Dual Closed-loop Control Research Articles

Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force

The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

The Control Strategies for Charging and Discharging of Electric Vehicles in the Vehicle–Grid Interaction Modes

In response to the challenges posed by large-scale, uncoordinated electric vehicle charging on the power grid, Vehicle-to-Grid (V2G) technology has been developed. This technology seeks to synchronize electric vehicles with the power grid, improving the stability of their connections and fostering positive energy exchanges between them. The key component for implementing V2G technology is the bidirectional AC/DC converter. This study concentrates on the non-isolated bidirectional AC/DC converter, providing a detailed analysis of its two-stage operation and creating a mathematical model. A dual closed-loop control structure for voltage and current is designed based on nonlinear control theory, along with a constant current charge–discharge control strategy. Furthermore, midpoint potential balance is achieved through zero-sequence voltage injection control, and power signals for the switching devices are generated using Space Vector Pulse Width Modulation (SVPWM) technology. A simulation model of the V2G system is then constructed in MATLAB/Simulink for analysis and validation. The findings demonstrate that the control strategy proposed in this paper improves the system’s robustness, dynamic performance, and resistance to interference, thus reducing the effects of large-scale, uncoordinated electric vehicle charging on the power grid.

Adaptive dual closed-loop trajectory tracking control for a wheeled mobile robot on rough ground

Adaptive dual closed-loop trajectory tracking control for a wheeled mobile robot on rough ground

Research on constant tension yarn transfer control technology based on AGA-PID and FOC algorithm

To solve the problems of poor real-time tension tracking, large overshoot, long adjustment time, and large tension fluctuation error that exist in the current control system for yarn feeding in the circular weft knitting machine, this paper presents an optimized and improved adaptive genetic algorithm (AGA) for adjusting the PID (Proportional Integral Derivative) parameters of the tension control part of the yarn-conveying system (AGA-PID). The algorithm is combined with the field-oriented control technology of the permanent magnet synchronous motor to design a closed-loop control strategy for the yarn-conveying system of a circular weft knitting machine. The MATLAB-Simulink simulation model was used to analyze the external tension loop-based AGA-PID controller and permanent magnet synchronous motor dual closed-loop control strategy of the yarn transport control system. The experimental verification was conducted by constructing an experimental platform that simulates the real process of yarn transportation. The outcomes of system simulations and experiments have consistently demonstrated that the AGA-PID control algorithm outperforms the GA-PID and PID control algorithms in terms of overshooting, response speed, stability, and anti-jamming ability. The yarn transport control system, which is designed to operate based on an AGA-PID control algorithm, is capable of reducing the fluctuations in tension that occur during the transportation of yarn and exhibits enhanced control accuracy, effectively stabilizing yarn tension control during the conveying process. The application of this algorithm can enhance the overall elasticity uniformity and surface flatness of knitted fabrics, thereby facilitating the realization of adjustable and controllable local elasticity in fabrics.

Trajectory tracking of Jiaolong submersible with velocity constraints via dual closed-loop control

Trajectory tracking of Jiaolong submersible with velocity constraints via dual closed-loop control

Motion/force coordinated trajectory tracking control of nonholonomic wheeled mobile robot via LMPC-AISMC strategy

Nonholonomic constrained wheeled mobile robot (WMR) trajectory tracking requires the enhancement of the ground adaptation capability of the WMR while ensuring its attitude tracking accuracy, a novel dual closed-loop control structure is developed to implement this motion/force coordinated control objective in this paper. Firstly, the outer-loop motion controller is presented using Laguerre functions modified model predictive control (LMPC). Optimised solution condition is introduced to reduce the number of LMPC solutions. Secondly, an inner-loop force controller based on adaptive integral sliding mode control (AISMC) is constructed to ensure the desired velocity tracking and output driving torques by combining second-order nonlinear extended state observer (ESO) with the estimation of dynamic uncertainties and external disturbances during WMR travelling process. Then, Lyapunov stability theory is utilised to guarantee the consistent final boundedness of the designed controller. Finally, the system is numerically simulated and practically verified. The results show that the double-closed-loop control strategy devised in this paper has better control performance in terms of complex trajectory tracking accuracy, system resistance to strong interference and computational timeliness, and is able to realise effective coordinated control of WMR motion/force.

