Time Domain Performance Research Articles

A robust proportional filtered integral controller based on backpropagation neural network

This paper introduces a novel design of a proportional filtered-integral (P-FI) controller whose parameters are auto-tuned using the backpropagation neural networks (BPNN) algorithm. The proposed controller is designed to address the main challenges posed by a class of complex systems characterized by uncertain high-gain and pure integrator dynamics, including high-frequency noise amplification and poor robustness against parameter variations. Designing such a controller involves three main steps: First, a proportional–integral–derivative (PID) controller is designed, with its parameters auto-tuned online using the BPNN algorithm, resulting in the primary (BPNN-PID) controller. Second, the obtained parameters of the previous controller are utilized to compute those of a low-pass filter offline. This filter is then cascaded with the integral parts of a PID controller, forming a P-FI controller structure. This configuration introduces a phase lead within a specific frequency range without amplifying high-frequency noise, overcoming the primary disadvantage of the derivative term. Finally, the parameters of the resulting P-FI controller are again auto-tuned online using the BPNN algorithm, resulting in the final robust (BPNN-P-FI) controller. This novel controller structure and its parameters tuning procedure, based on a two-stage BPNN learning approach, constitute the main contributions of this paper. Simulation results demonstrate the superiority of the proposed controller in terms of time-domain performance, sensor noise attenuation, and closed-loop robustness compared to those obtained with the BPNN-PID and optimally tuned PID controllers.

A comparative study on PI-PD controller design using stability region centroid methods for unstable, integrating and resonant systems with time delay

In this paper, controller tuning methods based on stability region centroid methods reported in the literature are used to design PI-PD controllers for unstable, integrating and resonant systems with time delay. By analyzing the stability boundary locus (SBL) for the PD controller, which is utilized in the inner loop of this structure, the controller parameters are obtained using three methods which are the Weighted Geometric Center (WGC), Centroid of Convex Stability Region (CCSR), and Stability Triangle Approach (STA). These techniques were applied analytically, step by step. For the closed loop transfer function obtained in the inner loop of the controlled system, these three methods were utilized to design the PI controller in the outer loop, individually. Unit step responses of the controlled system, using PI-PD gains determined by each method, have been obtained. Furthermore, a disturbance of a certain time and amplitude was added to the systems to test the disturbance rejection behavior and the robustness performance of the methods. Perturbed responses were obtained through changing the model parameters at a certain rate. Time domain performance metrics were analyzed to compare the responses. The simulations were evaluated using settling time, rise time, and percentage overshoot as the assessment criteria. As a result of this study, the effectiveness of three methods, namely WGC, CCSR, and STA, in controller design for unstable, integrating, and resonant time-delay systems has been demonstrated. In addition, a comparison of time domain performance metrics is presented for the nominal and perturbed systems. Based on these comparisons, it is concluded that the methods outperform each other only in some time response performance measures. The presented results showed the advantages of these methods over each other in terms of some performance criteria. The contribution of this study to the literature is the comparative analysis of these three analytical methods.

Dynamic output feedback control strategy for a satellite orbital model within negative-imaginary systems theory framework

This article presents the synthesis of a dynamic output feedback controller for a satellite orbital system confronted with uncertainties. The investigated method transforms the closed-loop system, synthesized by the controller, into an α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}-strictly negative-imaginary system. It utilizes the DC-loop gain condition associated with negative-imaginary systems theory to demonstrate robust stability of the satellite orbital system in the presence of uncertainties. Furthermore, the synthesized negative-imaginary closed-loop system exhibits notable time-domain performance. The numerical simulation outcomes presented in this article validate the investigated synthesis method.

