Search

In the present paper, the primary resonance and feedback control of the fractional Duffing-van der Pol oscillator with quintic nonlinear-restoring force is studied. The approximately analytical solution and the amplitude-frequency equation are obtained using the multiple scale method. Based on the Lyapunov theory, the stability conditions for the steady-state solution are obtained. The bifurcations of primary resonance for system parameters are analyzed, and the influence of parameters on fractional-order model is also studied. Numerical simulation shows that when the parameter values are fixed, the curve bends to the right or left, resulting in jumping phenomena and multi-valued amplitudes. As the excitation frequency changes, the typical hardening or softening characteristics of the oscillator are observed. In addition, the comparisons of approximate analytical solution and numerical solution are fulfilled, and the results certify the correctness and satisfactory precision of the approximately analytical solution.

This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme.

This article aims to unravel the dynamics of social influence by examining the processes that occur when one person is the target of another’s influence. We hypothesized that these processes are part of a feedback loop system in an individual. This loop involves the situation (input), a goal state (reference), a comparator, a selection mechanism, a feedback predictor, and an action (output). Each element can become the target of social influence, and different types of social influence can be classified and explained by how these elements are targeted. For instance, attempting to persuade another person with strong arguments targets the goal state of the affected individual, while obedience targets the selection mechanism, and violence targets the action. In summary, this article aims to categorize, order, and explain phenomena in social influence research using a feedback loop framework focusing on the influenced individual.

Simultaneous ultra-intense pulses at petawatt laser facilities enable a broad range of experiments in nuclear photonics and strong field quantum electrodynamics. These experiments often require very precise control of the time delays between pulses. We report measurements of the time delay between the two 1 PW outputs of the Extreme Light Infrastructure - Nuclear Physics (ELI-NP) facility in Romania. The short-term standard deviation of the time delay was approximately half of the pulse duration of 23 fs, and the average delay drifted with up to 100 fs/h. The drift and sporadic delay jumps were corrected using a feedback loop, which reduced the long-term standard deviation of the delay close to its short-term value. These results imply that in ELI-NP experiments using two simultaneous pulses, a temporal overlap of better than half of the pulse duration can be achieved for more than two thirds of the shots, which would enable high data rate experiments using simultaneous petawatt pulses.

Physiological networks, as observed in the human organism, involve multi-component systems with feedback loops that contribute to self-regulation. Physiological phenomena accompanied by time-delay effects may lead to oscillatory and even chaotic dynamics in their behaviors. Analogous dynamics are found in semiconductor lasers subjected to delayed optical feedback, where the dynamics typically include a time-delay signature. In many applications of semiconductor lasers, the suppression of the time-delay signature is essential, and hence several approaches have been adopted for that purpose. In this paper, experimental results are presented wherein photonic filters utilized in order to suppress time-delay signatures in semiconductor lasers subjected to delayed optical feedback effects. Two types of semiconductor lasers are used: discrete-mode semiconductor lasers and vertical-cavity surface-emitting lasers (VCSELs). It is shown that with the use of photonic filters, a complete suppression of the time-delay signature may be affected in discrete-mode semiconductor lasers, but a remnant of the signature persists in VCSELs. These results contribute to the broader understanding of time-delay effects in complex systems. The exploration of photonic filters as a means to suppress time-delay signatures opens avenues for potential applications in diverse fields, extending the interdisciplinary nature of this study.

This article aims to unravel the dynamics of social influence by examining the processes that occur when one person is the target of another’s influence. We hypothesized that these processes are part of a feedback loop system in an individual. This loop involves the situation (input), a goal state (reference), a comparator, a selection mechanism, a feedback predictor, and an action (output). Each element can become the target of social influence, and different types of social influence can be classified and explained by how these elements are targeted. For instance, attempting to persuade another person with strong arguments targets the goal state of the affected individual, while obedience targets the selection mechanism, and violence targets the action. In summary, this article aims to categorize, order, and explain phenomena in social influence research using a feedback loop framework focusing on the influenced individual.

In this work, we set up a new discrete predator–prey competitive model with time-varying delays and feedback controls. By virtue of the difference inequality knowledge, a sufficient condition which guarantees the permanence of the established discrete predator–prey competitive model with time-varying delays and feedback controls is derived. Under some appropriate parameter conditions, we have proved that the periodic solution of the system without delay exists and globally attractive. To verify the correctness of the derived theoretical fruits, we give two examples and execute computer simulations. Our obtained results are novel and complement previous known results.

CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction. • Designed precision mismatches at crRNA level reduce the overall gene expression. • Decoy crRNA binding sites reduce repression of expression in the absence of induction. • Feedback control of crRNA levels enables gradual control of the expression level. [ABSTRACT FROM AUTHOR]

This study presents the feasibility of implementing commercial-off-the-shelf reciprocating piston compressors for a developed active flow control (AFC) actuation framework to quantify the aerospace relevant performance ramifications of control architecture and compressor operational choices. Three architectures are studied: supply valve metering, exit area metering, and a combined approach. All concepts are studied under varying compressor operation schedules. The analysis framework in this study integrates internal pneumatic actuation and discharge dynamics, an experimentally calibrated compressor pressure and thermal dynamics model, three feedback control architectures, and flight dynamics models. The framework is implemented in simulation to provide a user-friendly tool for linking AFC architecture choices to achievable flight trajectories. Actuator performance is evaluated using actuation time, output, compressor duty cycle, and specific energy consumption. Aircraft tracking performance is evaluated as usable time and slalom centerline deviation. The analysis indicates that a supply-volume-based metering approach is comparatively inefficient concerning an exit-area-based metering, resulting in high flight tracking error. Exit area metering provides the best efficiency and run time with some structural drawbacks, while the combined approach provides the best flight tracking performance at the expense of additional complexity. These results inform the choice of onboard AFC hardware choices. [ABSTRACT FROM AUTHOR]

This paper studies a class of the non-autonomous competition and cooperation model of two enterprises involving discrete time delays and feedback controls. The paper proposes new criteria for analyzing the permanence, periodic solution, and global attractiveness of the model. The common mathematical techniques of the Lyapunov method, the continuation theorem, and the comparison principle are used in this paper. By means of the comparison principle and inequality techniques, the concept of permanence is investigated, which refers to the long-term survival of the enterprises within the competitive and cooperative framework. Meanwhile, using the continuation theorem, we establish conditions under which the system exhibits periodic behavior. Additionally, the global attractiveness of the system is derived by constructing multiple Lyapunov functionals. Finally, an example is presented to illustrate the applicability and validity of the proposed criteria in this paper. This example serves as a demonstration that showcases the main results derived from the analysis. [ABSTRACT FROM AUTHOR]

The dispersion of batch time, i.e., the time for finalizing batch crystallization satisfying batch end conditions, in internally seeded cooling crystallization with direct nucleation control (DNC) was estimated by computer simulation. The batch time is considered to disperse at such crystallization due to stochastic nucleation. In this study, first, a population balance equation was digitized for numerical calculation, and the simulation was developed in MATLAB. Then, repetitive simulations of internally seeded cooling crystallization considering stochastic nucleation with DNC were performed. Finally, the batch time of each simulation was arranged. As a result, it was found that there is little batch time dispersion in crystallization controlled by DNC and without adding seed. [ABSTRACT FROM AUTHOR]

Essential tremor (ET) is a neurological disorder characterized by involuntary oscillations of the limbs. Previous studies have hypothesized that ET is a cerebellar disorder and reported impairments in motor adaptation. However, recent advances have highlighted that motor adaptation involves several components linked to anticipation and control, all dependent on cerebellum. We studied the contribution of both components in adaptation to better understand the adaptation impairments observed in ET from a behavioral perspective. To address this question, we investigated behavioral markers of adaptation in ET patients (n = 20) and age-matched neurologically intact volunteers (n = 20) in saccadic and upper limb adaptation tasks, probing compensation for target jumps and for velocity-dependent force fields, respectively. We found that both groups adapted their movements to the novel contexts; however, ET patients adapted to a lesser extent compared with neurologically intact volunteers. Importantly, components of the movement linked to anticipation were preserved in the ET group, whereas components linked to movement execution appeared responsible for the adaptation deficit in this group. Altogether, our results suggest that execution deficits may be a specific functional consequence of the alteration of neural pathways associated with ET. [ABSTRACT FROM AUTHOR]

