Response Of Closed-loop System Research Articles

A new hybrid fixed and adaptive gains control algorithm to reduce power losses on LLCL filter-based renewable energy conversion systems with systematic parametrization using Grey Wolf optimizer

Currently, there is a transition in the energy matrix around the world, where traditional sources of energy generation are continually being replaced by energy generation systems based on renewable sources to mitigate the climate crisis. In this bias, this work presents the mathematical modeling of an LLCL filter, used to connect power generation systems based on renewable energy sources to the electrical grid, and presents a novel hybrid fixed-and adaptive gains control strategy for current injection into the grid using this system. The developed hybrid controller is composed of a proportional–integral controller and a direct robust adaptive controller. The first term of the controller guarantees the reference current, while the second term of the controller is used for disturbance rejection. Furthermore, a systematic procedure for the controller’s parametrization based on Grey Wolf Optimizer is also provided. The control of the current injected into the grid is carried out considering the LLCL filter without passive damping resistors in the filter structure to avoid power losses due to the passive filter elements. Additionally, the LLCL filter model considers minimal parasitic resistances to evaluate the controller’s performance and optimize it for the application of interest, aiming to maximize the system performance by ensuring a short transient regime due to the fast closed-loop system response. Simulation results indicate high performance of this optimized control strategy with small tracking error even considering grid impedance variations.

Transient Response Analysis of Reset PID Control Systems

Reset controllers have demonstrated their efficacy in enhancing transient responses, such as the overshoot and response time in motion control systems. Designing these systems to meet specific transient requirements requires a method for analyzing transient responses. However, the inherent nonlinearity of reset control systems presents challenges in this regard, limiting their widespread application. This study introduces a novel method for analyzing the step responses of closed-loop reset control systems. By decomposing the step response of the reset system into piece-wise functions, with each piece-wise function computed based on linear systems, this analysis method offers new insights into understanding reset systems. Experimental validation conducted on eleven reset Proportional-Integral-Derivative (PID) control systems implemented on a precision motion stage confirms the effectiveness of the proposed method. The experimental results also underscore the applicability of the method as a tool for selecting optimized parameters and reset control structures to achieve enhanced transient responses.

Distributed and Localized Model Predictive Control—Part II: Theoretical Guarantees

Engineered cyberphysical systems are growing increasingly large and complex. These systems require scalable controllers that robustly satisfy state and input constraints in the presence of additive noise – such controllers should also be accompanied by theoretical guarantees on feasibility and stability. In our companion paper, we introduced Distributed and Localized Model Predictive Control (DLMPC) for large-scale linear systems; DLMPC is a scalable <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">closed-loop</i> MPC scheme in which subsystems need only exchange local information in order to synthesize and implement local controllers. In this paper, we provide recursive feasibility and asymptotic stability guarantees for DLMPC. We leverage the System Level Synthesis framework to express the maximal positive robust invariant set for the closed-loop system and its corresponding Lyapunov function in terms of the closed-loop system responses. We use the invariant set as the terminal set for DLMPC, and show that this guarantees feasibility with minimal conservatism. We use the Lyapunov function as the terminal cost, and show that this guarantees stability. We provide fully distributed and localized algorithms to compute the terminal set offline, and also provide necessary additions to the online DLMPC algorithm to accommodate coupled terminal constraint and cost. In all algorithms, only local information exchange is necessary, and computational complexity is independent of the global system size – we demonstrate this analytically and experimentally. This is the first distributed MPC approach that provides minimally conservative yet fully distributed guarantees for recursive feasibility and asymptotic stability in the nominal and robust settings.