Attitude tracking control of a foldable wave energy powered AUV based on linear time-varying MPC under position constraints

In this paper, we investigate the tracking control of attitude and specific spatial position for a foldable wave energy powered autonomous underwater vehicle (FWEPAUV) under space constraints. In order to reduce energy consumption and maximizing the efficiency of the charging, a cascaded dual closed-loop control strategy is proposed. Firstly, we utilize model predictive control (MPC) with multi-variable constraint capabilities to design the kinematics controller. The output constraints are set as space constraints for MPC, and an objective function is used to strike a balance between control accuracy and energy consumption. The improved chaotic firefly algorithm (ICFA) is chosen due to its rapid convergence and strong robustness. It is employed in the rolling optimization process of MPC to secure a viable solution. Secondly, the kinematics controller is combined with the dynamics controller based on adaptive sliding mode control (ASMC) to achieve robust tracking control. In order to eliminate the interference from time-varying ocean currents and complex external forces meanwhile utilizing these interferes to reduce energy consumption, An ocean current observer based on ICFA-PI control and a prescribed time disturbance observer (PTDO) are devised to estimate them. Finally, an event-triggered (ET) mechanism is applied to integrate with the trajectory tracking controller to decrease the computational load. The stability of the ICFA-MPC controller and the ASMC controller is proven using the Lyapunov stability theory. Simulation results demonstrate that in complex external interference environments, the controller can achieve stable tracking control of the attitude and a specific spatial position, thereby meeting predefined goals such as space constraints, energy savings, and maximizing the efficiency of the charging.

Double closed loop PI control with full compensation arc elimination based on zero sequence voltage of neutral point

Aiming at the problem of zero sequence voltage generated by unbalance parameters of line to ground, which affects arc suppression effect of grounding fault of controllable voltage source. By analyzing the influence of ground unbalance parameters on the arc suppression effect of controllable voltage source under different grounding modes, the mechanism of full compensation arc suppression based on zero sequence voltage of neutral point is revealed, and on this basis, a fully compensated arc suppression model of controllable voltage source controlled by double closed loop PI is established, and the deviation control is carried out by using the neutral voltage of distribution network and the voltage of fault phase supply. The residual voltage ring adopts the ground fault phase residual voltage for closed loop control. The simulation results show that the dual-closed-loop PI control algorithm can continuously stabilize the output waveform of the controllable voltage source. When the transition resistance is 0.1 ~ 10 kΩ, the residual voltage stabilization time of the independent controllable voltage source grounding method is 43 ms ~ 2.4 s, and the parallel arc suppression coil grounding method is 43 ms ~ 4.7 s. The proposed dual closed-loop PI control method for neutral point voltage deviation and fault residual voltage can stabilize the residual voltage of the grounded fault phase to below 10 V, forcing reliable arc extinction at the grounded fault point, exhibiting good stability. Low-voltage simulation tests have also proved the feasibility of the algorithm.

Design and Implementation of a Two-Wheeled Self-Balancing Car Using a Fuzzy Kalman Filter

To improve the upright balancing performance of the two-wheeled self-balancing car, this paper proposes an attitude estimation algorithm based on fuzzy Kalman filtering. Fuzzy logic is used to correct the inclination angle and angular velocity of the two-wheeled self-balancing car, thereby optimizing the state of the Kalman filter and ultimately improving the balancing performance of the car. This paper combines dual closed-loop PID control with the complementary filtering algorithm, Kalman filtering algorithm, and fuzzy Kalman filtering algorithm to conduct experiments on a physical two-wheeled self-balancing car. The experimental results validate the superiority of the fuzzy Kalman filtering algorithm proposed in this paper for improving the upright balancing performance of the two-wheeled self-balancing car.

