Unknown External Load Research Articles

Fixed-time adaptive neural control of electro-hydraulic system with model uncertainties: Theory and experiments

Nonlinearities, uncertainties and unknown external loads decline tracking dynamic performance and steady-state accuracy of electro-hydraulic systems. Most existing electro-hydraulic controllers have well guaranteed both the cylinder position and the load pressure asymptotic stable or uniformly ultimately bounded. However, the corresponding output response is relatively slow and achieves the desired performance in an infinite time, which cannot meet the requirements of fast convergence in some engineering applications. In this study, a fixed-time adaptive neural control (FTANC) is proposed for an electro-hydraulic system to improve the fast convergence performance and steady-state accuracy of the cylinder position in case of hydraulic model uncertainties A rigorous theoretical derivation proves that the electro-hydraulic system obtains practically fixed-time stability, such that all system state errors converge to the zero neighborhood in a fixed time without relation to the initial conditions of electro-hydraulic systems. Finally, both the simulation and experimental results verify the effectiveness of the proposed control method.

Distributed cooperative control of mechatronic system driving multiple electrohydraulic actuators with uncertain nonlinearity and communication delay

AbstractBeing different from many centralized mechatronic systems, the distributed transmission mechanism has the significant advantage such that realize cooperative task only based on small amount neighbour nodes with low computational complexity. In this study, a distributed cooperative control is proposed for multiple electrohydraulic system (MEHS) to guarantee the follower electrohydraulic node tracking the leader motion, based on the approach of directed spanning tree. Firstly, the MEHS model is constructed as three‐orders isomorphic nonlinear dynamics. Then, a disturbance observer is adopted to estimate uncertain nonlinearities caused by hydraulic parametric uncertainties and unknown external loads in the MEHS. To address unknown communication delays in the network topology of MEHS, a quasi‐synchronous controller is designed via Lyapunov–Krasovskii technique to guarantee that the synchronous errors asymptotically converge to a zero neighbourhood. Finally, the effectiveness of the proposed distributed synchronous control is verified by simulation results under uncertain nonlinearities and different communication delays.

Discontinuous Control Algorithm for Buck Converter under Time-Varying Load and Input Voltage

In this paper, the problem of the output voltage regulation of buck converters is considered. The novelty of the problem statement is that the external electric load and the input voltage of the converter are unknown bounded functions of a certain class. In particular, the external load equivalent scheme is similar to the successive connection of the inductive and resistive elements. In this case, the behavior of the load current is described by the differential equation with time-varying coefficients. In this equation, the equivalent inductance and resistance are described by unknown arbitrary bounded functions with several bounded derivatives. Under known bounds for these functions and their derivatives, the initial system can be transformed into the special form with smooth bounded perturbation. This disturbance is an unknown function, and its action channel differs from the input channel. Therefore, the influence on the unknown external load can not be compensated for directly by the control input. Due to this reason, the new control strategy is developed in the paper with the help of a “vortex” algorithm, which provides asymptotic convergence of the regulation error to zero in time. How to choose the converter parameters and the bounds for the input voltage to operate the closed-loop system properly are shown. The convergence proof is organized with the help of the Lyapunov function approach, and the transient rate is also estimated. The simulation results show the efficiency of the designed control law for the wide class of input voltage and electrical parameter functions. The proposed control scheme may be further used in electric drive systems.

Optimal Robust Control of Electro-Hydraulic System Based on Hamilton–Jacobi–Bellman Solution With Backstepping Iteration

There exist hydraulic parametric uncertainty and unknown external load in electro-hydraulic system (EHS), which inevitably decline the tracking performance and the stability of the closed-loop system. In this study, an optimal robust controller (ORC) is presented to solve this problem. Different from the traditional backstepping control, the ORC constructs the Hamilton–Jacobi–Bellman (HJB) equation based on the tracking error model of EHS to optimize the performance cost function as well as derive the optimal control variable. Furthermore, a critical neural network is adopted to estimate the optimal control solution of HJB equation such that guarantee the system state error of EHS uniformly ultimate boundary. Since the model uncertainty is considered in the HJB solution, the ORC has satisfactory robustness by using the network weight updation rather than direct parametric estimation or disturbance observer. The effectiveness of the proposed controller is verified by comparative simulation and experimental results.