An Improved Feedforward-Robust Algorithm for Active Vibration Control of Helicopter Maneuver Flight

To solve the problem of secondary path mutation and external disturbance abrupt changes during helicopter maneuver flight, the previous research proposed a hybrid active vibration control law. To improve the engineering applicability, the original algorithm is ameliorated to the least mean square-input-output-based robust (LMS-IOBR) algorithm. The system model within the target frequency band can be identified through the input-output data to avoid constructing complex state observers. In addition, the output form of the feedback controller is constructed by an autoregressive moving average model with extra input, which is beneficial to improve operational efficiency. Numerical simulations demonstrate that compared with the original algorithm, controller real-time computation can be reduced by 52% with control effects guaranteed at the same time. Furthermore, to verify the effectiveness and adaptability of LMS-IOBR, multi-input multioutput vibration control experiments are carried out on a specially developed simple platform for simulating helicopter maneuver states. Comparative tests in various typical states are performed between the LMS-IOBR and the multichannel least mean square algorithm. Under the complex circumstances of simulating continuous subduction uplift, the peak response of closed-loop system attenuates by 80% and 70%, and the vibration of two points is reduced to 15% and 20%, respectively, within 3 s. The experimental results demonstrate that the proposed LMS-IOBR algorithm shows stronger transient adaptability and robustness against external disturbance excitation and secondary channel mutation in helicopter maneuver flight.

Mitigation of Uncertainty in an Islanded Microgrid Using Robust Voltage Controller

In microgrid, a severe problem occurs in terms of voltage oscillations due to mismatch between synchronizing and damping torque. In this study, a centralized nonlinear sliding mode voltage controller proposes to minimize the rotor and DC voltage oscillations issue in an islanded microgrid. The linear matrix inequality (LMI) technique has been applied for bounding the state error. Lyapunov criteria is utilized for assurance of asymptotic convergence and LMI optimization approach is used for obtaining the controller parameters. The proposed controller is able to tackle the parametric uncertainties of diesel generator, oscillations of rotor and voltage fluctuation as well as the closed-loop system responses also improves both transient responses and steady state responses simultaneously. The simulation results authenticate that the proposed controller confirms speedy recovery of nominal frequency without any oscillations and reduced the limitation of chattering notably without any loss in control accuracy. The performance and robustness of the proposed controller is also compared with conventional controllers.

Finite-Time Stabilization of the Generalized Bouc–Wen Model for Piezoelectric Systems

When designing controllers for piezoelectric systems with hysteresis, usually simplified models are used. This can lead to inaccuracies in the closed-loop system response. In this letter, we pose the problem of tracking stabilization of piezoelectric systems using the generalized Bouc-Wen model, a highly non-linear system rarely used to design controllers. Besides, we consider only partially knowledge of one hysteresis system parameter and external disturbances in all the system states. We propose an interconnected control composed of three parts for the solution: an observer, a virtual hysteresis control, and actuator control. It is demonstrated that the closed-loop system converges in finite time. Simulation experiments were carried out, demonstrating the effectiveness of our approach despite exogenous and unknown disturbances.

Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops

In this paper, a robust control technique is developed to achieve the quadrotor stabilization against unmodeled matching vanishing dynamics. The synthesis of the proposed robust control is based on the Lyapunov approach and the backstepping method allowing to construct an iterative control algorithm. To compare the performance of the proposed controller, a Proportional Derivative (PD) controller is used to obtain experimental results in an outdoor environment. To compare the closed-loop system responses with both controllers, the Integral Absolute Error is computed and several tests are conducted to calculate the error standard deviation. Ultimately, employing the robust backstepping control approach in pest recognition in maize crops, which is a specific task of precision agriculture, demonstrates its effectiveness in improving the trajectory tracking of the vehicle while it captures images of the crops.

A nonlinear adaptive fuzzy controller with signal transmission delay compensation for steel rope tension active control of mining hoists

