Open-loop Control Research Articles

An open-loop control algorithm for improved tracking in a heliostat

The growing energy demand and its relation to climate change have driven the search for sustainable alternatives, such as concentrated solar energy. In this context, heliostats play a crucial role by reflecting and concentrating solar light onto a receiver. However, traditional control approaches based on geographical data have limitations. This study introduces an autonomous control system for heliostats that eliminates the need for preloaded geographical data. The approach is based on communication between the heliostat and the solar tracker, with two configuration modes: map calibration and automatic. Centralized and autonomous heliostats are distinguished, with the latter being the focus of the study. Autonomous heliostats have their own control system and can make decisions regarding positioning and safety. The methodology involves a mathematical algorithm that calculates the optimal rotation and tilt of the heliostat to redirect light toward a target. Simulation and physical prototype testing validate a remarkable consistency between simulated and experimental data. A key result is the surprising similarity of 97.9% between the obtained data, validating the algorithm's effectiveness. This study provides a robust approach for designing autonomous heliostat control systems, integrating simulation and experimentation. These results support the algorithm's precision and ability to direct solar radiation effectively. Expanding towards autonomous control and complete heliostat system evaluation facilitates the path toward more efficient and sustainable concentrated solar energy.

Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media

Metasurface-programmable radio environments are considered a key ingredient of next-generation wireless networks. Yet, identifying a metasurface configuration that yields a desired wireless functionality in an unknown complex environment was so far only achieved with closed-loop iterative feedback schemes. Here, we introduce open-loop wave control in metasurface-programmable complex media by estimating the parameters of a compact physics-based forward model. Our experiments demonstrate orders-of-magnitude advantages over deep-learning-based digital-twin benchmarks in terms of accuracy, compactness and required calibration examples. Strikingly, our parameter estimation also works without phase information and without providing measurements for all considered scattering coefficients. These unique generalization capabilities of our pure-physics model unlock unforeseen and previously inaccessible frugal wave control protocols that significantly alleviate the measurement complexity. For instance, we achieve coherent wave control (focusing or perfect absorption) and phase-shift-keying backscatter communications in metasurface-programmable complex media with intensity-only measurements. Our approach is also directly relevant to dynamic metasurface antennas, microwave-based signal processors and emerging in situ reconfigurable nanophotonic, optical and room-acoustical systems.

Field oriented control driver development based on BTS7960 for physiotherapy robot implementation

In conjunction with sustainable development goal 3 (SDG 3), it is important to develop a national electrical component for physiotherapy robot development. This study aimed to develop an open-loop field-oriented control (FOC) driver utilizing BTS7960. The driver utilized three BTS7960s that produce sinewave with variable angular frequency (ω). The research then compared the open-loop FOC driver with electronics speed controller (ESC) performance to drive a brushless DC (BLDC) motor with an initial rotation per minute (RPM) of 400, 500, and 600. The main observation was RPM reduction when the BLDC motor was subjected to loads of 20, 35, 50, 65, and 80 gr. The result showed that the open-loop FOC driver performed better, especially on an 80 gr load. For an initial RPM of 600, the RPM reduced to 100 when controlled with an open-loop FOC driver, but lesser when controlled using ESC. The open-loop FOC driver produces higher torque on the BLDC motor so it could rotate with less reduction compared to ESC, which is evident. The open-loop FOC driver can be easily developed using BTS7960 with a settling time of 4 seconds. However future studies should still consider close-loop FOC drivers to achieve higher torque performance and faster transient response for physiotherapy robot applications.

A Untethered Magnetic Micro-Robot for Local Therapeutic Delivery for Neurosurgical Oncology

INTRODUCTION: Microrobots designed for biomedical applications have garnered significant research interest, offering advantages in drug delivery, microsurgery, and biopsies. Magnetic fields enabled by electromagnetic coils permit untethered nonlinear movement of these tiny robots within the brain on the surface, the cerebrospinal fluid, and parenchyma. Microdrillers (either individually or in swarms) are a promising tool for microsurgery, capable of drilling through viscoelastic media (brain tissue). However, challenges remain in scaling down the robot size and exploring diverse applications. METHODS: Parallelizable (batch) microfabrication involved 3D printing via two-photon lithography. The pH-sensitive hydrogel was synthesized through UV-initiated radical polymerization mixed with a tracer (fluorescein sodium salt). Imaging via photon-counting CT was performed for microbot tracking in preclinical models including hydrogel phantoms, large animal cadaveric fresh brain tissue, and human cadaveric tissue. RESULTS: Microbot speeds in various tissues were characterized with speeds up to 800 um/sec over magnetic field amplitudes of 5 to 55 mT while performing complex nonlinear trajectories via open-loop surgeon control via surgeon. Targeted hydrogel delivery of fluorescein label/nanoparticle drug over a pH range of 6.2 (tumor tissue) and 7.8 (normal tissue) over a time interval of 50 s is demonstrated as proof of concept with a rate of 2.4 times faster in acidic conditions. Lastly, we show state-of-the-art micromillmetric resolution for real time imaging via photon-counting spectral CT for implementation of closed loop control. CONCLUSIONS: A novel minimally invasive microrobotic platform technology capable of targeted local drug delivery in brain parenchyma is demonstrated.