Design of an artificial neural network and proportional‐integral‐derivative controller using particle swarm optimization for Boeing 747‐400 aircraft pitch control

AbstractThis paper presents the design of an artificial neural network (ANN) and proportional integral derivative (PID) controller using particle swarm optimization (PSO) for Boeing 747‐400 aircraft pitch control (APC). The combinations of disturbance, open loop unstable and nonlinear dynamics are major problems in a Boeing 747‐400 commercial aircraft. This paper investigates the control mechanism of pitch angle control of Boeing 747‐400 with small disturbance theory linearization methods and ANN based non‐linear controllers. A PID controller is tuned by PSO, whereas the PID is tuned by graphical user interface (GUI) when compared with an ANN controller. The controller for this system was designed using an ANN controller and PID tuned using a recent optimization technique such as the PSO method with integral square error (ISE) as an objective function. A comparative study of the time domain performances of the pitch control of the Boeing 747‐400 commercial aircraft was presented. The ANN controller outperformed the PID‐PSO and PID‐GUI controllers in terms of system performance, including rising time (tr), settling time (ts), percentage overshoot (percent OS), and steady state error, across various elevator deflection angles. Basically, the percentage overshoot and steady state error were 0% and 0 respectively, indicating that the ANN controller achieved an improvement of 100%. Various parameters were compared with the PID‐GUI, PID‐PSO, and ANN controllers for pitch control of the Boeing 747‐400 air craft. The ANN controller architecture comprises of two input neurons, two hidden layer neurons, and one output layer neuron. The simulation was performed using Matlab/Simulink. The results show that the PID‐PSO controller was improved by the ANN controller and the performance specifications of the aircraft obtained by the ANN controller were satisfactory.

New PID parameter tuning based on improved dung beetle optimization algorithm

AbstractIn this paper, a proportional‐integral‐derivative (PID) controller parameter optimization method based on the improved dung beetle optimization (IDBO) algorithm is proposed, which improves the balance between the global exploration and local exploitation capabilities of the dung beetle optimization (DBO) and significantly enhances the convergence speed and optimization accuracy. Initially, the dung beetle population is initialized using piecewise linear chaotic map (PWLCM) chaotic mapping in order to increase its variety and the DBO algorithm's capacity for global exploration. Furthermore, adaptive weighting in the DBO algorithm is now balanced between the capabilities of local exploitation and global exploration with the addition of adaptive weights. After that, in order to improve the DBO algorithm's capacity for local exploitation, a triangle wandering strategy is included during the dung beetle reproductive phase. Finally, using both Lévy flying wandering and greedy strategy (GS) together make it easier to take advantage of opportunities in both local and global areas. The outcomes of the traditional benchmark function test demonstrate a significant improvement in both convergence speed and optimization accuracy when the particle swarm optimization (PSO), DBO, grey wolf optimization (GWO), and sparrow search algorithm (SSA) algorithms are compared. The performance index function incorporates an overshooting penalty term to prevent the overshooting phenomenon in the control system. Simulation experiments are carried out for the DC motor control system, and the time domain performance, frequency domain performance, and robustness performance of the closed‐loop control system with ZN‐PID, Lambda‐PID, PSO‐PID, and IDBO‐PID rectified PID controller parameters are comparatively analyzed, which verifies the validity and practicability of the IDBO algorithm.

A Comparative Analysis of Sliding Mode and Fuzzy Sliding Mode Controllers for Climate Control Application of a Greenhouse Flower Garden