The double-rope winding hoists have been widely used in the ultra-deep mines. However, there exists tension imbalance issue on two steel rope of the double-rope winding hoist. The passive tension control method is not ideal in both adjust accuracy and response speed. Therefore, a novel hybrid control method is proposed for active control of two steel rope tensions considering the wireless transmission delay of steel rope tension signal, nonlinear uncertainties, and external disturbance. First, a signal transmission delay compensator is designed to obtain the observed feedback signal and other correlated variables. It is worth mentioning that the effectiveness of designed signal transmission delay compensator is verified not only in theory and simulation but also by experiments. Then, a hybrid controller that combines the adaptive backstepping theory and adaptive fuzzy algorithm is designed to obtain the active control output of two steel rope tensions. It is theoretically depicted that the proposed nonlinear adaptive fuzzy controller combined with the signal transmission delay compensator not only achieves good robust performance on model uncertainty but also improves the closed-loop system response rate. Moreover, the proposed controller can compensate external disturbance and suppress chattering caused by ordinary methods based on backstepping technology. The stability of the integrated closed-loop system with the hybrid controller is proved on the basis of Lyapunov theory. In order to demonstrate the feasibility and effectiveness of the proposed nonlinear adaptive fuzzy controller combined with the signal transmission delay compensator, a double-rope winding hoisting simulated test device is set up for experimental investigation. Then, contrast experiments with the traditional proportion–integration, adaptive backstepping controller, and the proposed controller are conducted on the test device. Experimental results verify the superior of the proposed nonlinear adaptive fuzzy controller combined with the signal transmission delay compensator on tension control of two steel ropes for the double-rope winding hoist.

Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set point. The FF arrangements are made based on various pre-analysis. A detailed simulation study indicates that the proposed PID controller tuned with Firefly Algorithm (FF-PID) for MRS is beneficial and suitable to achieve desired closed-loop system response. The FF is touted as providing an easy, reliable, and efficient tuning technique for PID controllers. The most suitable ideal performance is accomplished with FF-PID, according to the display in the time response. Further, the observed response is compared to those received by applying GA and conventional off-line tuning techniques. The comparison of all tuning methods exhibits supremacy of FF-PID tuning of the given nonlinear Mobile Robot System than GA-PID tuning and conventional controller.

Wind turbine load reduction based on 2DoF robust individual pitch control

The individual pitch controller can mitigate asymmetric loads in wind turbines. However, wind turbine dynamics have strong nonlinearity and high uncertainty. In addition to target value tracking, suppression of wind disturbance is also a performance requirement of the individual pitch controller, while the traditional PI controller cannot take into account the tracking and disturbance rejection performance simultaneously. Therefore, the two-degree-of-freedom (2DoF) robust individual pitch controller is proposed to reduce loads in the above-rated region. Besides, parameter tuning is complicated in the design of the robust individual pitch controller. So the reference model method is proposed to preset the closed-loop system response. Firstly, the state-space model is established to describe the dynamics of the wind turbine. The multi-blade coordinate transformation is applied to transform the model into the fixed coordinate system. Subsequently, the μ-synthesis problem is solved by the D-K iterative algorithm to get the controller parameter. Finally, the control method is verified in GH Bladed. It is shown that rotor loads are suppressed without affecting the output power. Tower loads are also mitigated. Moreover, the relationship between the pitch actuator action and the load reduction capability is discussed by designing different bandwidths of the proposed method.

Kateter Tahrik Sisteminin Kayma Kipli Kontrolü ve Bulanık Mantık ile Performans İyileştirmesi

Catheters are used in medical applications such as bronchoscopy, colonoscopy, angiography. Due to the catheters are in direct contact with the tissue in these procedures, their movements must be controlled. In this study, three different sliding-mode controllers that can be used to control the movement of the catheter have been proposed. These are the classical sliding mode controller, quasi sliding mode controller, and asymptotic sliding mode controller structures. Performance comparison of the controllers was made by assessing the closed-loop system response. The results indicated that the performance of the quasi sliding mode controller was better than the other controllers. It has been proposed to use a fuzzy logic-based highest controller to improve the performance of the quasi sliding mode controller. The proposed controller structure updates the controller parameters depending on the predicted disturbance magnitude and position error. The results show that the real-time performance of the quasi sliding mode controller is improved by the change of the proposed control structure.

Particle Swarm Optimization-Based Fuzzy PID Controller for Stable Control of Active Magnetic Bearing System

In this paper, the application of particle swarm optimization (PSO) algorithm based fuzzy PID control for the stable control of an active magnetic bearing (AMB) system is studied. Active magnetic bearings are known to be highly nonlinear multivariable systems. An AMB system is used in motors, turbines and various other machineries in different industries to provide an active suspension to the rotor shafts. The heuristic PSO algorithm is applied to optimize the parameters of the PID controller offline. The fuzzy PID controller based on PSO algorithm is designed to adjust the control parameters of AMB system online. The comparison of controlled responses of closed-loop systems resulting from the use of conventional PID, Incomplete differential PID and particle swarm optimization-based fuzzy logic PID control strategies is discussed. The proposed controller performance is superior as compared to PID and incomplete differential PID controllers in improving the system response of an AMB under normal conditions as well as under external disturbances.