In this article, we consider the chemostat system with n≥1$$ n\ge 1 $$ species, one limiting substrate, and mutations between species. Our objective is to globally stabilize the corresponding dynamical system around a desired equilibrium point. Doing so, we introduce auxostat feedback controls which are controllers allowing the regulation of the substrate concentration. We prove that such feedback controls globally stabilize the resulting closed‐loop system near the desired equilibrium point. This result is obtained by combining the theory of asymptotically autonomous systems and an explicit computation of solutions to the limit system. The performance of such controllers is illustrated on an optimal control problem of Lagrange type which consists in maximizing the production of species over a given time period w.r.t. the dilution rate chosen as control variable. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We propose and analyze a new dynamical system with a closed-loop control law in a Hilbert space H , aiming to shed light on the acceleration phenomenon for monotone inclusion problems, which unifies a broad class of optimization, saddle point, and variational inequality (VI) problems under a single framework. Given an operator A : H ⇉ H that is maximal monotone, we propose a closed-loop control system that is governed by the operator I − (I + λ (t) A) − 1 , where a feedback law λ (·) is tuned by the resolution of the algebraic equation λ (t) ‖ (I + λ (t) A) − 1 x (t) − x (t) ‖ p − 1 = θ for some θ > 0. Our first contribution is to prove the existence and uniqueness of a global solution via the Cauchy–Lipschitz theorem. We present a simple Lyapunov function for establishing the weak convergence of trajectories via the Opial lemma and strong convergence results under additional conditions. We then prove a global ergodic convergence rate of O (t − (p + 1) / 2) in terms of a gap function and a global pointwise convergence rate of O (t − p / 2) in terms of a residue function. Local linear convergence is established in terms of a distance function under an error bound condition. Further, we provide an algorithmic framework based on the implicit discretization of our system in a Euclidean setting, generalizing the large-step hybrid proximal extragradient framework. Even though the discrete-time analysis is a simplification and generalization of existing analyses for a bounded domain, it is largely motivated by the aforementioned continuous-time analysis, illustrating the fundamental role that the closed-loop control plays in acceleration in monotone inclusion. A highlight of our analysis is a new result concerning p th -order tensor algorithms for monotone inclusion problems, complementing the recent analysis for saddle point and VI problems. Funding: This work was supported in part by the Mathematical Data Science Program of the Office of Naval Research [Grant N00014-18-1-2764] and by the Vannevar Bush Faculty Fellowship Program [Grant N00014-21-1-2941]. [ABSTRACT FROM AUTHOR]

Chaos, which is found in many dynamical systems, due to the presence of chaos, systems behave erratically. Due to its erratic behaviour, the chaotic behaviour of the system needs to be controlled. Severe acute respiratory syndrome Coronavirus 2 (Covid-19), which has spread all over the world as a pandemic. Many dynamical systems have been proposed to understand the spreading behaviour of the disease. This paper investigates the chaos in the outbreak of COVID-19 via an epidemic model. Chaos is observed in the proposed SIR model. The controller is designed based on the fractional-order Routh Hurwitz criteria for fractional-order derivatives. The chaotic behaviour of the model is controlled by feedback control techniques, and the stability of the system is discussed. [ABSTRACT FROM AUTHOR]

The Quadcopter is a flying machines that has four propellers driven by rotors. It has a simple mechanical design and excellent maneuverability and can perform vertical takeoff and landing. In order for the quadcopter to fly properly, a controller is needed that can maintain the stability of its flight. In this paper, a comparison of quadcopter motion stability testing using the Feedback control and LQG methods was carried out. The Linear Quadratic Gaussian control method is used in this research, which combines the Linear Quadratic Regulator with Kalman Filter. LQG control was chosen because it can estimate state variables that are not measured and save costs and time. At the same time, the feedback control system was selected because it can improve systems performance from the feedback generated. This research shows that the LQG control system is better than the feedback control. [ABSTRACT FROM AUTHOR]

This study proposes a deep learning-based approach to optimize power systems with hybrid renewable energy sources (HRES) using particle swarm optimization (PSO). The proposed algorithm is evaluated against the iterative optimization method to evaluate its efficacy. The study focuses on the network layer between the local HRES controllers and the distributed power control hub, where loads and renewable energy sources are aggregated and tested for their ability to interact with a centralized unit. The proposed method utilizes data from a variety of sources, both live and archived, to develop a Grey Wolf Optimization strategy for enhancing mitigation efforts and decreasing power quality disruptions. The system's efficiency is improved by algorithms, giving designers the flexibility to build a more flexible system while switching between various energy sources to produce electricity. The study also includes a deep learning-based approach to power forecasting and optimum sizing to minimize the system's cost while keeping its dependability. The proposed approach can help rural areas reduce their reliance on fossil fuels and improve dispatch efficiency, ultimately saving utility money. [ABSTRACT FROM AUTHOR]