Control Synchronization Design of a Multiple Electrohydraulic Actuator System with Linearization Dynamics and an External Disturbance Observer

The control synchronization of multiple electrohydraulic actuators (MEHAs) is initially discussed to ensure the consensus of every electrohydraulic actuator (EHA) with three-order isomorphic dynamics. First, the EHA model is linearized using the Lie derivative method to obtain the state-space model of MEHAs. Then, the disturbance observer is used to estimate and compensate for the unknown external load caused by the driving force of a motion plant. Via the Lyapunov technique, this protocol asymptotically achieves consensus to a zero neighborhood with the ultimate boundaries of the MEHAs’ state errors. The effectiveness of the synchronous control protocol is verified by both simulation and experimental benches with two-node EHAs.

Damage identification of long-span bridges based on the correlation of probability distribution of monitored quasi-static responses

Structural health diagnosis is one of the most critical issues in structural health monitoring (SHM). Vibration-based methods have been extensively investigated in the last few decades in the SHM community, but they encounter the challenges of local damage insensitivity and environmental sensitivity. However, the study of structural health diagnosis based on structural quasi-static response data, which has well-defined spatial coordinates and is sensitive to the local condition of the structure, is insufficient. It is difficult to extract structural models or parameters that directly indicate structural damage owing to the coupling effect of the damage and unknown external loads in the quasi-static response data. This study proposes a method based on the correlation of the probability distribution of the quasi-static response data for damage identification, and it is proved that the variation in the structural condition can be inferred from the variation in the correlation of the probability distribution of multiple quasi-static response data. The earth mover’s distance (EMD) is introduced as a quantitative indicator of the variation in the probability distribution function. The difference in the EMD (DEMD) between two monitored quasi-static responses was adopted as the damage indicator. The monitored strain on the steel box girder of a multi-tower cable-stayed bridge and the monitored cable tension of the cable-stayed bridge were employed to validate the proposed method. The results show that the proposed method successfully identifies the damage to the steel box girders and stay cables.

Extended sliding mode observer‐based high‐accuracy motion control for uncertain electro‐hydraulic systems

AbstractIn this paper, a novel robust backstepping control strategy is introduced to achieve high‐accuracy tracking performance for electro‐hydraulic servo systems (EHSSs) without velocity information in the presence of uncertainties and disturbances. Firstly, system dynamics of the studied EHSS considering parameter deviations, modeling errors, and unknown external loads which are grouped into lumped mismatched and matched disturbances in the mechanical system and pressure dynamics, respectively, are developed. On the basis of the sliding mode theory, two extended sliding mode observers (ESMOs) are originally established to simultaneously estimate the immeasurable angular velocity of the actuator, and lumped mismatched and matched uncertainties. As a consequence, an observer‐based controller is designed using the conventional backstepping technique to ensure a highly accurate tracking position control. In addition, the stability of the observer and overall closed‐loop control system is conclusively proven through the Lyapunov theory. Finally, several numerical simulations for an EHSS with a hydraulic rotary actuator are conducted to demonstrate the advantage of the recommended method compared to the existing well‐known extended state observer‐based control approaches.

Synchronous control for multiple electrohydraulic actuators with feedback linearization

Based on some research of electrichydraulic servo system (EHSS), the synchronous control problem of multiple electrohydraulic actuators (MEHAs) is investigated to guarantee the MEHAs’ system stability and leader-following synchronization with third-order nonlinear dynamics and unknown external load. Firstly, the EHA model is linearized by Lie derivatives technique to obtain the third-order linear isomorphic model of MEHAs with unknown external load. Then the disturbance observer is adopted to estimate unknown external load caused by the driven force of mechanical plant. Meanwhile, the state-feedback matrix is firstly designed by pole placement technique to guarantee the feedback linearization model Hurwitz. Furthermore, the synchronous controller is designed by Lyapunov technique and LMI to guarantee that n EHAs follower states synchronize the leader state with arbitrarily small zeros neighborhood under directed spanning tree. The effectiveness of the synchronous controller is verified by both comparative simulation and experimental bench.

