Nonlinear Modeling and Identification of the Electro-hydraulic Control System of an Excavator Arm Using BONL Model

Electro-hydraulic control systems are nonlinear in nature and their mathematic models have unknown parameters.Existing research of modeling and identification of the electro-hydraulic control system is mainly based on theoretical state space model,and the parameters identification is hard due to its demand on internal states measurement.Moreover,there are also some hard-to-model nonlinearities in theoretical model,which needs to be overcome.Modeling and identification of the electro-hydraulic control system of an excavator arm based on block-oriented nonlinear(BONL)models is investigated.The nonlinear state space model of the system is built first,and field tests are carried out to reveal the nonlinear characteristics of the system.Based on the physic insight into the system,three BONL models are adopted to describe the highly nonlinear system.The Hammerstein model is composed of a two-segment polynomial nonlinearity followed by a linear dynamic subsystem.The Hammerstein-Wiener(H-W)model is represented by the Hammerstein model in cascade with another single polynomial nonlinearity.A novel Pseudo-Hammerstein-Wiener(P-H-W)model is developed by replacing the single polynomial of the H-W model by a non-smooth backlash function.The key term separation principle is applied to simplify the BONL models into linear-in-parameters structures.Then,a modified recursive least square algorithm(MRLSA)with iterative estimation of internal variables is developed to identify the all the parameters simultaneously.The identification results demonstrate that the BONL models with two-segment polynomial nonlinearities are able to capture the system behavior,and the P-H-W model has the best prediction accuracy.Comparison experiments show that the velocity prediction error of the P-H-W model is reduced by 14%,30%and 75%to the H-W model,Hammerstein model,and extended auto-regressive(ARX)model,respectively.This research is helpful in controller design,system monitoring and diagnosis.

Fuzzy Feedback Control for Electro-Hydraulic Actuators

Electro-hydraulic actuators(EHA)have recently played a significant role in modern industrial applications,especially in systems requiring extremely high precision.This can be explained by EHA’s ability to precisely control the position and force through advanced sensors and innovative control algorithms.One of the promising approaches to improve control accuracy for EHA systems is applying classical to modern control algorithms,in which the proportional–inte-gral–derivative(PID)algorithm,fuzzy logic controller,and a hybrid of these methods are popular options.In this paper,we developed a novel version of the fuzzy control algorithm and linear feedback control method,namely fuzzy lin-ear feedback control,to improve the control performance.To achieve the highest performance,wefirst designed a mathematical EHA model based on the Matlab/Simulink software packages thanks to the selected parameters,which are similar to a real EHA system.Then,we respectively applied PID,fuzzy PID(FPID),and fuzzy linear feedback control(FLFC)before comparing them to have a full view of the outstanding advantages of the proposed algorithm.The simulation results showed that the proposed FLFC algorithm is approximately 99%and 77%super-ior in performance to the PID and feedback control algorithms,respectively.

Present Status and Prospect of High-Frequency Electro-hydraulic Vibration Control Technology

Electro-hydraulic vibration equipment(EHVE)is widely used in vibration environment simulation tests,such as vehicles,weapons,ships,aerospace,nuclear industries and seismic waves replication,etc.,due to its large output power,displacement and thrust,as well as good workload adaptation and multi-controllable parameters.Based on the domestic and overseas development of high-frequency EHVE,dividing them into servo-valve controlled vibration equipment and rotary-valve controlled vibration equipment.The research status and progress of high-frequency electro-hydraulic vibration control technology(EHVCT)are discussed,from the perspective of vibration waveform control and vibration controller.The problems of current electro-hydraulic vibration system bandwidth and waveform distortion control,stability control,offset control and complex vibration waveform generation in high-frequency vibration conditions are pointed out.Combining the existing rotary-valve controlled high-frequency electro-hydraulic vibration method,a new twin-valve independently controlled high-frequency electro-hydraulic vibration method is proposed to break through the limitations of current electro-hydraulic vibration technology in terms of system frequency bandwidth and waveform distortion.The new method can realize independent adjustment and control of vibration waveform frequency,amplitude and offset under high-frequency vibration conditions,and provide a new idea for accurate simulation of high-frequency vibration waveform.