Optimizing Controls to Track Moving Targets in an Intelligent Electro-Optical Detection System

Electro-optical detection systems face numerous challenges due to the complexity and difficulty of targeting controls for “low, slow and tiny” moving targets. In this paper, we present an optimal model of an advanced n-step adaptive Kalman filter and gyroscope short-term integration weighting fusion (nKF-Gyro) method with targeting control. A method is put forward to improve the model by adding a spherical coordinate system to design an adaptive Kalman filter to estimate target movements. The targeting error formation is analyzed in detail to reveal the relationship between tracking controller feedback and line-of-sight position correction. Based on the establishment of a targeting control coordinate system for tracking moving targets, a dual closed-loop composite optimization control model is proposed. The outer loop is used for estimating the motion parameters and predicting the future encounter point, while the inner loop is used for compensating the targeting error of various elements in the firing trajectory. Finally, the modeling method is substituted into the disturbance simulation verification, which can monitor and compensate for the targeting error of moving targets in real time. The results show that in the optimal model incorporating the nKF-Gyro method with targeting control, the error suppression was increased by up to 36.8% compared to that of traditional KF method and was 25% better than that of the traditional nKF method.

Finite-Time Robust Flight Control of Logistic Unmanned Aerial Vehicles Using a Time-Delay Estimation Technique

This paper proposes a cascaded dual closed-loop control strategy that incorporates time delay estimation and sliding mode control (SMC) to address the issue of uncertain disturbances in logistic unmanned aerial vehicles (UAVs) caused by ground effects, crosswind disturbances, and payloads. The control strategy comprises a position loop and an attitude loop. The position loop, which functions as the outer loop, employs a proportional–integral–derivative (PID) sliding mode surface to eliminate steady-state error through an integral component. Conversely, the attitude loop, serving as the inner loop, utilizes a fast nonsingular terminal sliding mode approach to achieve finite-time convergence and ensure a quick system response. The time-delay estimation technique is employed for the online estimation and real-time compensation of unknown disturbances, while SMC is used to enhance the robustness of the control system. The combination of time-delay estimation and SMC offers complementary advantages. The stability of the system is proven using Lyapunov theory. Hardware-in-the-loop simulation and flight tests demonstrate that the control law can achieve a smooth and continuous output. The proposed control strategy can be effectively applied in complex scenarios, such as hovering, crash recovery, and high maneuverability flying, with significant practicality in engineering applications.

Power Source Converter Based on a Variable-Domain Fuzzy PI Control

The inadequacy of conventional control strategies for multi-phase interleaved parallel circuits in terms of adaptive adjustment makes it difficult to meet the power source design requirements for transient electromagnetic detection systems. This paper introduces a novel approach, the variable-domain fuzzy proportional–integral (PI) adaptive control strategy. This strategy dynamically adjusts the fuzzy domain in real time based on the input error magnitude, ensuring improved control effectiveness. By leveraging the benefits of both the functional scaling factor and the fuzzy reasoning scaling factor, we design scaling factors for the input and output domains to enhance control precision. The focus of this study is on a four-phase interleaved parallel converter, emphasizing the design of the variable-domain fuzzy PI control strategy for the voltage outer loop within the traditional dual closed-loop structure. An experimental prototype with a 220 Vac input, 380 V output, and a power rating of 1000 W is constructed. A comparative analysis between fuzzy control and variable-domain fuzzy PI control is conducted in the voltage outer loop of the dual closed-loop control. Results reveal that dual closed-loop control with variable-domain fuzzy PI control for the voltage outer loop significantly enhances system stability. The startup time to reach the steady state is reduced to 0.632 s, with an overshoot of 28.8 V. Transitioning from 25% load to full load takes only 0.096 s, resulting in a minimal drop of 21.4 V and an overshoot of 13.4 V. Similarly, switching from full load to 25% load in 0.167 s exhibits an overshoot of only 19.6 V. The adaptive regulation capability of the converter is markedly improved, showcasing smaller overshoots and higher-level controlling effectiveness.

