Controller Tuning Research Articles

Synthesis of Tetrasubstituted Alkenes by Rhodium-Catalyzed Regioselective Cyano Transfer.

We describe herein a novel, general, and robust approach to structurally diversified alkenyl nitriles through a Rh-catalyzed cyano transfer reaction between alkynyl-malononitrile derivatives and aryl/alkenyl boronic acids. This reaction exhibits high chemo- and regioselectivity and a broad substrate scope. The tetrasubstituted alkenyl dinitriles (34 examples, average 58% yield) are obtained through substrate tuning and ligand control.

Generation of Multiwavelength Fibre Laser based on Erbium-Doped Fibre Amplifier with Lyot Filter

A ring cavity setup consisting of erbium-doped fibre amplifier (EDFA) as the optical pump and lyot filter aids in the production of a multiwavelength spectrum. The wavelength of EDFA pumps in photons range of 1530 nm to 1560 nm, respectively. Using maximum power of 18 dBm and a single mode fibre (SMF) of 10 km length, the number of peak lasing lines produced between 3 dB spectral range is 51. Tuning of the polarization controller (PC) to a specific angle helps provide the most stable lasing line. Stability test is done on the output multiwavelength fibre laser (MWFL) over a time period to analyze the wavelength stability.

Frequency Control of Interconnected Power System via SBO assisted Simultaneous Tuning Strategy in Presence of DFIG

To achieve the objectives of the automatic generation control (AGC) of wind integrated interconnected power system (WIIPS), better tuning and control strategies are required. This paper suggests simultaneous tuning strategy for the AGC and wind system controllers to improve the stability of the WIIPS. The bulk amount of wind is integrated into the grid using the doubly fed induction generator (DFIG) and its simplified model is used to simulate the WIIPS. Initially, classical controllers are opted in AGC mechanism to reduce the frequency disturbances caused by the load and wind generation uncertainties. Further, classical controllers of WIIPS are replaced with cascade controllers to enhance the system frequency profile during the disturbances. The optimal set of solutions of the classical and cascade controllers are examined by the satin bowerbird optimizer (SBO) with the help of integral square error as fitness function of the optimization problem. Comparisons are provided to show the merits of the WIIPS over normal interconnected power system, cascade controller over classical controller and simultaneous tuning strategy over regular tuning mechanism.

Tunable acoustic transmission control and dual-mode ventilated sound insulation by a coupled acoustic metasurface

Tunable acoustic transmission control and dual-mode ventilated sound insulation by a coupled acoustic metasurface

Tunable polarization control with self-assembled arrays of anisotropic plasmonic coaxial nanocavities

Polarization control with nanostructures having a tunable design and allowing inexpensive large-scale fabrication is important for many nanophotonic applications. For this purpose, we developed and experimentally demonstrated nanostructured plasmonic surfaces based on hexagonal arrays of anisotropic coaxial nanocavities, which can be fabricated by a low-cost self-assembled nanosphere lithography method. Their high polarization sensitivity is achieved by engineering anisotropy of the coaxial nanocavities, while the optical response is enhanced by the excitation of surface plasmon resonances. Particularly, varying the geometrical parameters of the coaxial nanocavities, namely the height and tilt angle of their central core nanoellipsoids, the plasmonic resonance wavelengths as well as the polarization-selective behavior can be individually tuned in the entire visible and near-infrared spectral regions, which makes such nanostructures good candidates for the implementation of polarization-controlled optical switches and polarization-tunable filters. Moreover, the developed nanostructures demonstrate sensitivity up to 1335 nm/RIU in refractive index sensing.

Fractional High-Order Differential Feedback Controller Based on Meta-Heuristic Algorithms for Automatic Voltage Regulator

In this study, optimally parameter tuning of fractional high-order differential feedback controller (FHODFC) for an automatic voltage regulator (AVR) system regulating the terminal voltage of the synchronous generator is presented. Recently developed meta-heuristic optimization techniques named honey badger algorithm (HBA) and gorilla troops optimizer (GTO) have been employed for the first time in order to optimally determine ten different parameters of the FHODFC. The performance of the proposed controllers, that is, HBA-FHODFC and GTO-FHODFC, is analyzed in terms of transient and steady state responses, and robustness against uncertainties and external disturbances. In addition, their performance is compared to a FHODFC of which parameters were tuned by using particle swarm optimization algorithm in a previous study. The results indicate that the proposed HBA-FHODFC and GTO-FHODFC controllers provide zero overshoot and better results in terms of settling time and objective function then the PSO tuned FHODFC. Therefore, the proposed controllers can be used as an effective method in the AVR system.

