Integral Feedback Control Research Articles

Integrating feedback control for improved human-structure interaction analysis

The human body, composed of interconnected subsystems with complex dynamic behavior, is often oversimplified or neglected by structural designers and building codes. Human-induced loads, whether passive (e.g., standing, sitting) or active (e.g., walking, dancing, jumping), considerably impact the dynamic response of structures such as grandstands, slender slabs, and pedestrian bridges, highlighting the necessity for their consideration in design. This study introduces three closed-loop control models to represent the human-structure interaction (HSI) effect: a Proportional Integral (PI) controller, the Pole Placement control algorithm (PP), and the Linear Quadratic Regulator with an Observer (LQR + L). While well-established in robotics and automation engineering, these control algorithms represent a novel and transformative approach when applied to HSI. They offer an intuitive and effective framework for modeling the dynamic feedback mechanisms inherent in HSI. The model parameters are obtained using global optimization and curve fitting methods, followed by experimental validation on a test structure. The results of this study indicate that feedback controllers accurately predict the experimental structural response for different subjects. These findings highlight the importance of incorporating HSI effects into structural design, promising the design of safer and more comfortable structures in human-occupied environments.

Autonomous learning of generative models with chemical reaction network ensembles.

Can a micron-sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory and statistical physics to develop a general architecture whereby a broad class of chemical systems can autonomously learn complex distributions. Our construction takes the form of a chemical implementation of machine learning's optimization workhorse: gradient descent on the relative entropy cost function, which we demonstrate can be viewed as a form of integral feedback control. We show how this method can be applied to optimize any detailed balanced chemical reaction network and that the construction is capable of using hidden units to learn complex distributions.

Perancangan Kendali Integral State Feedback (KISF) Pada Sistem Pengaturan Kecepatan Motor DC

This research aims to design and simulate a DC motor speed control system using integral state feedback (KISF) control. This control is designed to maintain DC motor speed stability with high accuracy despite disturbances or load changes. The research stages include mathematical modeling of the DC motor, PID control design, integral state feedback control design, simulation implementation and simulation results analysis. The show that althought integral state feedback control has a rise time 273.501 ms, slightly slower than PID 197.604 ms, integral state feedback compensates with higher slew rate of change 6.540 V/ms compared to PID 4.344 V/ms. Integral state feedback offers greater flexibility through pole placement values with Ackerman’s formula J3 = [-12 -100 -600], indicating that this system has good capability in responding to input changes, thus maintaining motor speed stably and efficiently. This indicates that integral state feedback control is superior in system adaptation and handling complex dynamics.

Robust Driving Control Design for Precise Positional Motions of Permanent Magnet Synchronous Motor Driven Rotary Machines with Position-Dependent Periodic Disturbances

Position-dependent periodic disturbances often limit the accuracy and smoothness of the positional motion of permanent magnet synchronous motor (PMSM)-driven rotary machines. Because the period of these disturbances varies with the motion velocity of the rotary machine, spatial domain control methods such as spatial iterative learning control (SILC) and spatial repetitive control (SRC) have been proposed and applied to improve rotary machine motion control designs. However, problems with learning period convergence and rotary machine dynamics significantly affect transient motion, further constraining the overall motion performance. To address these challenges, this study developed a robust driving control (RDC) that integrates a robust control design with position-dependent periodic disturbance feedforward compensation, rotary machine dynamics compensation, and proportional–proportional integral feedback control. A position-dependent periodic disturbance model was developed using multiple position–sinusoidal signals and identified using a spatial fast Fourier transform. RDC compensates for disturbances and dynamics and considers the effects of model parameter uncertainty and modeling error on the stability of the control system. Several motion control experiments were conducted on a PMSM test bench to compare the RDC, SILC, and SRC. The experimental results demonstrated that although both SILC and SRC can effectively suppress position-dependent periodic disturbances, SILC provides slower position error convergence owing to the learning process, and SILC and SRC result in significant position errors because of the influence of the PMSM-driven rotary machine dynamics. RDC not only suppresses position-dependent periodic disturbances, but also significantly reduces position errors with a reduction rate of 90%. Therefore, the RDC developed in this study effectively suppressed position-dependent periodic disturbances and significantly improved both the transient-state and steady-state position-tracking performances of the PMSM-driven rotary machine.

