Feedback Compensation Research Articles

Ultraprecision multi-axis CARIC control strategy with application to a nano-accuracy air-bearing motion stage.

Multi-axis contouring control is crucial for ultraprecision manufacturing industries, contributing to meeting the ever-increasingly stringent performance requirements. In this article, a novel contouring adaptive real-time iterative compensation (CARIC) method is proposed to achieve extreme multi-axis contouring accuracy, remarkable trajectory generalization, disturbance rejection, and parametric adaptation simultaneously. Specifically, control actions generated by CARIC consist of robust feedback, adaptive feedforward, and online trajectory compensation components. Robust feedback and adaptive feedforward terms initially stabilize single-axis closed-loop control systems and adapt to parameter variations. An online contouring error prediction model subsequently captures upcoming contouring errors in advance, enabling the iterative calculation of optimal online trajectory compensation signals at each sampling instant during real-time motion. This mechanism proactively suppresses potential contouring errors before their occurrence. Comparative simulations and experiments demonstrate that the proposed CARIC method reaches the accuracy limit previously attainable only by iterative learning control (ILC) while enhancing trajectory generalization, disturbance rejection, and parametric adaptation. Notably, practical experiments on a nano-accuracy air-bearing motion stage showcase consistent 7-nm-level accuracy across various 100-mm stroke contouring tasks even under varying contours, payloads, and disturbances. Owing to these advantages, CARIC offers promising potential to enhance ultraprecision manufacturing performance through advanced motion control techniques.

Infinite-time optimal feedback control of a 3-phase asynchronous motor exploiting a nonlinear finite element model

This paper presents modelling of a squirrel-cage induction motor and an optimal control method based on suboptimal control for nonlinear systems to minimise consumed energy and power losses in an induction motor drive. A coupled motor model with optimal control as a closed-loop integrated system is proposed. For modelling of the squirrel-cage asynchronous machine, a field-circuit-mechanical finite-element (FE) model is employed, in which mechanical motion is realised by a moving-mesh method and fixed mesh approach. For the control problem purpose, a surrogate induction motor model, described in a stationary rotor reference d–q frame, is applied. The optimal control is realised by a nonlinear feedback compensator method based on the state-dependent Riccati equation (SDRE) with an infinite time horizon with the surrogate model state-dependent parametrisation (SDP). To perform the control strategy, a SDRE technique with Moore–Penrose pseudoinverse is adopted. To improve the accuracy of the optimisation procedure, a finite element model was used to calculate the motor performance.

Optimal Periodic Impulsive Control for Orbital Stabilization of Underactuated Systems

Abstract The orbital stabilization problem for underactuated systems with a single passive degree-of-freedom is revisited. The impulse controlled Poincaré map (ICPM) approach, in which stabilizing impulsive inputs are applied on a Poincaré section, has distinct advantages over existing methods but feedback compensation once every oscillation limits the rate of convergence to the desired orbit. To overcome these limitations, we propose stabilization through application of multiple impulsive inputs during each oscillation. An optimal control problem is formulated to minimize a quadratic cost functional and the optimal inputs are obtained by solving a discrete periodic Riccati equation. Simulation results for a Pendubot are presented, highlighting the advantages of the control design over the ICPM method in terms of convergence rate and robustness to parameter uncertainty.

Enhanced Operation Mode Design and Motion Control of a Dual-Redundancy Electro-Hydrostatic Actuator

In dual-redundancy electro-hydrostatic actuators (EHAs), the dual pumps are mainly designed for safety, where the cylinder is controlled mainly by one pump while the other one is standby for redundancy. However, such a strategy is basically like a single-pump-controlled system, and the flow from the pump may be inaccurate when the cylinder moves slowly, which will affect the motion control performance. A new dual-redundancy EHA is designed, and a series of corresponding operation modes are developed, enabling differential operation of the dual pumps. With the proposed operation modes, the inevitable flow inaccuracy problem of the single pump can be addressed through the coordination control of the dual pumps. In order to achieve better motion tracking performance, a model-based backstepping controller is synthesized, where the nonlinearities and uncertainties of the EHA are handled by model compensation and robust feedback design. Comparative simulations with existing control methods for EHAs are conducted and better motion tracking precision is achieved, especially during low-speed motion.