This paper describes a comparative performance analysis of sliding mode and fuzzy sliding mode controllers for climate control application of a greenhouse flower garden. Various internal and external climate related factors affect the overall growth and health of flowers that needs robust controllers to control the humidity and temperature of the greenhouse flower garden. Review of related works show that for non-linear systems, sliding mode controllers can provide robust performance even though chattering is a major drawback of the controller. A number of approaches are used to solve the chattering problem of sliding mode controllers such as hybrid uses of other controllers along with sliding mode controller. In this paper, sliding mode controller and fuzzy sliding mode controllers are designed and implemented for the specified control application based on the linearized and decoupled model of the system. The performance evaluation has been done for the control problems of reference tracking and disturbance rejection with time domain performance measures of percentage overshoot, settling time and rise time. Accordingly, the overall system has been implemented in MATLAB/Simulink and the simulations for the control problems have been done. Thus, FSMC has got rise time of 5.89min, 10.59min settling time and almost negligible percentage overshoot for indoor temperature at 27°C and humidity at 22g/m3. And for humidity control, the FSMC has got 5.44min settling time and nearly zero percentage overshoot for set point tracking problem. For the disturbance of solar radiation, decrease in outside temperature and fixed set point of 27°C and humidity of 22g/m3, FSMC outperforms SMC. In summary, both quantitative and qualitative results analysis results reveal that fuzzy sliding mode controller (FSMC) outperforms sliding mode controller (SMC) for the indoor temperature and humidity control tasks of both set point tracking and disturbance rejection problems.

Enhancing Mechanical Safety in Suspension Systems: Harnessing Control Lyapunov and Barrier Functions for Nonlinear Quarter Car Model via Quadratic Programs

Limiting the suspension stroke in vehicles holds critical and conceivable benefits. It is crucial for the safety, stability, ride comfort, and overall performance of the vehicle. Furthermore, it improves the reliability of suspension components and maintains consistent handling during regular and rough driving conditions. Hence, the design of a safety-critical controller to limit the suspension stroke for active suspension systems is of high importance. In this study, we employed a quarter-car model that incorporates a suspension spring with cubic nonlinearity. The proposed safety-critical controller is the control Lyapunov function–control barrier function–quadratic programming (CLF-CBF-QP). Initially, we designed the reference controller as a linear quadratic regulator (LQR) controller based on the linearized quarter-car model. The reference state-feedback LQR controller simplified the design of the control Lyapunov function. Consequently, from the nonlinear model, we construct a simple control Lyapunov function that relies only on the sprung mass velocity to have a relative degree of one. The CLF intends to improve the performance by considering the nonlinearity and via online optimization. We then formulate the control barrier function to restrict the suspension stroke from breaching its limits. To assess the effectiveness of the proposed controller, we present two challenging road inputs for the nonlinear quarter-car model when employing CLF-CBF-QP and LQR controllers. The CLF-CBF-QP findings surpassed the LQR controller in terms of safety and performance. This study highlights the immense potential of CLF-CBF-QP for suspension systems, improving the time-domain performance, limiting the suspension stroke, and guaranteeing safety.

Centralized model matching integer/fractional-order controller design for multivariable processes with real-time validation

This paper proposes a novel approach to design a centralized model matching integer/fractional-order (FO) controller for multivariable processes. As a first step, for a linear time-delay process, a desired closed-loop reference model is formulated with the inclusion of a linear quadratic regulator with integral controller. The reference model is formulated with the objective of embodying the desired closed-loop specifications. The second step involves equating the closed-loop system with the reference model, leading to a synthesis equation that yields a higher-order controller. In the third step, the lower-order approximant of the controller is obtained by matching a set of approximate generalized time moments/approximate generalized Markov parameters of the higher-order controller to that of its lower-order approximate at a few expansion points in the s-plane. The selection of an optimal set of expansion points is formulated in an optimization problem frame with the aim of minimizing the area between responses of the desired and designed closed-loop systems, keeping the stability of the designed closed-loop system as a constraint. The efficacy of the proposed approach is illustrated by the design of different controllers for time-delay-dominated nonsquare process and FO square process. Comparative analysis is carried out using time-domain performance indices by introducing parameter uncertainty and disturbance signals. To demonstrate the applicability of the proposed method, a real-time investigation is carried out with the design and implementation of a controller for interacting hybrid (conical and spherical) tank process setup.