Barrier Lyapunov functions-based dynamic surface control with tracking error constraints for ammunition manipulator electro-hydraulic system

This paper focuses on the dynamic tracking control of ammunition manipulator system. A standard state space model for the ammunition manipulator electro-hydraulic system(AMEHS) with inherent nonlinearities and uncertainties considered was established. To simultaneously suppress the violation of tracking error constraints and the complexity of differential explosion, a barrier Lyapunov functionsbased dynamic surface control(BLF-DSC) method was proposed for the position tracking control of the ammunition manipulator. Theoretical analysis prove the stability of the closed-loop overall system and the tracking error converges to a prescribed neighborhood asymptotically. The effectiveness and dynamic tracking performance of the proposed control strategy is validated via simulation and experimental results.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Continuous rotary motor electro-hydraulic servo system based on the improved repetitive controller

In order to suppress the periodic interference of the continuous rotary electro-hydraulic servo motor,this paper makes the motor tracking the periodic signals with high accuracy,and improves the influence of friction interference to the performance of continuous rotary electro-hydraulic servo motor.The mathematic model of the electro-hydraulic position servo system of the continuous rotary motor was established,and the compound control method was adopted based on the repetitive control,feed forward and PID to suppress the friction interference.Through the simulation,the result confirms that the compound control method decreases the tracking error of the system,increases the robust performance of the system and improves the performance of the continuous rotary electro-hydraulic servo motor.

HYBRID FUZZY CONTROL FOR ELECTRO-HYDRAULIC ACTIVE DAMPING SUSPENSION

A new control scheme, the hybrid fuzzy control method, for active damping suspension system is presented. The scheme is the result of effective combination of the statistical optimal control method based on the statistical property of suspension system, with the bang-bang control method based on the real-time characteristics of suspension system. Computer simulations are performed to compare the effectiveness of hybrid fuzzy control scheme with that of optimal damping control, bang-bang control, and passive suspension. It takes the effects of time-variant factors into full account. The superiority of the proposed hybrid fuzzy control scheme for active damping suspension to the passive suspension is verified in the experiment study.

Control method on serial type pump-valve coordinated electro-hydraulic servo system

In order to compromise the conflicts between control accuracy and system efficiency of conventional electro-hydraulic servo systems,a novel pump-valve coordinated electro-hydraulic servo system was designed and a corresponding control strategy was proposed.The system was constituted of a pumpcontrolled part and a valve-controlled part,the pump controlled part is used to adjust the flow rate of oil source and the valve controlled part is used to complete the position tracking control of the hydraulic cylinder.Based on the system characteristics,a load flow grey prediction method was adopted in the pump controlled part to reduce the system overflow losses,and an adaptive robust control method was adopted in the valve controlled part to eliminate the effect of system nonlinearity and parametric uncertainties due to variable hydraulic parameters and system loads on the control precision.The experimental results validated that the adopted control strategy increased the system efficiency obviously with guaranteed high control accuracy.

Dynamic Simulation and Valve Structure Optimization of an Electro-Hydraulic Clutch Shift Control System in an Automatic Transmission

The electro-hydraulic clutch control system controls the transferred torque of gear-shifting clutches in clutch-to-clutch transmissions. A nonlinear dynamic model of an electro-hydraulic clutch shift control system is presented. The mechanical and fluid subsystems of all valves are investigated, including their interactions. Model validation of the electro-hydraulic valve system is performed by comparing the simulated and measured pressure curves. The dynamic characteristics of the electro-hydraulic clutch shift control system with different supply pressures and different fluid temperatures are simulated and evaluated. It is found that pipes which are often ignored between the electro-hydraulic valve system and the clutch piston,have strong influence on clutch piston chamber pressures. In order to satisfy the required time and reduce the fluctuation of the clutch piston chamber pressures,the orifices' diameters and valve structure are optimized.