The Impact of Incentivization on Recruitment, Retention, Data Quality, and Participant Characteristics in Ecological Momentary Assessments

Ecological Momentary Assessment (EMA) study participation is usually incentivized using monetary (e.g., fixed or performance-contingent payment) or non-monetary (e.g., feedback) compensation. This study investigates the impact of this incentivization on recruitment, retention, data quality, and participant characteristics in a sample of 74 students. For this purpose, an EMA study (time-based sampling) was conducted in participants’ daily life using a 2 Payment (fixed/ performance-contingent) x 2 Feedback (yes/ no) experimental between-subjects design. Offering feedback increased the likelihood of participation and reduced the likelihood of participants receiving fixed payment to drop out. Offering feedback additionally improved data quality. Furthermore, offering feedback attracted participants with higher interest in research and the study topic. Offering fixed vs performance-contingent payment had little effect on the outcomes of interest. Offering feedback as compensation in EMA studies may facilitate recruitment and increase data quality; however, it may also risk higher selection bias. Conclusions are drawn from a relatively small student sample; the results thus need to be replicated in larger and more diverse samples.

Enhanced Readout Reliability in Phase Change Memory with a Dual-Sensing-Margin Offset-Compensated Sense Amplifier

Phase change memory (PCM) is considered one of the most promising candidates for next-generation non-volatile memory, owing to its scalability, durability, and cost-effectiveness. However, with the shrinking of device sizes and the reduction in supply voltages, achieving high-speed and reliable readouts in PCM has become increasingly challenging due to process variations. To address this, the dual-sensing-margin offset-compensated sense amplifier (DSOC-SA) is proposed. The DSOC-SA achieves the highest sensing margin, and the lowest read energy consumption compared to traditional sense amplifiers by utilizing a dual-sensing-margin structure, offset compensation, and strong positive feedback. Simulation results demonstrate that, compared to differential sense amplifier and offset-canceling current-sampling sense amplifier, DSOC-SA achieves a 5.6× and 1.6× improvement in sensing speed, respectively, while reducing power consumption by 87.1% and 51.2%.

Design and matching control strategy of electro-hydraulic load-sensitive hydraulic power unit for legged robots

A hydraulic power unit is the core energy source of hydraulic legged robots, ensuring the robot's maneuverability and carrying capacity in complex terrains. However, its pressure and flow output are usually set to a fixed level under all working conditions, which leads to mismatched pressure and flow requirements of hydraulic drive units. This mismatch reduces the stability and control accuracy of the hydraulic drive units and results in significant energy waste. To address these issues, this paper proposes an electro-hydraulic load-sensitive hydraulic power unit and a matching control strategy to better align outputs with requirements, thereby enhancing energy efficiency. Firstly, with the variable speed servo motor driving axial piston pump as the core, the closed system working principle of an electro-hydraulic load-sensitive hydraulic power unit is proposed, and the mathematical model of key components exhibiting strong nonlinearity and time-varying parameters is derived. After that, a matching control strategy based on flow feedforward and pressure difference compensation feedback is proposed. Finally, simulations and experiments are conducted to verify the feasibility of the unit and its matching control strategy. This paper provides a new solution for the design and control of hydraulic power units, laying the groundwork for achieving high-performance hydraulic systems.

Linear Disturbance Observer-Enhanced Continuous-Time Predictive Control for Straight-Line Path-Following Control of Small Unmanned Aerial Vehicles

This paper studies the straight-line path-following problem on the lateral plane for fixed-wing unmanned aerial vehicles (FWUAVs) which are susceptible to uncertainties. Firstly, based on the natural frame’s location on the prescribed reference paths, the command yaw angle (which is the basis for yaw angle control system design) is solved analytically by combining it with the errors of path following, attack angle, sideslip angle, attitude angles, and geometric parameters of the prescribed reference paths. Secondly, by considering complicated dynamic characteristics, a linear extended state observer is designed to estimate uncertainties such as nonlinearities, couplings, and unmodeled dynamics whose estimated values are incorporated into the continuous-time predictive controllers for feedback compensation. Finally, numerical simulations are conducted to demonstrate the advantages of the proposed method, including reduced tracking errors and enhanced robustness in the closed-loop system, as compared to the conventional nonlinear dynamic inversion and sliding mode control approaches.