Design of IIR full-band differentiators with improved nearly linear phase

Linear, or almost linear phase in the design of digital differentiators depends both on the method of calculation of the filter coefficients and the adopted structural design. Acknowledging the importance of this design objective, we developed a method to derive infinite impulse response differentiators which tackles it from both perspectives and yields improved characteristics compared to our previous design. We have replaced the differentiator structure comprising an all-pass filter and a delay line with a configuration of two infinite impulse response all-pass filters. Furthermore, we provide a procedure for determining an improved initial solution to the optimization of filter coefficients, as well as a procedure for improving the differentiator's magnitude response. The final solution exhibits considerably lower error at low frequencies and is thus suitable for the common scenario where the relevant spectral content decreases with frequency. The proposed filters of third and fifth order outperform many existing solutions in literature, especially in terms of the phase characteristic and time-domain performance.

Synthetic design and analysis of the new feed cabin mechanism in Five-hundred-meter Aperture Spherical radio Telescope (FAST)

Due to the large weight of the feed cabin, the observation range of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) is limited and unable to cover the galactic center. To solve this problem, a new feed cabin mechanism (NFCM) is designed to replace the heavy rigid components using the novel lightweight cable-driven structure, where the observation-related characteristics are investigated. After dimensional optimization, the observation range is analyzed using a two-level optimization that has explicit graphic-based solutions, the parameter sensitivity is studied by proposing the direct numerical method, and the anti-disturbance ability is discussed using the novel disturbance unit increment method. Numerical simulations indicate that the optimal designed NFCM can achieve required larger observation range with exceptional observation performance. Additionally, considering the two-level control mode of FAST, a novel controller is proposed for the NFCM by addressing dynamics in the non-inertial frame, and the control performance in time and frequency domain is validated using actual observation data, where the NFCM can effectively suppress residual errors from the outer six-cable-driven system in FAST and has satisfactory control robustness in resisting system disturbances.

Multi-center atrial fibrillation electrocardiogram (ECG) classification using Fourier space convolutional neural networks (FD-CNN) and transfer learning

There has been a proliferation of machine learning (ML) electrocardiogram (ECG) classification algorithms reaching >85% accuracy for various cardiac pathologies. Despite the high accuracy at individual institutions, challenges remain when it comes to multi-center deployment. Transfer learning (TL) is a technique in which a model trained for a specific task is repurposed for another related task, in this case ECG ML model trained at one institution is fine-tuned to be utilized to classify ECGs at another institution. Models trained at one institution, however, might not be generalizable for accurate classification when deployed broadly due to differences in type, time, and sampling rate of traditional ECG acquisition. In this study, we evaluate the performance of time domain (TD) and frequency domain (FD) convolutional neural network (CNN) classification models in an inter-institutional scenario leveraging three different publicly available datasets. The larger PTB-XL ECG dataset was used to initially train TD and FD CNN models for atrial fibrillation (AFIB) classification. The models were then tested on two different data sets, Lobachevsky University Electrocardiography Database (LUDB) and Korea University Medical Center database (KURIAS). The FD model was able to retain most of its performance (>0.81 F1-score), whereas TD was highly affected (<0.53 F1-score) by the dataset variations, even with TL applied. The FD CNN showed superior robustness to cross-institutional variability and has potential for widespread application with no compromise to ECG classification performance.

Enhancing time-domain performance of vehicle cruise control system by using a multi-strategy improved RUN optimizer