Animal locomotion is highly adaptive, displaying a large degree of flexibility, yet how this flexibility arises from the integration of mechanics and neural control remains elusive. For instance, animals require flexible strategies to maintain performance as changes in mass or inertia impact stability. Compensatory strategies to mechanical loading are especially critical for animals that rely on flight for survival. To shed light on the capacity and flexibility of flight neuromechanics to mechanical loading, we pushed the performance of fruit flies (Drosophila) near its limit and implemented a control theoretic framework. Flies with added inertia were placed inside a virtual reality arena which permitted free rotation about the vertical (yaw) axis. Adding inertia increased the fly's response time yet had little influence on overall gaze stabilization performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. By contrast, mathematical modelling predicted a significant decrease in gaze stabilization performance. Adding inertia altered saccades, however, flies compensated for the added inertia by increasing saccade torque. Taken together, in response to added inertia flies increase reaction time but maintain flight performance through adaptive neural control. Overall, adding inertia decreases closed-loop flight robustness. Our work highlights the flexibility and capacity of motor control in flight. [ABSTRACT FROM AUTHOR]

An internal unsteady compressible flowfield of a pulsed jet actuator (PJA) is simulated by unsteady Reynolds-averaged Navier-Stokes (URANS) and large-eddy simulation (LES) frameworks. The PJA's feedback loops are short enough to have non-negligible jet switching time compared to the oscillation period. The results show that within a range of inlet pressure (which is the only control parameter) where the jet goes from subsonic to supersonic regime, the oscillation frequencies and the exit velocity waveform predicted by LES are in better agreement with the measured data than those predicted by URANS. Although URANS is able to capture the flowfield inside the feedback loops, it fails to predict the exit jet dynamics, unlike LES. This indicates the importance of a proper resolution of turbulence in the interaction region where jet switching occurs. Using LES data, it is found that the total jet switching time remains constant as the inlet pressure changes. It is also found that only the part of the jet switching period that ends at the first moment when the jet attaches to the opposite wall is involved in the oscillation period. Therefore, a new lumped model is proposed to estimate the oscillation frequency, which also explains the trend observed for the low inlet pressure values. [ABSTRACT FROM AUTHOR]

The paper deals with game-theoretical control problem for the continuity equation. It is assumed that all agents of a multiagent system are influenced by the same controls of both players depending only on current time and current distribution of the agents. We extend the notion of - and -stability and the Krasovskii–Subbotin extremal shift rule to a given case and construct suboptimal strategies of players. Also, the existence theorem for a value function is proved. [ABSTRACT FROM AUTHOR]

Precise regulation of oxidizer mass flow rate is a crucial technology for hybrid rocket motors, and a flow control valve serves as a core component of an oxidizer delivery system. In this paper, we designed a variable area cavitating venturi (VACV) as a flow control valve to control oxidizer mass flow rate. Three types of experiments were carried out to investigate VACA-based flow feedback control and its application in hybrid rocket motors. Specifically, we measured flow characteristics at different pintle strokes and conducted five cold tests and one ground hot test based on flow feedback control. Test results are as follows: first, the VACA flow characteristic curve shows a wide regulation range with a flow regulation ratio of 21.8 and performs good linearity of 96.76%. Second, the mass flow rate curve measured with flow feedback control tracks the target curve. Flow feedback control effectively improves control accuracy by maintaining the steady-state error within 1.2%. Third, hot test results demonstrate that the VACA with flow feedback control can effectively maintain the accurate and consistent oxidizer mass flow rate during the firing stage of the hybrid rocket motor. The findings of this research indicate that VACA with flow feedback control can be used as an effective flow regulation component to maintain a constant and accurate oxidizer mass flow rate during the working stage of a hybrid rocket motor. • A firing test of a hybrid rocket motor based on feedback control was conducted. • VACV shows good linearity with a wide regulation range in flow characteristics curve. • Feedback control with VACV improves accuracy, keeping steady-state error within 1%. • Feedback control maintains an accurate and consistent oxidizer mass flow rate. [ABSTRACT FROM AUTHOR]

The purpose of the present research endeavor is to propose a novel control strategy for a DC-DC electrical converter realized as a switched circuit. The present endeavor is based on an early work by Leonard and Krishnaprasad where a prototypical DC-DC converter was modeled as a state space dynamical system and controlled by an open-loop strategy based on Lie group theory. In this work, we shall rather introduce a closed-loop control strategy based on maximum convergence rate, study some features of the novel method, and illustrate its behavior by numerical simulations. A numerical comparison of the two methods complements the paper. The numerical comparison shows how the proposed feedback control method outperforms the static one in terms of convergence rate and resiliency against parameters mismatch. [ABSTRACT FROM AUTHOR]