Digital stabilization of an I/Q modulator in the carrier suppressed single-sideband mode for atom interferometry

We present an all-digital method for stabilizing the phase biases in an electro-optic I/Q modulator for carrier-suppressed single-sideband (CS-SSB) modulation. Using programmable logic on the Red Pitaya STEMlab 125-14 platform, we digitally generate and demodulate an auxiliary radio-frequency tone whose beat with the optical carrier probes the I/Q modulator’s phase imbalances. We implement a multiple-input, multiple-output integral feedback controller that accounts for unavoidable cross-couplings in the phase biases to lock the error signals at exactly zero, where optical power fluctuations have no impact on phase stability. We demonstrate >23dB suppression of the optical carrier relative to the desired sideband at +3.4GHz over a period of 15 h and over temperature variations of 20°C.

Integral resonant negative derivative feedback suppression control strategy for nonlinear dynamic vibration behavior model

Integral resonant negative derivative feedback suppression control strategy for nonlinear dynamic vibration behavior model

A distributed integral control mechanism for regulation of cholesterol concentration in the human retina.

Tight homeostatic control of cholesterol concentration within the complex tissue microenvironment of the retina is the hallmark of a healthy eye. By contrast, dysregulation of biochemical mechanisms governing retinal cholesterol homeostasis likely contributes to the aetiology and progression of age-related macular degeneration (AMD). While the signalling mechanisms maintaining cellular cholesterol homeostasis are well-studied, a systems-level description of molecular interactions regulating cholesterol balance within the human retina remains elusive. Here, we provide a comprehensive overview of all currently-known molecular-level interactions involved in cholesterol regulation across the major compartments of the human retina, encompassing the retinal pigment epithelium (RPE), photoreceptor cell layer, Müller cell layer and Bruch's membrane. We develop a comprehensive chemical reaction network (CRN) of these interactions, involving 71 molecular species, partitioned into 10 independent subnetworks. These subnetworks collectively ensure robust homeostasis of 14 forms of cholesterol across distinct retinal cellular compartments. We provide mathematical evidence that three independent antithetic integral feedback controllers tightly regulate ER cholesterol in retinal cells, with additional independent mechanisms extending this regulation to other forms of cholesterol throughout the retina. Our novel mathematical model of retinal cholesterol regulation provides a framework for understanding the mechanisms of cholesterol dysregulation in diseased eyes and for exploring potential therapeutic strategies.

Simulation and time series analysis of responsive active Brownian particles (rABPs) with memory

To realise the goals of active matter at the micro- and nano-scale, the next generation of microrobots must be capable of autonomously sensing and responding to their environment to carry out pre-programmed tasks. Memory effects are proposed to have a significant effect on the dynamics of responsive robotic systems, drawing parallels to strategies used in nature across all length-scales. Inspired by the integral feedback control mechanism by which Escherichia coli (E. coli) are proposed to sense their environment, we develop a numerical model for responsive active Brownian particles (rABP) in which the rABPs continuously react to changes in the physical parameters dictated by their local environment. The resulting time series, extracted from their dynamic diffusion coefficients, velocity or from their fluctuating position with time, are then used to classify and characterise their response, leading to the identification of conditional heteroscedasticity in their physics. We then train recurrent neural networks (RNNs) capable of quantitatively describing the responsiveness of rABPs using their 2D trajectories. We believe that our proposed strategy to determine the parameters governing the dynamics of rABPs can be applied to guide the design of microrobots with physical intelligence encoded during their fabrication.

The Impact of the Nonlinear Integral Positive Position Feedback (NIPPF) Controller on the Forced and Self-Excited Nonlinear Beam Flutter Phenomenon

This article presents a novel approach to impact regulation of nonlinear vibrational responses in a beam flutter system subjected to harmonic excitation. This study introduces the use of a Nonlinear Integral Positive Position Feedback (NIPPF) controller for this purpose. This technique models the system as a three-degree-of-freedom nonlinear system representing the beam flutter, coupled with a first-order and a second-order filter representing the NIPPF controller. By applying perturbation analysis to the linearized system model, the authors obtain analytical solutions for the autonomous system with the controller. This study aims to reduce vibration amplitudes in a nonlinear dynamic system, specifically when 1:1 internal resonance occurs. The Routh–Hurwitz criterion is utilized to evaluate the system’s stability. Furthermore, the frequency–response curves (FRCs) exhibit symmetry across a range of parameter values. The findings highlight that the effectiveness of vibration suppression is directly related to the product of the NIPPF control signal after comparing with different controllers. Numerical simulations, conducted using the fourth-order Runge–Kutta method, validate the analytical solutions and demonstrate the system’s amplitude response. The strong correlation between the analytical and numerical results highlights the accuracy and dependability of the proposed method.