This paper addresses the pressing concern of traffic safety by focusing on the optimization of vehicle cruise control systems. While traditional control techniques have been widely employed, their design procedures can be time-consuming and suboptimal. To overcome these limitations, metaheuristic algorithms have been introduced as promising solutions for complex optimization problems. In this study, an improved Runge Kutta optimizer (IRUN) is developed and applied to enhance the control performance of a real PID plus second-order derivative (RPIDD2) controller for vehicle cruise control systems. The IRUN optimizer incorporates advanced strategies such as quadratic interpolation, Laplacian segment mutation, Levy flight, and information-sharing-based local search mechanisms. By integrating these strategies, the IRUN algorithm demonstrates enhanced optimization capabilities, making it well-suited for tuning the controller. The proposed approach utilizes a master–slave system, where the ideal reference model sets the desired response and the RPIDD2 controller adjusts its parameters accordingly. The integral of the square error is employed as the objective function to evaluate the control system's performance. Statistical analyses, convergence analyses, and stability evaluations and robustness analysis are performed to demonstrate the effectiveness of the IRUN-based RPIDD2 controller. Comparative studies are conducted against established approaches using PID, fractional-order PID (FOPID), and RPIDD2 controllers, showcasing the superiority and effectiveness of the proposed approach. Overall, this paper presents a comprehensive study on enhancing the time-domain performance and stability of vehicle cruise control systems, providing significant improvements in control accuracy and efficiency. The subsequent sections delve into the proposed approach, experimental setup, and obtained results, further emphasizing the significance and potential impact of this research.

DESIGN OF A VARIABLE GAIN NONLINEAR FUZZY CONTROLLER AND PERFORMANCE ENHANCEMENT DUE TO GAIN VARIATION

In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs

The dynamics of one-dimensional quantum droplets and the emerging applications of deep learning in landing technology have become prominent research areas. In this work, we present a novel methodology, termed time piecewise physics-informed neural networks (PINNs), to study the intricate dynamics of one-dimensional quantum droplets by solving the amended Gross–Pitaevskii equation. Our network model exhibits superior training performance in the long time domain compared to conventional PINNs, with each of its subnetwork operating independently and offering high adjustability. By employing time piecewise PINNs with scarce training points, we not only study intrinsic modulations of single droplet and collision between two droplets, but also excite the breather on droplet background. Intriguingly, we obtain an interference pattern from training result of collision between two droplets, which is a significant feature of the interplay of coherent matter waves. The numerical findings demonstrate that in a nonlinear non-integrable system, varying parameters can result in vastly different dynamic behaviors despite sharing the same initial conditions. Our results offer valuable insights and guidance for leveraging deep learning technology to facilitate intrinsic modulations of single droplet, droplets collision, and excitation of breather.

Compact and high gain slotted patch antenna with moderate bandwidth for 60 GHz applications

A compact and high gain dual semi-circular slotted patch antenna with moderate bandwidth for 60 GHz applications is presented in this article. A rectangular-shaped patch inspires this design. The slotted antenna provides an impedance bandwidth of 1.75 GHz (58.87–60.62 GHz) and a gain of 7.55 dB. The overall size of the proposed antenna is 12 × 9.5 mm2. A dielectric superstrate is used to improve the antenna bandwidth and gain. The proposed antenna with superstrate exhibits an improved bandwidth of 2.48 GHz (58.22–60.70 GHz), an enhanced gain of 11.8 dB, and an efficiency of 95%, respectively. The antenna provides stable time-domain performance (isolation, isolation phase, group delay, and fidelity factor) over the operating band. The design prototype is fabricated and tested experimentally. Measured results exhibit a good agreement with the simulated results. The proposed antenna is suitable for high data-rate radio access and high gain 60 GHz applications.

PIDD2 Control of Large Wind Turbines’ Pitch Angle

The pitch control system has a profound impact on the development of wind energy, and yet a delay or non-minimum phase can weaken its performance. Thus, there is a strong incentive to enhance pitch control technology in order to counteract the negative effects of unidentified delays and non-minimum phase characteristics. To reduce the complexity of the parameter-tuning process and improve the performance of the system, in this paper, we propose a novel control method for wind turbine pitch angle with time delays. Specifically, the proposed control method is state-space PIDD2, which is based on internal model control (IMC) and the open-loop system step response. Then, considering the tracking, disturbance rejection and measurement noise, the proposed controller is verified through simulations. The simulation results demonstrate that the state-space PIDD2 (SS-PIDD2) can provide a trade-off between robustness, time domain performance and measurement noise attenuation and effectively improve pitch control performance in contrast to series PID and PI control methods.