Optimization tools for Twin-in-the-Loop vehicle control design: analysis and yaw-rate tracking case study

Given the urgent need to simplify the end-of-line tuning of complex vehicle dynamics controllers, the Twin-in-the-Loop Control (TiL-C) approach was recently proposed in the automotive field. In TiL-C, a digital twin is run in real time on-board the vehicle to compute a nominal control action; an additional controller is used to compensate for the mismatch between the simulator and the actual vehicle. As the digital twin is assumed to be the best replica available of the real plant, the key issue in TiL-C becomes the tuning of the compensator, which must be performed relying on data only. In this paper, we investigate the use of different black-box optimization techniques for the calibration of the compensator. More specifically, we compare the initially proposed Bayesian Optimization (BO) approach with Virtual Reference Feedback Tuning (VRFT), a one-shot direct data-driven design method, and with Set Membership Global Optimization (SMGO), a recently proposed black-box optimization method. The analysis will be carried out within a professional multibody simulation environment on a novel TiL-C application case study – the yaw-rate tracking problem – to further prove the TiL-C effectiveness on a challenging problem. Simulations will show that the VRFT approach is capable of providing a well-tuned controller after a single iteration, while 10 to 15 iterations are necessary for refining it with global optimizers. Also, SMGO is shown to reduce the computational effort required by BO significantly.

Shunted piezoelectric patch adaptive vibration absorber set to maximise electric power absorption: A comparison between parallel and series RL-shunts

This paper presents a comparative study on two types of shunted piezoelectric patch adaptive vibration absorbers, which can be bonded in batches on thin-walled structures to control the broad-band resonant response of low order flexural modes. The self-contained control units are formed by a thin piezoelectric patch connected either to a series or to a parallel resistive-inductive (RL) network. The two components of the shunt are adapted online in such a way as to maximise the time-averaged electric power absorbed by the shunt, which corresponds to minimising the time-averaged total flexural response of the hosting structure. The study considers a practical demonstrator formed by a thin rectangular plate with five piezoelectric patches connected to digital RL-shunts, which is excited in bending by a stationary white noise point force. The aim of the paper is to contrast the tuning and vibration control properties of the series and parallel RL shunts. More specifically, the online implementation of a recursive two-paths tuning strategy along R-constant and L-constant paths with an extremum seeking gradient search algorithm is analysed first for the two types of shunts. Then, the vibration control performance produced by the two types of shunts is investigated for the case where they are tuned to control the resonant response of the first flexural mode of the plate.

A Low-Power Tunable Differentiator Using Voltage Difference Transconductance Amplifier (VDTA) for Tunable PD Controller

The electronically tunable differentiator using a voltage difference transconductance amplifier (VDTA) is proposed, designed, and analyzed. The simulation was done using the Cadence Virtuoso tool of 45[Formula: see text]nm CMOS technology with a supply voltage of ±0.9[Formula: see text]V. The maximum power consumption of the proposed circuit is 246[Formula: see text][Formula: see text]W with a total harmonic distortion of 5.4%. The output can be tuned using four parameters: [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]. The transconductance can be varied using bias current and aspect ratio of CMOS transistors. The utilized area of VDTA layout is [Formula: see text]. The parasitic impedance affects the output of post-layout simulation and causes little delay compared to schematic. The design has been experimentally verified using LM13700 integrated circuit. The results of the proposed circuit show good agreement with the experimental results and mathematical expressions. The proposed circuit can be used as a tunable PD controller, in which the voltage gain of the proposed circuit is [Formula: see text]. The design is versatile and can be used in different applications such as temperature control systems, photo voltaic cells, waveform generators, microwave communications systems, and instrumentation systems.