On-line recognition of mixture control chart patterns using hybrid CNN and LSTM for auto-correlated processes

Statistical process control (SPC), designed to detect and identify process disturbances, is an effective quality control method for ensuring process stability. Owing to the growing automation of the industry, the manufacturing process can be autocorrelated. Engineer process control (EPC) is typically used to address autocorrelation. However, process disturbances can be offset by feedback compensation, making control chart patterns (CCPs) difficult to identify. Most studies on control chart pattern recognition (CCPR) techniques are based on a single abnormal control chart pattern (CCP). However, a mixture of CCPs can occur during real-world manufacturing processes. With the development of intelligent manufacturing systems, early detection of abnormal concurrent CCPs has become an important issue. In this study, a hybrid model combining a convolutional neural network (CNN) and long short-term memory (LSTM) in an online detection system was used to recognize the concurrent CCPR problem in SPC-EPC processes. The results showed that the average accuracy of the deep learning CNN-LSTM method was 99.83%, which was significantly better than that of the machine learning method. In addition, the running time of the CNN-LSTM model was shortened. In a comparison of online monitoring between the deep learning method and the machine learning method, the CNN-LSTM model for an online monitoring system identified abnormal concurrent patterns faster. Therefore, the proposed CNN-LSTM online monitoring scheme can be applied confidently and successfully to identify mixture CCPs in an SPC-EPC process.

A low power low phase noise wide frequency range PLL

This paper presents a low-noise, low-power, wide output frequency range phase-locked loop (PLL) for WLAN/WiFi transceivers. By employing a dual-symmetric CMOS cross-coupled pair differential inductor voltage-controlled oscillator (VCO), the design achieves low phase noise. In addition, an improved phase frequency detector (PFD) and a programmable low-mismatch charge pump (CP) with feedback compensation bias control are used to mitigate bandwidth and noise variations caused by different reference frequencies. The improved charge pump PLL (CPPLL) is designed in 65 nm CMOS process, and the chip layout occupies an area of 0.28 mm2. Post-layout simulation results indicate that the PLL has a tuning range of 4.6 GHz to 6 GHz, a phase noise of 111.7 dBc/Hz at 1 MHz offset at 5 GHz, a total power consumption of 7.14 mW, and a lock time of about 9μs.

A study on GaN-based high-efficiency class E power amplifier circuits at medium-low frequencies

Abstract In this paper, a high-power amplifier is designed to address the challenges of low transmission power and poor efficiency in wireless energy transmission technology at low frequencies. The design is based on a class E power amplifier circuit. The theoretical analysis is conducted to determine transistor selection and the static DC operating point. Load traction technology is employed to match the load impedance of the power amplifier, ensuring highly efficient and unified power additional efficiency, and output power. To enhance system stability and feedback compensation, gate series resistance and parallel capacitors are incorporated. Simulation results demonstrate that the designed power amplifier achieves an output power of 48 dBm with a power additive efficiency (PAE) of 85%. Furthermore, the third-order intermodulation component reaches 70 dBm, indicating concentrated output energy and high linearity in the amplifier system. Experimental results validate the consistency between theoretical analysis and model simulation, confirming the stability of the designed power amplifier circuit, and successfully achieving energy-efficient, high-power transmission.

Dynamic Optimal Obstacle Avoidance Control of AUV Formation Based on MLoTFWA Algorithm

In addressing the optimal formation obstacle avoidance control problem for Autonomous Underwater Vehicles (AUVs) in environments with unknown and moving obstacles, this paper employs the Modified Fireworks Algorithm based on a Loser Elimination Mechanism (MLoTFWA) and constructs a Distributed Model Predictive Control (DMPC) framework to achieve obstacle avoidance for AUV formations. Initially, a prediction model is established, followed by feedback compensation to mitigate the effects of unknown perturbations. An appropriate fitness function is then formulated, and enhancements such as the loser elimination rule are introduced to optimize the fireworks algorithm. Additionally, the concept of an adaptive DMPC prediction window is proposed to conserve resources. The local and global stability of the DMPC formation control framework is theoretically proven. Simulations verify that the control system based on the DMPC framework ensures safe obstacle avoidance for the formation, maintains formation consistency, and achieves the shortest and smoothest path. The improved fireworks algorithm demonstrates superior performance compared with the original fireworks algorithm and other optimization algorithms. In testing, the improved fireworks algorithm exhibits better adaptability, higher average fitness, and best fitness, along with a significantly faster convergence speed. Compared with the ordinary fireworks algorithm, the convergence speed is reduced by 30%.

A Transient Damping Improvement Strategy for Enhancing Grid-Connected Active Power Response Performance of VSG

The given power and grid frequency disturbances can cause transient oscillations and steady-state deviations in the output power of a virtual synchronous generator (VSG), which can be effectively addressed by adding transient damping. However, this approach may result in significant power overshoot. This article proposes an improved VSG control strategy based on transient electromagnetic power feedback compensation and a small-signal model reduction scheme. Firstly, the grid-connected active closed-loop small-signal models of typical VSG control and transient damping VSG control are established, respectively. The transient oscillation suppression mechanism of active power is revealed through root locus and frequency response analyses, and the power overshoot characteristics of the two control strategies are analysed by combining them with the system of zero points. Secondly, the active transient feedback compensation method and the small-signal model reduction design method are introduced in detail. Finally, comparative analysis experiments are conducted using the Matlab/Simulink and hardware-in-the-loop experimental platform. It is verified that the proposed control strategy can suppress transient oscillations in active power, prevent steady-state deviations, and effectively mitigate the power overshoot problem of the system.