Automatic Re-tuning of Poor-Performing PI-based Control Systems

The goal of the work is to create a new method for automatic re-tuning of PI controllers. It is achieved by solving the following problems. The first problem is to develop a method to identify a FOPDT estimation model by analyzing the dynamics of a control loop with a PI controller. The second problem is to demonstrate that the use of the estimated model allows to obtain better processes in control systems with PI controllers by comparing the resulting FOPDT model with a number of reduced models. The third problem is to develop a five-stage algorithm for automatic re-tuning of PI controllers. The fourth problem is to verify the software implementation of the developed algorithm. The most significant result was that the basis for estimating the FOPDT model in a loop with a Ziegler-Nichols tuned PI controller was the estimation the ratio of the delay to the time constant of the FOPDT model based on an assessment of the process overshoot. When the real control plant dynamics did not match with the dynamics of the FOPDT model this way was found effective for finding the optimal tuning of the PI controller. The significance of the results obtained was a structural robustness in case of estimated FOPDT model usage. The effectiveness of the procedure has been demonstrated on both linear and nonlinear models. The developed procedure is proposed to be used to automate the procedure of re-tuning SISO control systems when the control loop performance degradation has been detected.

An adaptive fluid-solid coupling time step control algorithm for unsteady conjugate heat transfer

Unsteady simulation with conjugate heat transfer has to tackle the stiffness issue that originates from the wide disparate time scales between fluid and solid heat transfer. In the loosely coupled framework, challenges remain in determining the optimal coupling time step between the fluid and solid solvers, in terms of efficiency and accuracy. This study formulates a correlation for the coupling error, together with the Proportional-Integral-Derivative (PID) control method, to propose an adaptive fluid-solid coupling time step algorithm, which dynamically adjusts the coupling time step such that the computational efficiency can be improved without sacrificing accuracy. The proposed algorithm has been tested in a 1D conjugate heat transfer application with typical operating conditions of a real engine, and the performance of different controllers (I, PI, PID) has been analyzed and compared. Results show that with the closed-loop control, all controllers can ensure the error control below the user specified tolerance at the cost of reducing efficiency. Meanwhile, with the open-loop control which is of more interest to practical applications, controllers suffer from instability issues when a conventional algorithm based on integration error is employed. The proposed coupling-error-based algorithm successfully tackles the instability issues. Compared with the baseline algorithm of the constant coupling time step, the proposed algorithm can reduce approximately 40%–90% computational cost for the 1D cases considered.

Counteracting Bleeding in Centrifugal Partition Chromatography: Redosing of the Stationary Phase

Centrifugal Partition Chromatography is a type of Liquid-Liquid Chromatography that offers several advantages compared to Liquid Chromatography. Two immiscible liquids are utilized, and one phase has to be immobilized to implement chromatographic separation. This is performed with the help of centrifugal force. As this immobilization is not ideal, the stationary phase continuously leaks out of the apparatus (so-called bleeding). We measured the stationary phase’s loss precisely and implemented a controller to compensate for it during operation. This innovative mode of operation is called redosing of the stationary phase and prolongs the experimental runtime significantly. In a first step, we implemented an open-loop controller, which was capable of counteracting bleeding but could not dial to a given setpoint precisely. Therefore, a closed-loop controller with a moving frame shifting factor was programmed. This controller reached and maintained setpoints with high accuracy. The last experimental step was to check for boundaries of this new degree of freedom. In addition, we highlighted the accompanying hydrodynamics during redosing with the help of Computational Fluid Dynamics. We were able to show the influence of different volumes of the redosed stationary phase on the flow regime.