Designing Heuristic-Based Tuners for Fractional-Order PID Controllers in Automatic Voltage Regulator Systems Using a Hyper-Heuristic Approach

This work introduces an alternative approach for developing a customized Metaheuristic (MH) tailored for tuning a Fractional-Order Proportional-Integral-Derivative (FOPID) controller within an Automatic Voltage Regulator (AVR) system. Leveraging an Automated Algorithm Design (AAD) methodology, our strategy generates MHs by utilizing a population-based Search Operator (SO) domain, thus minimizing human-induced bias. This approach eliminates the need for manual coding or the daunting task of selecting an optimal algorithm from a vast collection of the current literature. The devised MH consists of two distinct SOs: a dynamic swarm perturbator succeeded by a Metropolis-type selector and a genetic crossover perturbator, followed by another Metropolis-type selector. This MH fine-tunes the FOPID controller’s parameters, aiming to enhance control performance by reducing overshoot, rise time, and settling time. Our research includes a comparative analysis with similar studies, revealing that our tailored MH significantly improves the FOPID controller’s speed by 1.69 times while virtually eliminating overshoot. Plus, we assess the tuned FOPID controller’s resilience against internal disturbances within AVR subsystems. The study also explores two facets of control performance: the impact of fractional orders on conventional PID controller efficiency and the delineating of a confidence region for stable and satisfactory AVR operation. This work’s main contributions are introducing an innovative method for deriving efficient MHs in electrical engineering and control systems and demonstrating the substantial benefits of precise controller tuning, as evidenced by the superior performance of our customized MH compared to existing solutions.

Enhancing the performance in the offline controller tuning of robotic manipulators with chaos: a comparative study with differential evolution

Enhancing the performance in the offline controller tuning of robotic manipulators with chaos: a comparative study with differential evolution

Local Bayesian optimization for controller tuning with crash constraints

Abstract Controller tuning is crucial for closed-loop performance but often involves manual adjustments. Although Bayesian optimization (BO) has been established as a data-efficient method for automated tuning, applying it to large and high-dimensional search spaces remains challenging. We extend a recently proposed local variant of BO to include crash constraints, where the controller can only be successfully evaluated in an a-priori unknown feasible region. We demonstrate the efficiency of the proposed method through simulations and hardware experiments. Our findings showcase the potential of local BO to enhance controller performance and reduce the time and resources necessary for tuning.

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.

Ultra-fast tuning of neural network controllers with application in path tracking of autonomous vehicle

Neural network (NN) controllers have shown great potential in solving complex control or decision-making tasks. However, most of the NN controllers either rely on the availability of large datasets or require dense interactions with the environment, which hinders their application in real systems. In this paper, we introduce a model-based reinforcement learning (MBRL) algorithm, aimed at realizing ultra-fast tuning of deep NN controller from a small sample set of real-world data. The algorithm uses Gaussian processes (GPs) to model the unknown dynamics of real system and updates controller parameters through stochastic gradient descent. By using particle-based method for long-term predictions, the algorithm can easily incorporate online state estimators and filters into controller learning, which is conductive to learning from systems with partially measurable states and stochastic control delay. We apply the algorithm to calibrate a deep NN controller for the path tracking of a full-size autonomous vehicle (AV). Simulation and field test results show that the deep NN controller can be well calibrated after only one interaction with the environment and can achieve similar tracking performance to optimization-based methods such as nonlinear model prediction control (NMPC) in various test scenarios by combining with a feed-forward pure pursuit (PP) controller.

Analytically derived disturbance rejection‐based PID controller tuning for second‐order plus dead time plants

AbstractThis letter proposes a proportional‐integral‐derivative (PID) design method for second‐order plus dead time models based on a desired closed‐loop transfer function for load disturbance changes. Also, tuning rules for single integrating first‐order plus dead time models are provided. Using a two‐degree‐of‐freedom control scheme, the design problem considers load disturbance rejection, robustness to model uncertainties, and setpoint tracking. Three examples are used to assess the performance of the proposed method. Finally, the results are compared to two popular PID control design methodologies, skogestad internal model control or skogestad IMC (SIMC) and improved SIMC (iSIMC).