Synchronous control of multiple electrohydraulic actuators under distributed switching topologies with lumped uncertainty

A leader-following synchronous control is proposed in multiple electrohydraulic actuators (MEHAs) under distributed switching topologies to guarantee the follower electrohydraulic actuators (EHAs) tracking the leader motion. Each EHA has a 3-orders nonlinear dynamics with lumped uncertainties involving uncertain hydraulic parameters and unknown external load. Then a quasi-synchronization controller together with a high-gain disturbance observer is designed by Lyapunov techniques to guarantee the synchronous errors asymptotically convergence to a zero neighborhood. Finally, the effectiveness of the proposed quasi-synchronous controller is verified by both simulation and experimental bench such that the finite EHA nodes achieve leader-following synchronous motion under distributed switching topologies.

Leader-Following Synchronization Control of Multiple Electrohydraulic Actuators Under Switching Network Topologies

Abstract A leader-following quasi-synchronization control is proposed in multiple electrohydraulic actuators (MEHAs) under different switching network topologies to guarantee the follower electrohydraulic actuators (EHAs) track the leader motion. Firstly, each EHA has a three order nonlinear dynamics with an unknown external load. Then by using Lie derivative technique, the MEHAs nonlinear models with n + 1 nodes are feedback linearized for convenient control design. Furthermore, the leader node is constructed as a virtual simulation model to be stabilized by PI controller. Meanwhile, a quasi-synchronized controller together with a disturbance observer is designed by linear matrix inequality (LMI) and Lyapunov techniques to guarantee that the synchronization errors between the n follower nodes and the leader node 0 are uniformly ultimate boundaries. Finally, the effectiveness of the leader-following quasi-synchronized controller is verified by a MEHAs experimental bench with three EHAs under switching network topologies.

Optimization and H∞ Performance Analysis for Load Frequency Control of Power Systems With Time-Varying Delays

With the development and expansion of the power grid, the load frequency control (LFC) scheme receives sensor signals and outputs control signals through an open communication network with a mass of data and extensive information exchange, which may introduce constant, and time-varying delays. This paper considers the optimization andH∞performance problem for LFC of power systems with time-varying delays. Some improved criteria for guaranteeing the stability andH∞performance of the closed-loop system with unknown external load disturbances via the Lyapunov stability theory application. An unique delay-dependent proportional-integral (PI) controller and an optimized PI controller are designed for a specifiedH∞performance index and set, respectively. The criteria proposed in this paper are based on linear matrix inequalities (LMIs), which can be easily solved by the MATLAB LMI-Toolbox. Finally, in case studies, the effectiveness of our method is demonstrated.

Augmented Tikhonov Regularization Method for Dynamic Load Identification

We introduce the augmented Tikhonov regularization method motivated by Bayesian principle to improve the load identification accuracy in seriously ill-posed problems. Firstly, the Green kernel function of a structural dynamic response is established; then, the unknown external loads are identified. In order to reduce the identification error, the augmented Tikhonov regularization method is combined with the Green kernel function. It should be also noted that we propose a novel algorithm to determine the initial values of the regularization parameters. The initial value is selected by finding a local minimum value of the slope of the residual norm. To verify the effectiveness and the accuracy of the proposed method, three experiments are performed, and then the proposed algorithm is used to reproduce the experimental results numerically. Numerical comparisons with the standard Tikhonov regularization method show the advantages of the proposed method. Furthermore, the presented results show clear advantages when dealing with ill-posedness of the problem.