An energy-based model of soft robot grippers realizing design and prediction of multistable configuration under open loop control

An energy-based model of soft robot grippers realizing design and prediction of multistable configuration under open loop control

Offline supervised learning v.s. online direct policy optimization: A comparative study and a unified training paradigm for neural network-based optimal feedback control

This work is concerned with solving neural network-based feedback controllers efficiently for optimal control problems. We first conduct a comparative study of two prevalent approaches: offline supervised learning and online direct policy optimization. Albeit the training part of the supervised learning approach is relatively easy, the success of the method heavily depends on the optimal control dataset generated by open-loop optimal control solvers. In contrast, direct policy optimization turns the optimal control problem into an optimization problem directly without any requirement of pre-computing, but the dynamics-related objective can be hard to optimize when the problem is complicated. Our results underscore the superiority of offline supervised learning in terms of both optimality and training time. To overcome the main challenges, dataset and optimization, in the two approaches respectively, we complement them and propose the Pre-train and Fine-tune strategy as a unified training paradigm for optimal feedback control, which further improves the performance and robustness significantly. Our code is accessible at https://github.com/yzhao98/DeepOptimalControl.

Detection of poor controller tuning with Gramian Angular Field (GAF) and StackAutoencoder (SAE)

Efficient control loop performance is pivotal in process industries to ensure optimal production, maintain product quality, and adhere to regulatory standards. Poorly tuned controllers can disrupt these objectives, necessitating accurate detection methods. This paper introduces a novel approach for detecting poor controller tuning through advanced techniques: the Gramian Angular Field (GAF) and Stack Auto-Encoder (SAE). Unlike manual methods, this automated system promptly identifies poorly tuned controllers, offering real-time monitoring and timely alerts to operators. The proposed methodology is substantiated through two case studies: the ISDB dataset and the pulp and paper dataset. The outcomes illustrate that the proposed approach correctly determines the appropriate outcome for the majority of the analyzed control loops across diverse industries.

Power control in LTE based on heuristic game theory for interference management

In the conventional LTE homogeneous network, sufficient transmit power of user equipment (UE) is determined by open-loop power control (OL-PC) and closed-loop power control (CL-PC) schemes. However, in a Het-Net environment, setting the UE’s transmit power requires delicate responsiveness to handle the severe and complicated uplink interference. In this paper, an interference-aware uplink power control mechanism based on Heuristic game theory approach is proposed for devices coexisting in a heterogeneous wireless network. Various wireless constraints like channel response, path loss, fading, shadowing, interference and metrics like SNR, SINR, throughput and bit rates are considered. Uplink power is controlled by suitably selecting the penalization factor (β) based on a simple Heuristic game theory approach considering the possible wireless constraints of each user depending on its location in the cell under consideration. The algorithm is framed in such a way to reduce inter-cell interference, limit transmit power, enhance bit rates and throughput of users. A significant improvement of 5.2% in the user coverage/distribution is achieved as a result of interference management compared to conventional power control scheme and power control with convex pricing.

High authenticity steering feel control strategy for Steer-by-Wire system based on terminal sliding mode rack force observer

This article proposes a high authenticity steering feel control strategy for Steer-by-Wire (SBW) system based on terminal sliding mode rack force observer, in response to the issue of how to design the steering feel of the SBW system to reflect road conditions. Firstly, a terminal sliding mode rack force observer is designed to achieve real-time and accurate estimation of steering system rack force. Then, based on the vehicle motion state, design the feedback characteristic curve of the rack force and the compensation torque of the handwheel to obtain the expected steering feel, and use the automatic disturbance rejection controller (ADRC) method to control the voltage of the handwheel motor. In simulation testing, a SBW open loop control system model is established to verify the performance of the designed rack force observer. The objective evaluation indicators are used to verify that the designed feedback method can intuitively adjust and meet the driver's steering feel needs, and the impact of various compensation torques on the evaluation indicators is analyzed. Finally, the results of actual vehicle experiments indicate that the designed method can provide suitable steering feel, verifying the feasibility of the design technology.

Design of 2DOF control system fused with artificial intelligence for power enhancement and mitigation of degradation in fuel cell systems

The commercialization of Fuel Cell Systems (FCSs) faces a key obstacle in the form of limited cell lifespan and resultant cell degradation. This paper introduces a new approach, leveraging an artificial intelligence-based 2DOF control system to regulate the Oxygen Excess Ratio (OER) with two main goals: mitigating cell degradation due to oxygen starvation and optimizing net power output. The proposed control system incorporates a data-driven feedforward controller in conjunction with a feedback controller, facilitating the tracking of desired OER values generated by a data-driven reference generator. We develop fuzzy models and neural networks as the reference generator and feedforward controller to capture the complex FCS behavior by processing the stack current w/wo the temperature of FCS (i.e. Single input or Double input models). By exploring the effects of the structural settings of the models, this study provides a comprehensive understanding of their impact on the representation performance of the FCS characteristics. Although the fitting performances of all models are quite satisfactory, their actual performance gain is evaluated on a realistic FCS model at various operation points. The findings and comparative analysis emphasize the efficacy of incorporating stack temperature in fuzzy-model-based 2DOF control systems, showcasing their potential to maximize net power output through enhanced OER control loop performance while also extending the lifespan of FCSs, as confirmed by results from a developed degradation model.