Controlled circular dichroism with graphene-based metamaterial for terahertz wave

This article explores the design and analysis of a metal-graphene hybrid metamaterial structure tailored for tunable circular dichroism (CD) effects in the terahertz (THz) frequency regime. Chiral metamaterials have garnered considerable interest in photonics due to their versatile applications, including sensing, polarization manipulation, and chiral imaging. The proposed metamaterial unit cell features four meta-atoms with C4 rotational symmetry, composed of gold on a polyimide substrate. By strategically integrating the graphene sheets above the gold patterns, selective control over the absorption efficiency for the incident wave of left-handed circularly polarized (LCP) and right-handed circularly polarized (RCP) light is achieved. The study demonstrates that adjusting graphene chemical potential enables precise modulation of CD from 0.80 to 0.10 across a wide THz frequency spectrum. Furthermore, the article investigates the structure optical response for incident angles ranging up to 75°, revealing stable CD behavior up to 30° and intriguing dual-band effects beyond 50°. These findings underscore the potential of the proposed metamaterial for practical applications in photonics, sensing, and chiral imaging, offering tunable control over the CD effects in the THz regime.

Controlling effective field contributions to laser-induced magnetization precession by heterostructure design

Nanoscale heterostructure design can control laser-induced heat dissipation and strain propagation, as well as their efficiency for driving magnetization precession. Here, we incorporate MgO layers into the experimental platform of metallic Pt-Cu-Ni heterostructures to block the propagation of hot electrons. We show via ultrafast x-ray diffraction the capability of our platform to control the spatio-temporal shape of the transient heat and strain. Time-resolved magneto-optical Kerr experiments with systematic tuning of the magnetization precession frequency showcase control of the magnetization dynamics in the Ni layer. Our experimental analysis highlights the role of quasi-static strain as a driver of precession when the magnetic material is rapidly heated via electrons. The effective magnetic field change originating from demagnetization partially compensates the change induced by quasi-static strain. The strain pulses can be shaped via the nanoscale heterostructure design to efficiently drive the precession, paving the way for opto-magneto-acoustic devices with low heat energy deposited in the magnetic layer.

Design and Evaluation of a Bilateral Semi-Rigid Exoskeleton to Assist Hip Motion.

This study focused on designing and evaluating a bilateral semi-rigid hip exoskeleton. The exoskeleton assisted the hip joint, capitalizing on its proximity to the body's center of mass. Unlike its rigid counterparts, the semi-rigid design permitted greater freedom of movement. A temporal force-tracking controller allowed us to prescribe torque profiles during walking. We ensured high accuracy by tuning control parameters and series elasticity. The evaluation involved experiments with ten participants across ten force profile conditions with different end-timings and peak magnitudes. Our findings revealed a trend of greater reductions in metabolic cost with assistance provided at later timings in stride and at greater magnitudes. Compared to walking with the exoskeleton powered off, the largest reduction in metabolic cost was 9.1%. This was achieved when providing assistance using an end-timing at 44.6% of the stride cycle and a peak magnitude of 0.11 Nm kg-1. None of the tested conditions reduced the metabolic cost compared to walking without the exoskeleton, highlighting the necessity for further enhancements, such as a lighter and more form-fitting design. The optimal end-timing aligns with findings from other soft hip exosuit devices, indicating a comparable interaction with this prototype to that observed in entirely soft exosuit prototypes.

Improvisation of artificial hummingbird algorithm through incorporation of chaos theory in intelligent optimization of fractional order PID controller tuning

Improvisation of artificial hummingbird algorithm through incorporation of chaos theory in intelligent optimization of fractional order PID controller tuning

Enhanced room temperature ammonia sensing using Ti2VC2Tx double-transition-metal MXenes: experimental and theoretical insights

Double-transition-metal (DTM) MXenes are potentially multifunctional materials with greater compositional and structural tunability than mono-transition-metal (MTM) MXenes, enabling controllable formation of defects and controllable tuning of material properties. Herein, we investigate Ti2VC2Tx's ammonia gas sensing via experiments and theoretical calculations. Ti2VC2Tx exhibited a notable response, exceeding 25 %, to 100 ppm ammonia at room temperature with rapid response/recovery times of 4 s/16.2 s. Furthermore, the Ti2VC2Tx sensor shows exceptional ammonia selectivity, attributed to closer adsorption distances and higher adsorption energies of ammonia molecules. This study broadens the application area of DTM MXenes and further demonstrates the potential of MXene materials for gas sensing.