We consider an optimal control problem for a dynamical system described by a Caputo fractional differential equation of order α ∈ (0 , 1) and a terminal cost functional. We prove that, under certain assumptions, the (non-smooth, in general) value functional of this problem has a property of directional differentiability of order α . As an application of this result, we propose a new method for constructing an optimal positional (feedback) control strategy, which allows us to generate ε -optimal controls for any predetermined accuracy ε > 0 . [ABSTRACT FROM AUTHOR]

Due to improper selection of gradient update direction or learning rate, SGD optimization algorithms for deep learning suffer from oscillation and slow convergence. Although Adam algorithm can adaptively adjust the update direction and learning rate at the same time, it still has the overshoot phenomenon, and hence suffers from wasting computing resources and slow convergence. In this work, the PID controller from the feedback control area is borrowed to re‐express the adaptive optimization algorithm (the Adam optimization algorithm is derived into the integral I component form) of deep learning. In order to alleviate the overshoot phenomenon and hence speed up the convergence of Adam, a complete adaptive PID optimizer (adaptive‐PID) is proposed by incorporating the proportional P and derivative D component. Extensive experiments on standard data sets verify that the proposed adaptive‐PID algorithm significantly outperforms Adam algorithm in terms of convergence rate and accuracy. [ABSTRACT FROM AUTHOR]

Visual perception can be modulated by the physiological potential for action. For instance, it was famously shown that a geographical slant appears steeper when wearing a heavy backpack than not wearing any. However, those results are not always replicated. In the present exploratory study, we test the hypothesis that the backpack weight's effect on perception relies on the ability of the cognitive system to integrate the physiological constraint's change rather than the change itself. Young adults (n = 54) wore an electrocardiogram monitor and completed a computerised task in which photographs of real geographical slants were displayed on a screen while wearing a heavy versus light backpack. The activity of the vagus nerve, as an index of physiological adaptability, was recorded as a proxy of the physiological state during the task. The participants also completed an interoception task assessing one's ability to detect his or her own heartbeat as the index of integration ability of the cognitive system. While Bayesian analyses revealed no difference in angle estimation between carrying a heavy versus light backpack, the results indicated that interoception predicted less accurate angle estimation only when wearing a heavy backpack. In contrast, there was anecdotal evidence that vagal activity changes predicted visual perception. Interoception might thus play a crucial role in the interplay between the physiological potential for action and action-related visual perception. [ABSTRACT FROM AUTHOR]

The given unstable hybrid stochastic differential equation is stabilized in the sense of pth-moment exponential stability. We achieve the results by feedback controls based on the discrete-time state and mode observations. The upper bound on the duration between two consecutive observations is obtained as well. Finally, a numerical example is given to verify the validity of the theoretical conclusions. [ABSTRACT FROM AUTHOR]

With the evolution of the aerospace industry, structures have become larger and more complex. These structures exhibit significant characteristics such as extensive flexibility, low natural frequencies, numerous modes, and minimal structural damping. Without implementing vibration control measures, the risk of premature structural fatigue failure becomes imminent. In present times, the installation of inertial actuators and control signal acquisition units typically requires independent setups, which can be cumbersome for practical engineering purposes. To address this issue, this study introduces a novel approach: an independent control unit combining a loudspeaker-based inertial actuator (LBIA) with an integrated piezoelectric ceramic sensor. This unit enables autonomous vibration control, offering the advantages of ease of use, low cost, and lightweight construction. Experimental verification was performed to assess the mechanical properties of the LBIA. Additionally, a mathematical model for the LBIA with an integrated piezoelectric ceramic sensor was developed, and its efficacy as a control unit for thin plate structure vibration control was experimentally validated, showing close agreement with numerical results. Furthermore, the LBIA's benefits as an actuator for low-frequency mode control were verified through experiments using external sensors. To further enhance control effectiveness, a mathematical model of the strain differential feedback controller based on multi-bandpass filtering velocity improvement was established and validated through experiments on the clamp–clamp thin plate structure. The experimental results demonstrate that the designed LBIA effectively reduces vibration in low-frequency bands, achieving vibration energy suppression of up to 12.3 dB and 23.6 dB for the first and second modes, respectively. Moreover, the LBIA completely suppresses the vibration of the fourth mode. Additionally, the improved control algorithm, employing bandpass filtering, enhances the effectiveness of the LBIA-integrated sensor, enabling accurate multimodal damping control of the structure's vibrations for specified modes. [ABSTRACT FROM AUTHOR]