New Speed Control Scheme for a Three-Phase Induction Machines - (3~IM) Based on Sine Duty Cycle Modulation (SDCM)

This paper proposes a new control scheme for three-phase induction machines based on the sinusoidal duty cycle modulation control strategy combined with V/f control. This technique allows efficient open-loop control of inverter switches. The proposed diagram shows the main characteristics:1 0.1   ,0 50 ,Hzf 21.44 ,base KHzf  2 ,12ref V Vu  . In addition, it guarantees optimum operation of the inverter with the torque and speed parameters of the three-phase induction machine complying with current requirements:10rC Nmmax 6,5A/50Hz/ THD=1,2%

Research on Adaptive Cycle Engine Mode Transition Control Method

Mode transition is an important dynamic process of an adaptive cycle engine (ACE). In order to obtain a smooth mode transition process, the closed-loop controller is designed based on the strong robust augmented linear quadric regulator (ALQR) method, and with the objective of minimizing the thrust fluctuation in the process of mode transition, an open-loop geometrical mechanism control schedules optimization method based on Bézier curves is proposed, so that the closed-loop control and the open-loop control can work in coordination. The simulation results at the subsonic cruise operating point and supersonic cruise operating point show that based on the optimized open-loop geometrical mechanism control schedules and the designed closed-loop ALQR control system, the ACE achieves fast and smooth geometrical mechanisms and engine output transition during the mode transition process with a maximum thrust fluctuation of 2.58%, which is much smaller than that of the traditional linear variation geometric mechanisms with a maximum 4.64% thrust fluctuation, which verifies the effectiveness of the proposed control method.

Investigation of directional discrimination in the nociceptive system using temperature-controlled laser stimuli.

Cutaneous laser stimulation has commonly been employed to investigate the thermal properties of the nociceptive system. The aim of this study was to investigate how a temperature-controlled laser system improves the assessment of directional discrimination in the nociceptive system. In total, twenty healthy volunteers participated in this study. To determine the directional discrimination threshold (stimulation length 50% correct, expressed in mm), thermal stimuli were delivered using a diode laser and the laser beam was perpendicularly displaced across the skin to give a linear stimulation in four different directions (distal, proximal, lateral and medial) and displacement lengths (3 for lateral-medial and 5 for distal-proximal). Two temperature control modes were used in the stimulation system, open-loop and closed-loop control. The subjects had to report the perceived stimulus direction, the degree of certainty regarding the perceived direction and the intensity of the perceived stimulus (0-10 numerical rating scale, 3: pain threshold). During closed-loop control, the orientation of stimuli was discriminated significantly more accurately than during open-loop control. During closed-loop control, the directional discrimination threshold was 31.9 and 26.1 mm for distal-proximal and lateral-medial directed stimuli, respectively. A numerical rating scale was significantly higher for the lateral/medial directions. Moreover, the variability of the discrimination threshold is reduced in the closed-loop control system. The findings show that discrimination ability is better in the lateral-medial directions compared to the distal-proximal directions. This study indicates that using a system enabling closed-loop temperature control, allows more robust probing of the temporo-spatial mechanisms in the nociceptive system. This study shows that a newly developed temperature-controlled laser stimulation system enhances the possibilities to investigate the nociceptive temporo-spatial integration, as shown by a less variable directional discrimination threshold. The results also show that different orthogonal directions are discriminated differently. This new method allows a better investigation of the combined temporal and spatial mechanisms in the nociceptive system.