Adaptive Tracking PID and FOPID Speed Control of an Elastically Attached Load Driven by a DC Motor at Almost Step Disturbance of Loading Torque and Parametric Excitation

Adaptive tracking control of the speed of a very elastically attached circular load driven by a direct current motor accompanied with an adaptive conventional and a fractional-order Proportional Integral Derivative (PID) controller is studied. It refers to improving the closed-loop control system response of elastically coupled components of drivelines. The motor and the load mechatronic models and the block diagrams are constructed. Parameters of the PID controller in the model reference control are both constant, as well as vary in time. The adaptive control method is improved by the application of a new closed-loop control structure canceling error dynamics. A few competing control strategies are tested based on the application of two types low and high frequency stepwise increasing variations of loading torque and damping coefficient of motion. Moreover, the performance of the control strategies is verified by Integral Time-Weighted Absolute Error (ITAE) index, since their robustness is evaluated by applying a sine modulated triangle waves of selected electric parameters. Therefore, a dynamic forcing and parameter uncertainty is applied. Simulation results are compared for checking the proposed methods.

Discrete-time SISO LTI Systems with Monotonic Closed-loop Step Responses: Analysis and Control Based on Impulse Response Models

An explicit relation between the open- and closed-loop system responses is established directly in the time domain by means of Bell polynomials. This relation is used to derive necessary and sufficient conditions on the open-loop impulse response that guarantees that its closed-loop impulse response under unity feedback is non-negative in a given time range. Based on these conditions, a new design technique for PID controllers is presented that guarantees a monotonic closed-loop step response over a desired time interval. The results hold for any (possibly infinite-dimensional) discrete-time LTI system with a known impulse response. Numerical examples are provided to assess the contribution.

Linearized Bregman iteration based model‐free adaptive sliding mode control for a class of non‐linear systems

There is a growing demand for robust data-driven control methods particularly for industrial process control. This paper presents a new model-free adaptive sliding mode control approach for a class of discrete-time, multiple input and multiple output non-linear systems. The proposed methodology seeks to address issues with the computation of inverse matrices and problems with singularity in existing methods while at the same time seeking to enhance robustness. A Majorization–Minimization technique and the L1 norm are used within the proposed optimization and an online iterative approach is described for update of the control law. The closed-loop system response is proved to be stable. The effectiveness of the proposed control is validated by extensive simulation and also experimental results, with the performance obtained by the proposed approach being compared throughout with a well-known approach from the established literature.

Modeling and controller optimization for current-fed isolated bidirectional DC–DC converters

Current-fed isolated bidirectional DC–DC converters (CF-IBDCs) play an important role in battery energy storage systems. However, the closed-loop dynamics is rather slow with conventional proportional–integral controllers because a precise mathematic model remains absent for optimization. In this paper, a simple precise mathematical model is presented to describe the large and small-signal behaviors of the CF-IBDC. The full-order continuous model can accurately capture the dynamic behaviors and cover all operation conditions. The small-signal model is derived, and the DC filter inductors and clamp capacitors are found to be the natural causes of instability. Based on this finding, special controllers are proposed to optimize the dynamic response of the full closed-loop control system. The dynamic response time of the CF-IBDC is greatly reduced with the proposed controller. The correctness of the presented model and the dynamic response of the optimized closed-loop control system are verified by simulations.