Finite Time Fractional-order Adaptive Backstepping Fault Tolerant Control of Robotic Manipulator

In this paper, fractional calculus theory is employed to inspect a finite time fault tolerant controller for robotic manipulators in the presence of uncertainties, unknown external load disturbances, and actuator faults, using fractional-order adaptive backstepping approach in order to achieve, fast response and high-precision tracking performance. Knowing the advantages of adaptive controllers an adaptive form of the above controller is then established to deal with the overall uncertainties in the system. The most important property of the proposed controller is that we do not need to have knowledge about the actuator fault, external disturbances and system uncertainties exist in system. In this study two important achievements are made. The first one is that the finite time convergence of closed-loop system is ensured irrespective of initial states values. The second one is that the effects of the actuator faults and other uncertainties are attenuated by the suggested controller. The performance of the suggested controller is then tested for a PUMA560 robot in which the first three joints are used. The simulation results validate the usefulness of the suggested finite-time fractional-order adaptive backstepping fault-tolerant (FOAB-FTC) controller in terms of accuracy of tracking, and convergent speed.

Neural adaptive control of single-rod electrohydraulic system with lumped uncertainty

In electro-hydraulic system (EHS), there exist typical lumped uncertainties due to the uncertain hydraulic parameters and unknown external load, which usually decline the output dynamic performance. To address this problem, this paper proposes a neural adaptive control for single-rod EHS to improve the dynamic tracking performance of the cylinder position under these lumped uncertainties. A Radial-Basis-Function (RBF) neural network is constructed to train the unknown model dynamics caused by lumped uncertainties and obtain the self-learning models. Moreover, an adaptive estimation law is used to self-tune the trained-node weights and the self-learning models are online optimized to enhance the robustness of the neural adaptive controller. The effectiveness of the proposed controller has been verified by comparative simulation and experimental results with the other typical control methods.

A Control-Oriented Engine Torque Online Estimation Approach for Gasoline Engines Based on In-Cycle Crankshaft Speed Dynamics

Engine brake torque is a key feedback variable for the optimal torque split control of an engine–motor hybrid powertrain system. Due to the limitations in available sensors, however, engine torque is difficult to measure directly. For torque estimation, the unknown external load torque and the overlap of the expansion stroke between cylinders introduce a great disturbance to engine speed dynamics. This makes the conventional cycle average engine speed-based estimation approach unusable. In this article, an in-cycle crankshaft speed-based indicated torque estimation approach is proposed for a four-cylinder engine. First, a unique crankshaft angle window is selected for load torque estimation without the influence of combustion torque. Then, an in-cycle angle-domain crankshaft speed dynamic model is developed for engine indicated torque estimation. To account for the effects of model inaccuracy and unknown external disturbances, a “total disturbance” term is introduced. The total disturbance is then estimated by an adaptive observer using the engine’s historical operating data. Finally, a real-time correction method for the friction torque is proposed in the fuel cut-off scenario. Combining the aforementioned torque estimators, the brake torque can be obtained. The proposed algorithm is implemented in an in-house developed multi-core engine control unit (ECU). Experimental validation results on an engine test bench show that the algorithm’s execution time is about 3.2 ms, and the estimation error of the brake torque is within 5%. Therefore, the proposed method is a promising way to accurately estimate engine torque in real-time.

Finite-Time Convergent Control of Electrohydraulic Velocity Servo System Under Uncertain Parameter and External Load

The disturbances suppression is one common control problem in electrohydraulic systems (EHSs) since both unknown external load and hydraulic parametric uncertainty often obviously degrade the tracking performance and bias the load pressure of EHS. In this paper, a finite-time convergent controller (FTCC) is tried to use in EHS to address this problem. Different from the asymptotic convergent controller, this FTCC not only improve the dynamic and steady tracking performance of the velocity servo system but also guarantee the system state error convergent to zero in a finite time. According to the finite-time stable principle, the FTCC is derived by backstepping and fractional-type Lyapunov techniques. The effectiveness of the proposed controller is verified by comparative simulation and experimental results with the other traditional and advanced controllers.