Miniaturized Time-Domain Antenna With Improved Low-Frequency Radiation Performance

A miniaturized end-fire antenna with improved low-frequency radiation performance (RP) is proposed for time- domain applications. Through a novel resistive loading (RL) method, the proposed time-domain antenna (TDA) has a compact size of 0.176 λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ) × 0.156 λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sub> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">W</i> ), and improved low-frequency RP. Note that, this improvement does not mean the improvement of radiation efficiency, but means the enhancement of the radiation in forward and the reduction of the radiation in backward. Furthermore, the size of the proposed TDA is reduced by 78% as compared with the traditional antipodal Vivaldi antenna (AVA). In order to provide a certain reference for the design of end-fire TDAs, the mechanism of the novel RL technique is explored according to the design. Measured results show that the bandwidth of the proposed TDA is 0.168 ∼ 3 GHz (179%). Due to the compact size and good time-domain performance, the proposed TDA can be a good candidate for time-domain applications such as ground penetrating radar (GPR), Through-Wall Radar (TWR) and high-power pulsed source (HPS). Meanwhile, the novel RL technique can be a prior solution for the miniaturization and low-frequency RP improvement for end-fire TDAs.

Fractional-order PID controller design via optimal selection strategy of frequency domain specifications

In this paper, a novel fractional-order Proportional-Integral Derivative (PID) controller design depending on optimal selection of frequency domain specifications is proposed for time delay systems. The frequency domain specification sets, namely, (i) phase margin and gain crossover frequency and (ii) phase margin and gain margin are determined so that the reference model is optimal according to three time domain performance indices, i.e. Integral Square Error (ISE), Integral Time Square Error (ITSE) and Integral Absolute Error (IAE). Here, the delayed Bode's ideal transfer function is employed in the reference model. Moreover, the stability region of the reference model is given via a theorem. In simulation studies, the proposed methodology is compared with other two different methods using the same frequency domain specifications. It is observed that the proposed optimal fractional-order PID controllers outperform according to the mentioned performance indices, and they also possess considerably acceptable performance in terms of other time domain specifications such as overshoot, settling time, etc.

Effective PID controller design using a novel hybrid algorithm for high order systems.

This paper discusses the merging of two optimization algorithms, atom search optimization and particle swarm optimization, to create a hybrid algorithm called hybrid atom search particle swarm optimization (h-ASPSO). Atom search optimization is an algorithm inspired by the movement of atoms in nature, which employs interaction forces and neighbor interaction to guide each atom in the population. On the other hand, particle swarm optimization is a swarm intelligence algorithm that uses a population of particles to search for the optimal solution through a social learning process. The proposed algorithm aims to reach exploration-exploitation balance to improve search efficiency. The efficacy of h-ASPSO has been demonstrated in improving the time-domain performance of two high-order real-world engineering problems: the design of a proportional-integral-derivative controller for an automatic voltage regulator and a doubly fed induction generator-based wind turbine systems. The results show that h-ASPSO outperformed the original atom search optimization in terms of convergence speed and quality of solution and can provide more promising results for different high-order engineering systems without significantly increasing the computational cost. The promise of the proposed method is further demonstrated using other available competitive methods that are utilized for the automatic voltage regulator and a doubly fed induction generator-based wind turbine systems.

A novel observer design for friction estimation

In this paper, we propose a novel adaptive friction estimator for simple mechanical systems with Coulomb friction. We assume that the friction constant is unknown and we propose an adaptive observer for its estimation. We show that under certain conditions the observer structure is asymptotically stable. The proposed observer dynamics has two tuning parameters and essentially behaves as a second-order switching system. These parameters could be utilised to tune some time domain performance measures such as settling time, per cent overshoot. etc., under certain conditions. Lastly, simulations reveal that when the actual friction is not confined to Coulomb friction only, the proposed design improves the position tracking performance, especially when the position controller has low bandwidth.