Dual closed-loop control method for resonant integrated optic gyroscopes with combination differential modulation

In order to optimize the detection accuracy and output stability of Resonant Integrated Optic Gyroscopes (RIOG), a dual closed-loop control method for combined differential modulation (DCM Control) has been proposed. Two optical signals are differentially modulated in sync, and their differential-mode output results are compensated in real-time. Considering the distinct characteristics of the two frequency servo loops, they are respectively utilized to tune the laser frequency to track the resonant frequency's wide fluctuations and continuously changing resonant frequency due to random rotation. Through this novel structure, we have enhanced reciprocity while reducing optical components, suppressing RIM noise and laser frequency noise in the gyroscope system, and effectively reducing control errors. We analyze the principles affecting angular velocity detection accuracy and the system's output model. Experimental results indicate that this method can effectively achieve high reciprocity and high-precision frequency control, offering a larger dynamic detection range and better linearity. The long-term bias instability (BI) based on Allan deviation is measured at 0.95°/h, and the angle random walk (ARW) is 0.119°/√h, providing a simple and efficient approach for RIOG closed-loop signal processing.

ESO-based robust adaptive control for dual closed-loop fuel control system in aeroengine

To improve the flowrate control accuracy of fuel control system at high supply pressure and large flowrate working condition, this paper proposes a novel dual closed-loop control for fuel metering unit (FMU) to address issues related to unknown velocity, matched/unmatched disturbances, and parameter uncertainties. Firstly, for a comprehensive assessment in flowrate feedback method, a global sensitive analysis is utilized to research the effect ratio of factors affecting the discharge flowrate. Then, a novel dual closed-loop control is proposed, in which the outer loop is flowrate loop, and a novel extended-state-observer (ESO)-based robust adaptive control without velocity sensor is used as the internal displacement loop control. Specifically, ESO can effectively estimate the unknown velocity and unmatched disturbance, and the parameter estimations can be updated by the adaptive law determined only by spool displacement and reference signal. The novel robust control can address matched/unmatched disturbances and model uncertainties effectively. Through Lyapunov method, it follows that the novel ESO-based robust adaptive control can achieve asymptotic tracking performance when occurring time-invariant disturbances and bounded tracking performance when occurring time-varying disturbances. Comparative experiments verify the superiority of the proposed control, which provides a new method and glimpse for the advanced control strategy of aeroengine.

Robust adaptive three-dimensional trajectory tracking control for unmanned underwater vehicles with disturbances and uncertain dynamics

Aiming at the three-dimensional (3-D) trajectory tracking problem of UUV with uncertain dynamics in an unknown and bounded external disturbance environment, a new dual closed-loop controller based on nonlinear model predictive control (NMPC) and adaptive integral sliding mode control (AISMC) is designed. The outer-loop NMPC controller designed based on position and attitude tracking errors generates a virtual desired velocity command and transmits it to the inner-loop controller. The inner-loop adaptive integral sliding mode controller based on speed tracking error design combines adaptive radial basis (RBF) neural network controller and disturbance observer to approximate the uncertainty of system model parameters and environmental disturbances, and then generates the actual control input to the UUV system. Different from other cascaded control systems, the designed controller combines the advantages of display processing constraints of MPC and robustness of SMC, which can improve the robustness of the control system, it effectively considers the actual constraints of the system input and state, and avoids the saturation of the actuator. In addition, the stability of the closed-loop system with and without disturbances is proved respectively based on the Lyapunov method. Finally, simulation results verify the effectiveness of the proposed controller: Under the perturbation of 10% model parameters, the UUV can accurately track the desired trajectory.

LabVIEW-based servo valve dynamic and static test system

As a key component of the electro-hydraulic servo control system, the electro-hydraulic servo valve’s performance directly affects the stability of the system’s operation. Therefore, according to the company’s requirements, a servo valve testing system was designed based on LabVIEW. Firstly, the hydraulic system was designed according to the dynamic and static testing requirements of the servo valve. Then, the electrical control system and software system were designed based on PLC and LabVIEW. Finally, dynamic and static characteristic tests of the servo valve were conducted on the designed test bench. A flow-pressure dual closed-loop steady-state control method for testing the no-load flow characteristics was proposed, effectively improving the testing accuracy and meeting the company’s requirements.