Mitochondrial dysfunction and quality control lie at the heart of subarachnoid hemorrhage

The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Sliding Mode Control of Hydraulic Pressure in Electro-Hydraulic Brake System Based on the Linearization of Higher-Order Model

The possibility to enhance the stability and robustness of electrohydraulic brake(EHB)systems is considered a subject of great importance in the automotive field.In such a context,the present study focuses on an actuator with a four-way sliding valve and a hydraulic cylinder.A 4-order nonlinear mathematical model is introduced accordingly.Through the linearization of the feedback law of the high order EHB model,a sliding mode control method is proposed for the hydraulic pressure.The hydraulic pressure tracking controls are simulated and analyzed by MATLAB/Simulink soft considering separately different conditions,i.e.,a sine wave,a square wave and a square wave with superimposed sine disturbance.The results show that the proposed strategy can track the target within 0.25 s,and the mean observed error is less than 1.2 bar.Moreover,with such a strategy,faster response and less overshoot are possible,which should be regarded as significant advantages.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Quantization and Event-Triggered Policy Design for Encrypted Networked Control

This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.

Practical Prescribed Time Tracking Control With Bounded Time-Varying Gain Under Non-Vanishing Uncertainties

This paper investigates the prescribed-time control(PTC) problem for a class of strict-feedback systems subject to non-vanishing uncertainties. The coexistence of mismatched uncertainties and non-vanishing disturbances makes PTC synthesis nontrivial. In this work, a control method that does not involve infinite time-varying gain is proposed, leading to a practical and global prescribed time tracking control solution for the strict-feedback systems, in spite of both the mismatched and nonvanishing uncertainties. Different from methods based on control switching to avoid the issue of infinite control gain that involves control discontinuity at the switching point, in our method a softening unit is exclusively included to ensure the continuity of the control action. Furthermore, in contrast to most existing prescribed-time control works where the control scheme is only valid on a finite time interval, in this work, the proposed control scheme is valid on the entire time interval. In addition, the prior information on the upper or lower bound of gi is not in need,enlarging the applicability of the proposed method. Both the theoretical analysis and numerical simulation confirm the effectiveness of the proposed control algorithm.

Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

Quaternion-Based Adaptive Trajectory Tracking Control of a Rotor-Missile with Unknown Parameters Identification

This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.

Versatile and controlled quantum teleportation network

A quantum teleportation network involving multiple users is essential for future quantum internet.So far,controlled quantum teleportation has been demonstrated in a three-user network.However,versatile and controlled quantum teleportation network involving more users is in demand,which satisfies different combinations of users for practical requirements.Here we propose a highly versatile and controlled teleportation network that can switch among various combinations of different users.We use a single continuous-variable six-partite Greenberger-Horne-Zeilinger(GHZ)state to realize such a task by choosing the different measurement and feedback operations.The controlled teleportation network,which includes one sub-network,two sub-networks and three sub-networks,can be realized for different application of user combinations.Furthermore,the coherent feedback control(CFC)can manipulate and improve the teleportation performance.Our approach is flexible and scalable,and would provide a versatile platform for demonstrations of complex quantum communication and quantum computing protocols.

Adaptive admittance tracking control for interactive robot with prescribed performance

An adaptive control approach is presented in this paper for tracking desired trajectories in interactive manipulators. The controller design incorporates prescribed performance functions (PPFs) to improve dynamic performance. Notably, the performance of the output error is confined in an envelope characterized by exponential convergence, leading to convergence to zero. This feature ensures a prompt response from admittance control and establishes a reliable safety framework for interactions. Simulation results provide practical insights,demonstrating the viability of the control scheme proposed in this paper.

Nonlinear robust adaptive control for bidirectional stabilization system of all-electric tank with unknown actuator backlash compensation and disturbance estimation

Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.