Switching Converters Dynamics Considering Non-Ideality of the Error Amplifier within the Analogue Control System

The paper discusses a pulse voltage converter with a high switching frequency of a switch with an analog control system capable of providing the required conversion frequencies. The pulsed voltage converter under study has a control system with a proportional-integral regulator, implemented on the basis of a general-purpose operational amplifier. Operational amplifiers with such parameters are widely used as part of modern control microcircuits for pulse-width converters. In this work, the influence of the technological spread of the gain of the operational amplifier on the dynamics of the converter is studied. The studies were carried out both using the developed nonlinear dynamic model of the system, and using a small-signal open-loop dynamic model. A technique has been developed for selecting the parameters of the controller, taking into account the technological spread of the gain of the operational amplifier based on a nonlinear dynamic model. An analysis of the results obtained using a nonlinear dynamic model showed a significant influence of the specified spread on the dynamics of the system, even when the cutoff frequency of the open-loop control system is significantly removed from the frequency of the high-frequency pole of the operational amplifier. This must be taken into account when designing pulse voltage converters with analog control systems, namely, when choosing the parameters of regulators. It is shown that with the optimal values of the controller, selected according to the proposed method, the effect of technological gain spread on the frequency characteristics of an open circuit in the low-mid frequency regions is minimal, which indicates the effectiveness of the method.

Forced synchronization of self-excited chaotic thermoacoustic oscillations

We experimentally investigate the forced synchronization of a self-excited chaotic thermoacoustic oscillator with two natural frequencies, $f_1$ and $f_2$ . On increasing the forcing amplitude, $\epsilon _f$ , at a fixed forcing frequency, $f_f$ , we find two different types of synchronization: (i) $f_f/f_1 = 1:1$ or $2:1$ chaos-destroying synchronization (CDS), and (ii) phase synchronization of chaos (PSC). En route to $1:1$ CDS, the system transitions from an unforced chaotic state ( ${\rm {CH}}_{1,2}$ ) to a forced chaotic state ( ${\rm {CH}}_{1,2,f}$ ), then to a two-frequency quasiperiodic state where chaos is destroyed ( $\mathbb {T}^2_{2,f}$ ), and finally to a phase-locked period-1 state ( ${\rm {P1}}_f$ ). The route to $2:1$ CDS is similar, but the quasiperiodic state hosts a doubled torus $(2\mathbb {T}^2_{2,f})$ that transforms into a phase-locked period-2 orbit $({\rm {P2}}_f)$ when CDS occurs. En route to PSC, the system transitions to a forced chaotic state ( ${\rm {CH}}_{1,2,f}$ ) followed by a phase-locked chaotic state, where $f_1$ , $f_2$ and $f_f$ still coexist but their phase difference remains bounded. We find that the maximum reduction in thermoacoustic amplitude occurs near the onset of CDS, and that the critical $\epsilon _f$ required for the onset of CDS does not vary significantly with $f_f$ . We then use two unidirectionally coupled Anishchenko–Astakhov oscillators to phenomenologically model the experimental synchronization dynamics, including (i) the route to $1:1$ CDS, (ii) various phase dynamics, such as phase drifting, slipping and locking, and (iii) the thermoacoustic amplitude variations in the $f_f/f_1$ – $\epsilon _f$ plane. This study extends the applicability of open-loop control further to a chaotic thermoacoustic system, demonstrating (i) the feasibility of using an existing actuation strategy to weaken aperiodic thermoacoustic oscillations, and (ii) the possibility of developing new active suppression strategies based on both established and emerging methods of chaos control.

Concatenated open-loop control for higher-order photon polarization qubit decoherence

Concatenated open-loop control for higher-order photon polarization qubit decoherence

Optimal social distancing in epidemic control: cost prioritization, adherence and insights into preparedness principles

The COVID-19 pandemic experience has highlighted the importance of developing general control principles to inform future pandemic preparedness based on the tension between the different control options, ranging from elimination to mitigation, and related costs. Similarly, during the COVID-19 pandemic, social distancing has been confirmed to be the critical response tool until vaccines become available. Open-loop optimal control of a transmission model for COVID-19 in one of its most aggressive outbreaks is used to identify the best social distancing policies aimed at balancing the direct epidemiological costs of a threatening epidemic with its indirect (i.e., societal level) costs arising from enduring control measures. In particular, we analyse how optimal social distancing varies according to three key policy factors, namely, the degree of prioritization of indirect costs, the adherence to control measures, and the timeliness of intervention. As the prioritization of indirect costs increases, (i) the corresponding optimal distancing policy suddenly switches from elimination to suppression and, finally, to mitigation; (ii) the “effective” mitigation region—where hospitals’ overwhelming is prevented—is dramatically narrow and shows multiple control waves; and (iii) a delicate balance emerges, whereby low adherence and lack of timeliness inevitably force ineffective mitigation as the only accessible policy option. The present results show the importance of open-loop optimal control, which is traditionally absent in public health preparedness, for studying the suppression–mitigation trade-off and supplying robust preparedness guidelines.