Over the past few decades, micro liquid dispensing technology has been widely used in biology, chemistry, material and environmental sciences due to its efficacy in processing multiple samples. For practical applications, precise and effective droplet generation is very important. Despite numerous droplet generation methods, the implementation of droplet-on-demand still faces challenges concerning system complexity, precision, cost, and robustness. In this work, a novel on-demand contacting droplet generation method incorporated with model-based feedback control with an image processing unit as a sensor was proposed. By studying droplet identification using image processing techniques, the model of droplet formation was simplified. Then model-based feedback control was implemented using volumes of dispensed samples as sensing signals by tuning related parameters adaptively to resist disturbances. The proposed method was integrated and applied to a homebuilt automated micro liquid dispensing system with droplets ranging from 20 nanoliter to 200 nanoliter. The experimental results demonstrated a high degree of accuracy and precision. Additionally, the proposed system's practical utility was evaluated by analyzing mutations in genes associated with sensorineural hearing loss, verifying its effectiveness. [ABSTRACT FROM AUTHOR]

Europe needs to save energy, and lowered indoor temperature is frequently promoted as part of the solution. To facilitate this, heating control systems with feedback from indoor temperature sensors are often required to avoid thermal discomfort and achieve long-term temperature reductions. This article describes a measurement- and interview-based study on feedback control where 107 Swedish multifamily buildings were analysed. The obtained results show that buildings with lowered indoor temperatures had reduced annual heating demand by 4 kWh/m2 and a reduced indoor temperature of 0.4 °C. There were, however, significant individual differences and even buildings with increased indoor temperatures, which harmed the energy savings. Temperature fluctuation was most often significantly reduced, but the impact on heating power demand during cold weather was, on average, only 2%. An interview with different actors indicated higher energy savings, possibly due to their stock's original room temperature levels. Several interviewees also mentioned other advantages of temperature mapping. Most of the results obtained in this study were in line with several previous investigations. The study's novelty lies in the large number of investigated buildings with mature commercial heat control technology, including PI-control for adjusting supply temperature, indoor temperature sensors in almost every apartment and a parallel analysis of additional affected parameters. [ABSTRACT FROM AUTHOR]

This paper introduces robust nonlinear controller strategies for multiphase induction machines, aiming to enhance operational reliability under healthy and faulty conditions, including stator phase and converter leg openings. Due to the induction machine's inherent nonlinearities and parameter variations, a robust control is required. The study evaluates the effectiveness of the sliding mode control with linear feedback and switched gains, the fuzzy proportional integral control, and their combined application in both healthy and faulty modes. The experimental assessment involves a symmetrical six-phase induction machine in generation mode, with comparisons with a classic proportional integral controller for inner current loop regulations. Experimental results show that the fuzzy proportional integral controller presents the best performance by minimizing torque ripples during both healthy and faulty operations. [ABSTRACT FROM AUTHOR]

The feedback control system was designed to control the pipeline blockage and leakage fault. Based on the open-loop engine system, different degrees of faults were simulated, and the changes in system parameters when faults occur were analyzed. Then, the faults were injected into the engine system with feedback control, and the effects of the controller to different degrees of faults and the changes of the parameters of the electric pump with the controller were studied. The simulation results showed that under the action of the feedback control system, the deviation of the engine system parameters caused by these faults can recover to the set value within a few seconds. When the fault disappears, the system parameters can be still within the normal operating range. [ABSTRACT FROM AUTHOR]

A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly. [ABSTRACT FROM AUTHOR]

This paper investigates a discrete-time predator–prey model with predator harvesting. The stability analysis for different fixed points of the discretized model is shown briefly. In this study, different types of bifurcation and their normal forms are determined. As the prey harvesting and conversion rate of prey into predator are ecologically significant, the impact of theirs have been studied by choosing the bifurcation parameter. The system exhibits a sequence of bifurcations of codim-1 viz. Neimark–Sacker bifurcation and flip bifurcation (period-doubling) and codim-2 resonance bifurcation (1:2, 1:3 and 1:4) at a positive fixed point. For each bifurcation, by using the critical normal form coefficient method, various critical states are calculated under non-degeneracy conditions. Further, a detailed numerical simulation is presented for supporting the analytical findings. The bifurcation curves, phase plots and Maximum Lyapunov exponent (MLE) are drawn. The system exhibits a wide range of bifurcation, including periodic orbits, quasi-periodicity, resonance bifurcation and chaos. Moreover, it is shown that predator harvesting has a stabilizing effect on the dynamics of the model. The chaos that occurred in the system is reduced beyond the critical value of harvesting. The predator population goes extinct after crossing the threshold value of harvesting. This work reflects that the feasible upper bound of the harvesting rate for the species coexistence can be guaranteed. Further, a state feedback controller is employed to suppress the dense chaos in the discrete system. The control technique applied for codim-1 Neimark–Sacker bifurcation and codim-2 1:4 resonance bifurcation is instrumental to reduce the complexity in the system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyberattacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme. [ABSTRACT FROM AUTHOR]