A Study of Friction Nonlinearity and Compensation for Turntable Servo Systems

In view of the worse dynamic performance and steady-state accuracy caused by nonlinear friction in turntable servo systems, challenges are posed in precise positioning tasks. However, most of the existing research ignores the effect of friction on system performance. Therefore, it is of great significance to analyze the nonlinear characteristics of the transmission mechanism and study compensation strategies for improving the control quality of non-direct drive turntable servo systems. Therefore, an improved active disturbance rejection control (ADRC) based on state feedback compensation is proposed in this paper to optimize the accuracy of the turntable servo system and improve the robustness of the system under nonlinear friction conditions. Firstly, friction is modeled and analyzed through offline identification, which is the basis for nonlinear friction compensation. Subsequently, the two methods of friction compensation are compared. Since feedforward compensation is prone to under-compensation and over-compensation, it is highly dependent on the parameters, while the traditional ADRC compensation method has poor dynamic performance under gap conditions. Therefore, the advantages of ADRC and state feedback are combined together to reduce the steady-state error and optimize the control performance of the system. Lastly, the effectiveness of the proposed compensation method is verified and compared through simulations and experiments. The method is able to comprehensively compensate the gap and friction nonlinearities, and the experimental steady-state error is reduced from 0.55° to 1/3 (0.19°), which improves the load-side positioning accuracy. Finally, a conclusion can be drawn that the new compensation method can improve the parameter adjustability, speed estimation precision, and system robustness.

A guaranteed cost based memory event‐triggered control of networked control systems with multiple disturbances via an interconnected disturbance observer approach

AbstractThis article is dedicated to event‐triggered anti‐disturbance control of networked control systems via a guaranteed cost triggering scheme. A distribution interconnected observer structure is built to estimate these unknown matched disturbances. A novel event triggered condition is constructed in terms of real‐time cost and averaged functions composed of observer states and the last successfully transmitted one. A composite control scheme is provided by an event‐triggered observer‐based state feedback controller and compensators for the matched disturbances. A sufficient condition in term of linear matrix inequality is supplied to ensure the asymptotic stability of the resultant closed‐loop system. A simulation is carried out to demonstrate the effectiveness of the proposed triggering control strategy.

Design and implementation of an adaptive unscented Kalman filter with interval Type-3 fuzzy set for an attitude and heading reference system considering gyroscope bias

Low-cost microelectromechanical sensors used in attitude and heading reference systems (AHRS) suffer from unstable on–off biases, scaling errors, and nonlinearities that lead to an increase of navigation errors over time. To damp these errors and uncertainties from ultimate attitude and heading angles, the bias term of gyroscopes is augemented in under estimation state vector for high frequency feedback compensation. In this paper, an adaptive estimation algorithm to combine the strong tracking filter (STF) and interval type-3 fuzzy set (IT3FS) with an unscented Kalman filter (UKF) is proposed to deal with the large uncertainties in the microelectromechanical AHRS. The UKF, involving strong capability of dealing with nonlinearity, is limited by large instable bias uncertainty. By combining the STF to adaptively tuning of the UKF gain matrix and the IT3FS to determine the STF fading factor as well, the new IT3FS-STUKF algorithm is developed for high estimation performance against the significant uncertainties. To validate the proposed IT3FS-STUKF, real experiments are conducted with ground vehicles in urban areas, which show an improved accuracy compared to the extended Kalman filter (EKF) at reasonable computational burden.

Evolutionary dynamics of cooperation coupled with ecological feedback compensation

A simple theoretical model (or a demonstrative example) was developed to illustrate how the evolution of cooperation can be affected by the density-dependent survival competition, in which we assume that the fertility of an individual depends only on the pairwise interaction between him and other individuals based on Prisoner’s Dilemma game, while its viability is only related to the density-dependent survival competitiveness. Our results show that not only cooperation could be evolutionarily stable if the advantage of cooperators in viability can compensate for the cost they pay for their fertility, but also the long-term stable coexistence of cooperation and defection is possible if none of cooperation and defection is evolutionarily stable. Moreover, for the stochastic evolutionary dynamics in a finite population, our analysis shows that the increase (or decrease) of the survival competitiveness of cooperators (or defectors) should be conductive to the evolutionary emergence of cooperation.