Effect of Bench Press Load Knowledge on One Repetition Maximum Strength.

Snarr, RL, Adams, K, and Cook, J. Effect of bench press load knowledge on one repetition maximum strength. J Strength Cond Res 35(8): 2121-2126, 2021-Knowledge of a given load and visual feedback are crucial while performing a given task. Although previous literature has examined the consequences of lifting a submaximal weight, the removal of load knowledge has yet to be examined under maximal effort. Therefore, the purpose of this investigation was to examine the differences in 1 repetition maximum (1RM) bench press values between a known and unknown external load. Twenty resistance-trained subjects (10 male subjects and 10 female subjects) completed 2 trials of a 1RM bench press protocol separated by 48-72 hours. The two 1RM trials consisted of (a) a traditional 1RM lift in which subjects could see the external load and (b) a 1RM lift in which the external load was blocked from view of the subject. Trials were randomized for all subjects. Results indicated that no differences were observed when the load was known vs. unknown within all subjects (p = 0.094; Cohen's d = 0.03; intraclass correlation coefficient = 0.99). In addition, 40% decreased and 15% increased their 1RM, despite the unknown condition. A statistical difference was found between the initial 1RM estimation vs. measured 1RM during the known load trial (p = 0.034, Cohen's d = 0.07). Practitioners should note that load knowledge before a maximal lift does not appear to present any significant detrimental effects on performance. Therefore, training during a "blinded" condition may present a unique modality and additional balance component that would not be presented during a traditional maximal lift. Further examination of attentional focus and muscle activation differences are warranted.

Study on solving the ill-posed problem of force load reconstruction

Force load reconstruction methodology is used to estimate the unknown time-dependent external load forces in a damped system based on the structural response. However, the measurement errors of responses and estimation error of the system can affect the reliability of the results in several such inverse problems. An implicit Landweber method was proposed for single-source and multi-source force load reconstructions, and the concept of response sensitivity was used to reconstruct the dynamic force load. Numerical simulations and transonic wind tunnel tests of a spacecraft model demonstrate the effectiveness and robustness of the proposed method.

Estimating Lumbar Load During Motion with an Unknown External Load Based on Back Muscle Activity Measured with a Muscle Stiffness Sensor

A forward bending motion is essential in everyday tasks, such as carrying objects, shoveling snow, and performing farm work. However, many people suffer from lumbar pain resulting from forward bending motion, which causes a lumbar disc load owing to the changing of the lumbar shape. We have developed a wearable lumbar load estimation system, which measures the skin shape on the back using a curvature sensor. Because the lumbar load varies with the external load, the lumbar load should be estimated based on the external load. Therefore, we have developed a method for estimating an unknown external force using a muscle stiffness sensor. Muscle strength can be estimated by measuring the muscle hardness from the surface, and the relationship between the external force and the muscle force can be modeled. Using this method, we estimate the dependence of the lumbar load on external forces in real time. In addition, we simplify the calculation by converting the external load into a load resulting from a person’s own weight. We incorporate the proposed method into our wearable sensor system, estimate the lumbar load, and compare this with the results of a musculoskeletal dynamics simulation.

Antiwindup Control of an Electrohydraulic System With Load Disturbance and Modeling Uncertainty

In this study, a linear antiwindup controller of an electrohydraulic system (EHS) is proposed to drive the joint motion of a two-degree-of-freedom robotic arm. Since the unknown external load disturbance is caused by the driven force/torque of the robotic arm and some hydraulic parametric uncertainties existing in an EHS model, perhaps the control saturation emerges in the controller, which will degrade the dynamic performance and the stable margin of the EHS. Thus, a model recovery antiwindup compensator embedded in an unconstrained controller is designed to suppress the control saturation of a servo valve. The antiwindup effectiveness of the proposed controller has been demonstrated by a comparative experiment study with both linear and nonlinear controllers, which indicates the proposed controller can achieve better dynamic performance under largely unknown load disturbance and model uncertainty.