This paper presents a quasi-static model-based control algorithm for controlling the motion of a soft robotic exo-digit with three independent actuation joints physically interacting with the human finger. A quasi-static analytical model of physical interaction between the soft exo-digit and a human finger model was developed. Then, the model was presented as a nonlinear discrete-time multiple-input multiple-output (MIMO) state-space representation for the control system design. Input–output feedback linearization was utilized and a control input was designed to linearize the input–output, where the input is the actuation pressure of an individual soft actuator, and the output is the pose of the human fingertip. The asymptotic stability of the nonlinear discrete-time system for trajectory tracking control is discussed. A soft robotic exoskeleton digit (exo-digit) and a 3D-printed human-finger model integrated with IMU sensors were used for the experimental test setup. An Arduino-based electro-pneumatic control hardware was developed to control the actuation pressure of the soft exo-digit. The effectiveness of the controller was examined through simulation studies and experimental testing for following different pose trajectories corresponding to the human finger pose during the activities of daily living. The model-based controller was able to follow the desired trajectories with a very low average root-mean-square error of 2.27 mm in the x-direction, 2.75 mm in the y-direction, and 3.90 degrees in the orientation of the human finger distal link about the z-axis.

Recent studies have identified rotational dynamics in motor cortex (MC), which many assume arise from intrinsic connections in MC. However, behavioral and neurophysiological studies suggest that MC behaves like a feedback controller where continuous sensory feedback and interactions with other brain areas contribute substantially to MC processing. We investigated these apparently conflicting theories by building recurrent neural networks that controlled a model arm and received sensory feedback from the limb. Networks were trained to counteract perturbations to the limb and to reach toward spatial targets. Network activities and sensory feedback signals to the network exhibited rotational structure even when the recurrent connections were removed. Furthermore, neural recordings in monkeys performing similar tasks also exhibited rotational structure not only in MC but also in somatosensory cortex. Our results argue that rotational structure may also reflect dynamics throughout the voluntary motor system involved in online control of motor actions.

The self-sensing technology of microactuators utilizes a smart material to concurrently actuate and sense in a closed-loop control system. This work aimed to develop a position feedback-control system of nickel electrothermal microactuators using a resistivity self-sensing technique. The system utilizes the change in heating/sensing elements’ resistance, due to the Joule heat, as the control parameter. Using this technique, the heating/sensing elements would concurrently sense and actuate in a closed loop control making the structures of microactuators simple. From a series of experiments, the proposed self-sensing feedback control system was successfully demonstrated. The tip’s displacement error was smaller than 3 µm out of the displacement span of 60 µm. In addition, the system was less sensitive to the abrupt temperature change in surroundings as it was able to displace the microactuator’s tip back to the desired position within 5 s, which was much faster than a feed-forward control system.

There is an unbalanced problem in the traditional laneway excavation process for coal mining because the laneway excavation and support are at the same position in space but they are separated in time, consequently leading to problems of low efficiency in laneway excavation. To overcome these problems, an advanced dual-arm tunneling robotic system for a coal mine is developed that can achieve the synchronous operation of excavation and the permanent support of laneways to efficiently complete excavation tasks for large-sized cross-section laneways. A dual-arm cutting robot (DACR) has an important influence on the forming quality and excavation efficiency of large-sized cross-section laneways. As a result, the relative kinematics, workspace, and control of dual-arm cutting robots are investigated in this research. First, a relative kinematic model of the DACR is established, and a closed-loop control strategy for the robot is proposed based on the relative kinematics. Second, an associated workspace (AW) for the DACR is presented and generated, which can provide a reference for the cutting trajectory planning of a DACR. Finally, the relative kinematics, closed-loop kinematic controller, and associated workspace generation algorithm are verified through simulation results.