Nonlinear control of passive vibratory systems with finite actuation stroke

Many vibration response control technologies employ actuators that exhibit finite stroke limits. In this paper, we consider the scenario in which a linear, time-invariant feedback law has been designed to control vibrations in a linear, time-invariant vibratory system, without accounting for the actuation stroke limits. In this scenario, the saturation of the actuator stroke may be viewed as introducing unmodeled dynamics into the closed-loop system response, which can be undesirable for a few reasons. Most importantly, it may destabilize the closed-loop system. Additionally, it introduces impulsive disturbances into the response, and may result in hardware damage. We illustrate a technique whereby the linear feedback law, designed a priori, may be augmented with a nonlinear feedback loop which protects against stroke saturation while simultaneously maintaining closed-loop stability. The nonlinear feedback law is developed around the concept of output-strict passivity, and exploits the known output-strict passivity of the vibratory system. Importantly, the nonlinear feedback law leaves the performance of the linear feedback law unaffected for small-signal responses.

Modeling and Voltage Control of Bidirectional Resonant DC/DC Converter for Application in Marine Power Systems

Abstract DC/DC converters have gained popularity in a number of industrial applications like electric vehicles or marine power systems, due to their high efficiency and power density levels. Pulse width modulation (PWM) and resonant converters are two main types of the DC/DC converters. Thereby, the resonant converters happen to be the preferred technology in the design of modern marine power systems since these converters are more suitable for the high and middle voltage DC applications. The resonant converters are, however, highly nonlinear systems, which limits the use of linear control methods. In this study, we propose a comprehensive analysis, modeling and control concept of a DC/DC resonant converter in marine power systems. First, a mathematical model of the DC/DC resonant converter in the so-called CLLC topology is derived based on the generalized state-space averaging method. The model is used to design a dual-loop voltage control, which aims to regulate the voltage level at the low-voltage DC bus of the resonant converter. The dual-loop voltage control consists of the primal linear controller, which directly regulates the voltage and the reference generator, which dynamically modifies the voltage reference of the primal controller. The major advantage of the suggested control concept is the improved performance of the simple controller without the need to substitute it as well as the possibility to realize, if required, a multi-rate control concept. Simulation studies under different load conditions show that the suggested modeling and control concept improves voltage control and the closed-loop system response.

PD-Like H∞ Control for Large-Scale Stochastic Nonlinear Systems Under Denial-of-Service Attacks

This paper focuses on the observer-based $H_\infty $ control issue for large-scale systems under denial-of-service attacks. Due to the security vulnerability of communication networks, adversaries have the capability to hamper the system normal operation by blocking the signal exchange in both sensor-to-observer channels and the observer-to-observer channels. Under this scenario, a decentralized proportional-derivative-like controller is employed to realize the predetermined $H_\infty $ performance while considering the improvement of dynamic response of closed-loop systems. By using the Lyapunov stability theory, a sufficient condition dependent on the attack occurring probability is established to realize the desired control performance. Furthermore, in light of the established condition, the desired controller and observer gains are formalized by resorting to the orthogonal decomposition of control matrix. Finally, the effectiveness and practicability of the control scheme are illustrated by resorting to the numerical simulation of a four area power system.

A Sensorless and Low-Gain Brushless DC Motor Controller Using a Simplified Dynamic Force Compensator for Robot Arm Application.

Robot arms used for service applications require safe human–machine interactions; therefore, the control gain of such robot arms must be minimized to limit the force output during operation, which slows the response of the control system. To improve cost efficiency, low-resolution sensors can be used to reduce cost because the robot arms do not require high precision of position sensing. However, low-resolution sensors slow the response of closed-loop control systems, leading to low accuracy. Focusing on safety and cost reduction, this study proposed a low-gain, sensorless Brushless DC motor control architecture, which performed position and torque control using only Hall-effect sensors and a current sensor. Low-pass filters were added in servo controllers to solve the sensing problems of undersampling and noise. To improve the control system’s excessively slow response, we added a dynamic force compensator in the current controllers, simplified the system model, and conducted tuning experiments to expedite the calculation of dynamic force. These approaches achieved real-time current compensation, and accelerated control response and accuracy. Finally, a seven-axis robot arm was used in our experiments and analyses to verify the effectiveness of the simplified dynamic force compensators. Specifically, these experiments examined whether the sensorless drivers and compensators could achieve the required response and accuracy while reducing the control system’s cost.