Stochastic performance evaluation method of wind power DC bus voltage control system

The stochastic fluctuation of DC bus voltage of wind power grid-connected system is related to the safe and stable of power system, and the stochastic performance evaluation is an important means for early warning system. In order to evaluate stochastic performance of control system, this paper proposes a stochastic performance evaluation method based on minimum variance theory. A dual closed loop control model of wind power grid-connected converter DC bus voltage is established, the stochastic performance evaluation indicator is derived by time-series analysis and Diophantine decomposition, and the method to solve the indicator through operation data is given. The effectiveness of the proposed method is verified by FAST-MATLAB co-simulation platform. And the results show that the stochastic performance of the system can be improved by optimizing the parameters of the controller and the DC bus voltage.

Admittance-Based Stability Analysis of Resistance-Emulating Controlled Grid-Connected Voltage Source Rectifiers

Due to low cost and high reliability, resistance-emulating control (REC) is an emerging approach for grid-connected voltage source rectifiers (VSRs). However, small-signal stability issues of the grid-connected VSR with REC are currently rarely studied. In this paper, the small-signal dq-admittance model of the grid-connected VSR with REC is first built and the small-signal stability superiority of the VSR with REC in weak-grid connection is revealed. First, a dq-admittance model of the grid-connected VSR with REC is established. The admittance characteristics of the grid-connected VSR with REC and the grid-connected VSR with traditional dual closed-loop control (DCC) are analyzed and compared. Then, the influence of short circuit ratio (SCR), voltage-loop bandwidth and the output power on the stability of the VSR with REC and DCC is analyzed based on the generalized Nyquist criterion. The stability comparison results indicate that the VSR with REC has better adaptability to the weak grid and can achieve a higher bandwidth at the voltage loop. Besides, it is found that the DCC controlled VSR is more suitable for light-load operation than the REC controlled VSR. Finally, the correctness of the analysis is verified by experiments.

Distributed Dual Closed-Loop Model Predictive Formation Control for Collision-Free Multi-AUV System Subject to Compound Disturbances

This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme.

Research on performance improvement of acoustic resonance-based wind sensors by using dual closed-loop control

To achieve high-precision and high-stability detection of wind speed and direction in complex environments, this research proposes a dual closed-loop control scanning technique for the wind sensor system based on the acoustic resonance principle. This technique has been found to significantly enhance the system’s performance indicators. The acoustic resonance method used on wind sensors allows for the simultaneous modulation of frequency and intensity of signals generated by the transducer, resulting in linear scanning of the ultrasonic transducer. Frequency modulation resolves the issue of a resonance frequency shift caused by environmental factors like pressure and temperature, while intensity modulation addresses transducer performance degradation over time and can significantly improve the signal-to-noise ratio. However, when confronted with issues such as wind shear, the rapid change in the ambient pressure of the wind sensor may lead to the failure of the frequency modulation, followed by the change in the rate of wind shear, resulting in significant errors in wind speed detection. Therefore, the dual closed-loop control method is used to combine the frequency scanning modes—the slow and long scanning and the short and fast scanning. The slow and long scanning is used to solve the resonance frequency shift caused by various slow external changes and achieve frequency following, while the short and fast scanning resolves the resonance frequency shift resulting from rapid changes in wind shear and achieves rapid frequency following. Experimental results demonstrate that the scanning method employing dual closed-loop control can accurately measure wind speed and direction. The wind speed measurement range is 0–50 m/s, with a measurement accuracy of ±0.3 m/s (≤15 m/s)/±4% (>15 m/s), while the wind direction measurement range is 0°–360°, with a measurement accuracy of ±3°. After improvements, the system has high accuracy and stability and strong anti-interference ability and is less affected by environmental changes in complex environments.