Biofabrication of Living Actuators.

The impact of tissue engineering has extended beyond a traditional focus in medicine to the rapidly growing realm of biohybrid robotics. Leveraging living actuators as functional components in machines has been a central focus of this field, generating a range of compelling demonstrations of robots capable of muscle-powered swimming, walking, pumping, gripping, and even computation. In this review, we highlight key advances in fabricating tissue-scale cardiac and skeletal muscle actuators for a range of functional applications. We discuss areas for future growth including scalable manufacturing, integrated feedback control, and predictive modeling and also propose methods for ensuring inclusive and bioethics-focused pedagogy in this emerging discipline. We hope this review motivates the next generation of biomedical engineers to advance rational design and practical use of living machines for applications ranging from telesurgery to manufacturing to on- and off-world exploration.

LQR controller design for portable power supply based on flyback converter

Abstract The stability of the power repair equipment guarantees the reliability of the repair of electrical equipment. The following problems exist in the power supply of the emergency equipment: the load equipment randomly cuts in the power supply network; load equipment requires fast dynamic performance of the power supply. This challenges the stability of the portable power supply with the Flyback converter as the core. In this paper, an optimal feedback control strategy based on linear quadratic regulator (LQR) theory is proposed to improve the dynamic and steady-state performance of the Flyback converter. First, the state-averaged space model of the Flyback is derived and established. Second, an output voltage feedback integral controller is introduced to eliminate the steady-state error of the output voltage. Next, according to the LQR optimal control theory, the control model of the Flyback converter has been established, and the parameter design of the controller has been carried out by obtaining the optimal feedback gain matrix of the system. Finally, the simulation models are implemented with an output power of 120 W and a switching frequency of 50 kHz. The simulation results prove that the LQR controller provides superior performance than the traditional PI controller.

An atomic force microscope-like dual-stage force controlled fast tool servo for in-process inspection of micro-structured surfaces

An atomic force microscope-like dual-stage force controlled fast tool servo for in-process inspection of micro-structured surfaces

Charging delay elimination of solder impregnated HTS coils with specific excitation current

Charging delay elimination of solder impregnated HTS coils with specific excitation current

Pole placement tuning of proportional integral derivative feedback controller for knee extension model

Functional electrical stimulation (FES) has shown potential in rehabilitative exercises for patients recovering from spinal cord injuries. In recent developments, conventional open-loop FES control techniques have evolved into closed-loop systems that employ feedback controllers for automation. However, closed-loop FES systems often face challenges due to muscle non-linear effects, such as fatigue, time delays, stiffness, and spasticity. Therefore, an accurate non-linear knee model is required during the design stage, and precise tuning of the feedback controller parameters is vital. A proportional– integral–derivative (PID) controller is commonly used as a feedback controller due to its simplicity and ease of implementation. However, most PID tuning methods are complex and time consuming. This paper investigates the viability of employing the pole placement technique for tuning a PID controller that regulates the non-linear knee extension model. The pole placement method aims to improve the control and adaptability of the PID controller in closed-loop FES systems, specifically by facilitating knee extension exercises. MATLAB Simulink was used to assess the effectiveness of this tuning approach. Results showed that the PID controller performed satisfactorily without non-linearities, but performance varied with the inclusion of specific non-linearities. The pole placement tuning method facilitated preliminary assessments of PID controller performance, preceding highly advanced optimization.

Design principles as minimal models

In this essay I suggest that we view design principles in systems biology as minimal models, for a design principle usually exhibits universal behaviors that are common to a whole range of heterogeneous (living and nonliving) systems with different underlying mechanisms. A well-known design principle in systems biology, integral feedback control, is discussed, showing that it satisfies all the conditions for a model to be a minimal model. This approach has significant philosophical implications: it not only accounts for how design principles explain, but also helps clarify one dispute over design principles, e.g., whether design principles provide mechanistic explanations or a distinct kind of explanations called design explanations.

Experimental study on an enhanced integral force feedback controller for active damping

In this paper, an enhanced integral force feedback controller is proposed for implementing active damping. Compared with the classical integral force feedback, the pure integrator is replaced with a combination of a first-order low-pass filter and a proportional term. The control performance of the proposed controller is examined on a single-degree-of-freedom host system. In order to better understand the physics behind, a full equivalent mechanical model is derived. It is found that the first-order low-pass filter is mechanically equivalent to a spring and a damper connected in parallel. The proportional term mechanically represents a spring which is connected in series with the inherent actuator spring. The optimal control parameters are numerically obtained with the ℋ∞ optimisation criterion. The analysis shows that the optimal feedback gain can be practically taken the same as that of the classical integral force feedback controller in the sense that the difference between the resultant control performance is negligible. The numerical study is also experimentally validated. The obtained results are found to correspond well with the theoretical developments.