A two‐step sizing method for multistage Op Amps based on behavioral initial sizing followed by Spice‐in‐the‐loop refining

AbstractAnalog integrated circuit sizing is a laborious process that requires many times of iteration with Spice simulations. Even by applying the method, it still requires iterations and test assignment of device values (and biasings) in each iteration until reaching a satisfactory sizing result. When facing a design of multiple‐stage circuits (such as multiple‐stage operational amplifier [Op Amp]), sizing becomes more challenging due to the requirement on pole‐zero placement in order to achieve a better high‐frequency performance. Simulation‐in‐the‐loop method has been the dominating means taken by a great many of existing circuit sizer, but they suffer from intolerable runtime while lacking the possibility of offering insight or design knowledge acquisition. On the other hand, behavioral‐level synthesis methods, although intuitive and fast, suffer from accuracy loss due to the adoption of simplified device models and significantly condensed design equations. However, a proper combination of these two types of methods could lead to a lucrative research territory, yet it demands a methodological development for efficient deployment in practice, namely, implementation easy, less runtime, and guaranteed sizing quality. In this paper, we propose a two‐step method that takes the advantage of behavioral synthesis (in the first step) that is capable of fast and broader coverage of design space then makes correction (in the second step) on sizing refining by Spice simulation. Due to the profiling knowledge acquired on the design space in the first step, it can avoid blindness of the optimization landscape that is faced by many simulation‐centric methods which could easily get trapped in local optima. Conducted experiments over eight three‐stage Op Amps with different compensation configurations, including nested Miller capacitor (NMC), NMC with feedforward path (NMCF), NMC with feedforward path and nulling resistor (NMCFNR), NMC with nulling resistor (NMCNR), double pole‐zero cancellation (DPZC), transconductance with capacitances feedback compensation (TCFC), impedance adapting compensation (IAC), active feedback frequency compensation (AFFC), have validated that the proposed method can successfully generate qualified sizing results, offering an opportunity to compare fairly what merit a specific compensation strategy could possibly have.

Sliding mode disturbance compensated speed control for PMSM based on an advanced reaching law

AbstractAddressing the sensitivity of permanent magnet synchronous motors to external disturbances, a novel sliding mode control (NSMC) strategy is proposed to suppress sliding mode jitter and enhance speed regulation performance. First, an advanced nonsingular fast terminal sliding mode (ANFTSM) surface and a new adaptive power rate reaching law (NAPRRL) were developed. A new switching function replaces the conventional sign function to enhance the system's disturbance immunity and dynamic response speed. Then, the system's anti‐interference performance was further enhanced by introducing an improved novel sliding mode observer (INSMO) for feedback compensation of the aggregate disturbance. Finally, MATLAB/Simulink simulations and experimental validations demonstrate that the NSMC control strategy exhibits superior performance in both the start‐up response and load disturbance phases, with enhanced dither resistance, rapid dynamic response, and disturbance suppression capabilities.

High-precision high-speed nanopore ping-pong control system based on field programmable gate array.

"Molecular ping-pong," emerging as a control strategy in solid-state nanopore technology, presents a highly promising approach for repetitive measurements of single biomolecules, such as DNA. This paper introduces a high-precision, high-speed nanopore molecular ping-pong control system consisting of a home-built trans-impedance amplifier (TIA), a control system based on a Field Programmable Gate Array (FPGA), and a LabVIEW program operating on the host personal computer. Through feedback compensation and post-stage boosting, the TIA achieves a high bandwidth of about 200kHz with a gain of 100 MΩ, along with low input-referred current noise of 1.6 × 10-4pA2/Hz at 1kHz and 1.1 × 10-3pA2/Hz at 100kHz. The FPGA-based control system demonstrates a minimum overall response time (tdelay) of 6.5 μs from the analog input current signal trigger to the subsequent reversal of the analog output drive voltage signal, with a control precision of 1 μs. Additionally, a LabVIEW program has been developed to facilitate rapid data exchange and communication with the FPGA program, enabling real-time signal monitoring, parameter adjustment, and data storage. Successful recapture of individual DNA molecules at various tdelay, resulting in an improvement in capture rate by up to 2 orders of magnitude, has been demonstrated. With unprecedented control precision and capture efficiency, this system provides robust technical support and opens novel research avenues for nanopore single-molecule sensing and manipulation.