraulic mixing complex system. If it can't be repaired for a long time, it is necessary to consider the possibility of occurrence of multiple faults. Considering this possibility, this paper presents an extended Kalman filter (EKF) based method for multiple faults diagnosis. Through analysing the failure modes and mechanism of the electro-hydraulic servo actuation system and modelling selected typical failure modes, the relationship between the key parameters of the system and the faults is obtained. The extended Kalman filter which is a commonly used algorithm for estimating parameters is used to on-line fault diagnosis. Then use the extended Kalman filter to diagnose potential faults. The simulation results show that the multi-fault diagnosis method based on extended Kalman filter is effective for multi-fault diagnosis of electro-hydraulic servo actuation system.

This paper presents the position tracking performance of an electro-hydraulic hydraulic actuator (EHA) system by using a discrete sliding mode control (DSMC). A point-to-point trajectory is used in the experimental works to evaluate the performance of the DSMC which is design in two-degree-of-freedom (2-DOF) control structure. The design consists of DSMC and a feed forward controller. The control law is derived from the reaching law concept and its parameters are determined methodically based on the identified model. Experimental results reveal that the DMSC with 2-DOF control structure is highly robust and capable to deal with the uncertainties and disturbances occur during the position tracking control for different point of trajectories. It is also shows that the proposed controller can achieve better tracking performance as compared to conventional LQR and PID controller.

Electrohydraulic actuators are widely used in automation industries. This paper presents a robust position controller of single-rod electrohydraulic actuators. The design methodology is based on the twisting algorithm(TA) with an integral sliding surface. The TA is one of the most promising high-order sliding-mode control algorithms. However, implementations of the TA usually require a derivative of the system's states making the implementations difficult. In this paper, by using an integral sliding surface, the implementation does not require any derivative. The integration also enhances steady state performance when approximating the discontinuous control signal with a continuous one to reduce the chattering. In addition, by formulating the stability conditions in Linear Matrix Inequality(LMI) forms, the parameters of the controller are readily solved. Experiments on a real-life electrohydraulic actuator were conducted to illustrate the success and effectiveness of the proposed controller.

State-observer-based asymptotic tracking control for electro-hydraulic actuator systems with uncertainties and unmeasurable velocity

The vital purpose of a vehicle suspension system is to isolate the car body and hence passengers, from roadway unevenness disturbances. Implementation of passive suspension systems has continuously improved disconnection from disturbances through available deflection constraints to provide maximum isolation. In the majority of relevant reported research studies, a quarter car is modelled as moving vertically straight for both a viscous damper and a stiffness spring. The motivation for this study, reported here, is to extend the modelling to take account of the actual configuration of a test rig system. Accordingly, a new passive suspension system model is presented, which includes nonlinear lubricant friction forces that affect the linear support body bearings. The friction model established relies on dynamic system analysis and the fact of slipping body on lubricant bearings; this model captures most of the friction behaviours that have been observed experimentally. The suspension model is composed of a car body and wheel unit, and only vertical motion (bounce mode) is addressed. In addition, an active actuator is used to generate the system inputs as a road simulator. Therefore, a nonlinear hydraulic actuator, including the dynamic of servovalve and proportional–integral controller model, is established. This study is validated by experimental work, with simulations achieving C++compiler. As a result, a good agreement is obtained between the experimental and simulation results, that is, the passive suspension system with considered nonlinear friction and the nonlinear hydraulic actuator with servovalve equation models are entirely accurate and useful. The suggested proportional–integral controller successfully derives the hydraulic actuator to validate the control scheme. The ride comfort and handling response are close to that expected for the passive suspension system with road disturbances.

This paper proposes a discrete-time sliding mode control (DT-SMC) algorithm for uncertain linear systems with time-varying delay on the state. The parameter uncertainties and the external disturbances are assumed to be unknown but norm-bounded. The sliding mode existence depends on that of the stable linear sliding surface, which is ensured by a sufficient condition that depends on the delay bounds and is derived using LMI. A numerical example as well as an application to the Two-Area Four-Machine power system has been presented to illustrate and confirm the usefulness and the effectiveness of the proposed control strategy.

We propose a congestion control algorithm and design a state feedback controller for regulating the congestion of available bit rate (ABR) traffic in asynchronous transfer mode (ATM) networks. ABR service is specified as the rate-based feedback mechanism for congestion control and provides a control signal to throttled sources from a bottleneck node in order to adjust the throttled source rates based on available capacity. Our main purposes are as follows: (1) to design a state feedback controller; (2) to place the closed-loop poles in any desired regions based on a pole placement constraint; (3) to use the LMI (linear matrix inequalities) approach for finding the optimal state feedback gain K. The simulation results show that, under pole placement and LMI approaches, our state feedback congestion controller for ABR traffic in ATM networks can possibly guarantee the system stability, provide no buffer overflow, determine the optimal source traffic rates and place the closed-loop poles in any desired regions as well.

Electro Hydraulic Actuators (EHAs) keep their role as the leading solution for the control of current generation primary flight control systems: the main reason can be found in their high power to weight ratio, much better than other comparable technologies. To enhance efficiency and reliability of modern EHAs, it is possible to leverage the diagnostics and prognostics disciplines; these two tools allow reducing life cycle costs without losing reliability, and provide the bases for health management of integrated systems, in compliance with regulations. This paper is focused on the development of a fault detection algorithm able to identify the early signs of EHA faults, through the recognition of their precursors and related degradation patterns. Our methodology provides the advantage of anticipating incoming failures, triggering proper alerts for the maintenance team to schedule adequate corrective actions, such as the replacement of the degraded component. A new EHA model-based fault detection and identification (FDI) method is proposed; it is based on deterministic and heuristic solvers able to converge to the actual state of wear of the tested actuator. Three different progressive failure modes were chosen as test cases for the proposed FDI strategy: clogging of the first stage of the flapper-nozzle valve, spool-sleeve friction increase, and jack-cylinder friction increase. A dedicated simulation model was created for the purpose. The results highlighted that the method is adequate in robustness, since EHA malfunctions were identified with a low occurrence of false alarms or missed failures.

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