Observer-based robust preview tracking control for a class of continuous-time Lipschitz nonlinear systems

<p>In this paper, a novel observer-based robust preview tracking controller design method is proposed for a class of continuous-time Lipschitz nonlinear systems with external disturbances and unknown states. First, a state observer is designed to reconstruct unknown system states. Second, using differentiation, the state lifting technique, the differential mean value theorem, and several ingenious mathematical manipulations, an augmented error system (AES) containing the previewable information of a reference signal is constructed, thereby transforming the tracking control problem into a robust $ H_{\infty} $ control problem. Based on linear parameter-varying (LPV) system theory, a sufficient condition for asymptotic stability of a closed-loop system with a robust $ H_{\infty} $ performance level is established in terms of the linear matrix inequality (LMI). Furthermore, a tracking controller, which includes observer-based feedback control, integral control, and preview feedforward compensation, is established for the original system. In particular, the tracking controller design is simplified by computing the observer and tracking controller gains simultaneously via only a one-step LMI algorithm. Finally, numerical simulation results demonstrate that the proposed controller leads to superior improvement in the output tracking performance compared with the existing methods.</p>

Performance analysis of proportional feedback control and integral control in DC motors and speed control

Control systems play a crucial role in modern engineering and technology, and their stability and performance are vital for the success of various applications. This paper aims to explore the application and performance analysis of proportional feedback control (P control) in DC motors and integral control (PI control) in speed control. The following section provides an exposition of the fundamental principles underpinning P control and PI control, alongside an exhaustive account of their practical implementations within the Tinkercad and Octave software environments. The simulations carried out in Tinkercad serve as the basis for evaluating step responses associated with varying values, leveraging a 1Hz function generator. Subsequent analysis pertains to proportional-integral control through the utilization of Octave's PZmap and root locus methodologies, with specific regard to their implications for system stability and control performance in the context of speed control. The experimental outcomes reveal the aptitude of P control in scenarios demanding rapid responses, while establishing the superiority of PI control in the context of steady-state error mitigation. In the experimental analysis conducted, an evident trend emerged as Kp values were systematically increased within the framework of proportional feedback control. The primary observation related to the reduction in system response times, along with the concurrent rise in overshooting tendencies.

Optimization and Stabilization of Distributed Secondary Voltage Control with Time Delays and Packet Losses Using LMIs

The proposed hierarchical secondary voltage control is a spatially distributed control system using communication networks which are disturbed by both a time delays and packet data dropouts. A state feedback integral control is adopted to eliminate the effect of non-zero disturbance and provide exact tracking of the references of the pilot points and alignment of the reactive powers of the generators that participate in the control. The system is modeled as a discrete-time switched system, and the control gains are synthesized by solving LMIs for a stability condition based on a state-dependent Lyapunov function. For that, the cone complementarity linearization (CCL) algorithm is used. The effectiveness of the proposed control strategy in preventing time delays and packet losses is simulated, considering the model of a realistic electric power grid under typical operational conditions using MATLAB.

A Proportional–Integral Feedback Controlled Automatic Flow Chemistry System to Produce On‐Demand AgAu Alloy Nanoboxes

Mixed‐metal nanoparticles present a challenging task for synthesis with high precision and reproducibility due to the complex interplay of compositional and reaction condition factors. The present study demonstrates a highly precise and automated flow chemistry technique for synthesizing AgAu alloy nanoboxes with tailored optical properties. The synthesis process involves a proportional–integral (PI) feedback control mechanism that enables accurate regulation of reaction parameters, such as the flow rate, to achieve the target AgAu nanoboxes having a desired UV–vis absorbance wavelength. The PI control algorithm is built on the first‐order plus dead‐time model, which correlates the flow rate of the precursors with the maximum absorbance peaks of the resultant nanoalloy products. Based on the difference between the real‐time measured UV–vis absorbance wavelength and the target wavelength, the flow rate of the precursor (i.e., reagent concentration) is tuned via an iterative process until the real‐time absorbance wavelength of the AgAu alloy nanoboxes is matched with the target setpoint. The implementation of a PI feedback control mechanism in a flow chemistry system can offer a highly versatile and universal strategy for generating on‐demand complex nanomaterials with significantly enhanced consistency and reliability by mitigating concentration variations and minimizing the need for human intervention.