This study examines the design and long-term implementation of a feedforward and feedback (FF–FB) mechanism in a control system for cement sulfates applied to all types of cement produced in two mills at a production facility. We compared the results with those of a previous controller (SC) that operated in the same unit. The Shewhart charts of the annual SO3 mean values and the nonparametric Mann–Whitney test demonstrate that, for the FF–FB controller, the mean values more effectively approach the SO3 target than the older controller in two out of the three cement types. The s-charts for the annual standard deviation of all cement types and mills indicate that the ratio of the central lines of FF–FB to SC ranges from 0.39 to 0.59, representing a significant improvement. The application of the error propagation technique validates and explains these improvements. The effectiveness of the installed system is due to two main factors. The feedforward (FF) component tracks the set point of SO3 when the mill begins grinding a different type of cement, while the feedback (FB) component effectively attenuates the fluctuations in the sulfates of the raw materials.

The uncertainty in the secondary path of active noise control (ANC) headphones affects the waterbed effect and stability of the feedback system. This study focuses on the uncertainty of the secondary path when real users wear headphones and proposes a new uncertainty constraint based on the measured results of the secondary path transfer function under different wearing conditions of a dummy head and limited subjects. This constraint and a cascaded second-order infinite impulse response filter with fixed coefficients are used to formulate a control strategic function, which is optimized using the Improved Grey Wolf Optimizer (IGWO) algorithm to obtain the optimal controller with better noise reduction performance. The proposed method and simulation model are validated based on the experimental test results. The results demonstrate that the safety factor and waterbed suppressing factor contained in the proposed uncertainty constraint ensure more stable noise reduction and effective suppression of the waterbed effect for new subjects without a priori data.

Spinal cord injury (SCI) can cause paralysis of trunk and hip musculature that negatively impacts seated balance and ability to lean away from an upright posture and interact fully with the environment. Constant levels of electrical stimulation of peripheral nerves can activate typically paralyzed muscles and aid in maintaining a single upright seated posture. However, in the absence of a feedback controller, such seated postures and leaning motions are inherently unstable and unable to respond to perturbations. Three individuals with motor complete SCI who had previously received a neuroprosthesis capable of activating the hip and trunk musculature volunteered for this study. Subject-specific muscle synergies were identified through system identification of the lumbar moments produced via neural stimulation. Synergy-based calculations determined the real-time stimulation parameters required to assume leaning postures. When combined with a proportional, integral, derivative (PID) feedback controller and an accelerometer to infer trunk orientation, all individuals were able to assume non-erect postures of 30–40° flexion and 15° lateral bending. Leaning postures increased forward reaching capabilities by 10.2, 46.7, and 16 cm respectively for each subject when compared with no stimulation. Additionally, the leaning controllers were able to resist perturbations of up to 90 N, and all subjects perceived the leaning postures as moderately to very stable. Implementation of leaning controllers for neuroprostheses have the potential of expanding workspaces, increasing independence, and facilitating activities of daily living for individuals with paralysis.

The rate of profit is a key element for understanding the movement of capitalism such as technological progress and economic crisis. Even though capitalists seek larger profit rates, there exists a tendency of stagnating or falling profit rates. According to Marx, the rate of profit would tend to decline in the long run as a result of technological progress, termed the law of tendential fall in the profit rate. This article introduces a novel approach based on the discrete-time feedback control mechanism to elucidate Marx’s theory. Specifically, this study presents a mechanism and conditions to show how the effort to maximize the profit rate, implemented by designing an “appropriate” control law under the sampling of fiscal years, eventually leads to the gradual decrease in the rate of profit in the long run.

By using linear entropy, a discrete quantum logistic chaotic map is introduced and the dynamical evolution of the quantum radiation field interacting with the matter is studied by changing the independent parameters. Its typical effect is the chaotic property of the quantum optics and a quantum classical correspondence is obtained, and the chaos and the regular structure of phase space can be better revealed by using the coherence dynamics of phase space. In addition, an approach for fast adaptive synchronization of the discrete quantum maps is proposed. Results validate the effectiveness of the proposed scheme.

By taking into account third-order dispersion effects in the presence of feedback, we investigate the stability and nonlinear dynamic movements of waves created in microcavities and fiber cavities from numerical simulations of the extended Lugiato–Lefever equation. The current analysis emphasizes that third-order scattering, feedback strength, and feedback local and global components allow for the numerical observation of dissipative bound states of solitons and chaos with extended and antisymmetric interaction domains. In this regard, we demonstrate how the symmetry of the localized structural interactions is broken by the radiation that results from third-order dispersion.