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This paper provides an overview of various control strategies for DC–DC converters along with a brief discussion on various performance indices for evaluating the reliability of designed controller. DC–DC converters are emerging as the fastest‐growing interfacing devices in the world because of their emergent applications in almost all domains of engineering. Notably, the non‐linear behavior of DC–DC converters offers a perplexing problem in designing a robust controller. A robust controller must ensure proper closed‐loop stability with desired performance and reliable control for output voltage regulation in the event of various possible perturbations. This creates the requirement for practically implementable non‐linear controllers that can effectively overlook the drawbacks of linear controllers. The prominence of this composition is based on the expansion in tuning techniques of proportional‐integral‐derivative controller gain parameters using linear strategies and heading towards non‐linear strategies by reviewing 196 research papers. The modification in non‐linear control strategies in terms of their fundamental features associated with key benefits and limitations are comprehensively reviewed. This study mostly revolves around non‐linear internal model control (IMC) strategies for parameter tuning of IMC‐based controllers for various order of plants with an improved degree of freedom. [ABSTRACT FROM AUTHOR]

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

In recent years, applications of inverse model-based control techniques have experienced significant growth in popularity and have been widely used in engineering applications, mainly in nonlinear control system design problems. In this study, a novel fuzzy internal model control (IMC) structure is presented for single-input-single-output (SISO) nonlinear systems. The proposed structure uses the forward and inverse dynamic Takagi–Sugeno (D-TS) fuzzy models of the nonlinear system within the IMC framework for the first time in literature. The proposed fuzzy IMC is obtained in a two-step procedure. A SISO nonlinear system is first approximated using a D-TS fuzzy system, of which the rule consequents are linearized subsystems derived from the nonlinear system. A novel approach is used to achieve the exact inversion of the SISO D-TS fuzzy model, which is then utilized as a control element within the IMC framework. In this way, the control design problem is simplified to the inversion problem of the SISO D-TS fuzzy system. The provided simulation examples illustrate the efficacy of the proposed control method. It is observed that SISO nonlinear systems effectively track the desired output trajectories and exhibit significant disturbance rejection performance by using the proposed control approach. Additionally, the results are compared with those of the proportional-integral-derivative control (PID) method, and it is shown that the proposed method exhibits better performance than the classical PID controller. [ABSTRACT FROM AUTHOR]

Active Distribution Networks are Multi-Input Multi-Output (MIMO) systems with coupled dynamics, which cause interactions among the control loops of Distributed Energy Resources (DERs). This undesired effect leads to performance degradation of voltage control. To mitigate the effects of this unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction's sources. In detail, each DER is equipped with a double-loop PI to control the active and reactive power output of the voltage source converter, which connects the DER to the network's node. Furthermore, to guarantee ancillary services, the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter's pulse are designed according to a procedure with two sequential steps based on the Internal Model Control (IMC) technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in the presence of model parameter uncertainty in the MIMO plant, modeling various operating conditions of the ADN, including a step connection of large loads, renewable energy source variations, and changes in the substation transformer ratio. [ABSTRACT FROM AUTHOR]

The extensive practice of DC-DC converter interfacing circuits to maintain DC link voltage in DC microgrid applications introduces unavoidable voltage regulation problems due to its nonlinearity. These unregulated voltages demean the performance and result in an unstable system. This brief proposes an internal model control (IMC) non-linear approach based robust proportional-integral-lead (PI-Lead) controller design for regulating a practical fifth-order DC-DC boost converter. The main innovation of this paper is the developed procedure for designing controller. The prominent feature of IMC filter coefficient is to fulfil the desired level of gain margin and phase margin to show the trade-off between performance and robustness. The proposed controller's performance is evaluated in the presence of uncertain disruptions and its effectiveness is verified by comparing it with the some conventional proportional-integral (PI) as well as with recently published IMC-proportional-integral-derivative (IMC-PID) and IMC-proportional integral derivative double derivative (IMC-PIDD2) controllers. The applicability of the proposed control methodology has been validated under varying supply and load current levels in presence of parametric uncertainty using a MATLAB/Simulink tool along with a low-cost microcontroller DSP F280379D based laboratory prototype.

Energy efficiency optimization for the ultra supercritical (USC) boiler-turbine unit is a major concern in the field of power generation. In order to deal with the nonlinearity and slow dynamic response problems, a new nonlinear control method is proposed which integrates internal model control (IMC) and generalized predictive control (GPC) into a unified framework. Specifically, through a long short-term memory (LSTM) neural network based IMC, the system achieves rapid convergence to the vicinity of the desired setpoint, significantly enhancing the response speed. Then, by a composite weighted human learning optimization network based nonlinear generalized predictive control (CWHLO-GPC), high-accuracy tracking performance is achieved. Finally, an example on a 1000MW USC power plant demonstrates the proposed method can achieve fast and stable dynamic response under large load variation. • A rapid changing control quantity is obtained by a LSTM neural network based IMC. • A modeling network is constructed to simulate the nonlinear dynamic process of USC. • Accurate control is achieved by an improved GPC based on the constructed models. [ABSTRACT FROM AUTHOR]

With the growing demand of low-cost transportation service, Hybrid airship plays a significant role for providing this service as a cargo nowadays. This paper deals with the controller design for winged hybrid airship with suspended payload for maintaining stability and controllability of the system. Controller design is required for the system to achieve desired tracking performance and collision avoidance for closed loop analysis. Internal Model Control (IMC) compensator is also designed to make few subsystems represented as velocity transfer function stable. The system is a small sized winged hybrid airship with attached suspended payload and having controlling maneuvers like elevator. The system taken is discussed as an approach of single body longitudinal dynamics. A Proportional-Integral-Derivative (PID) controller has been designed for pitch control of hybrid airship including collision avoidance in the pitch up and pith down path. A Hardware-In-the-Loop (HIL) solution also provided for the designed PID controller on UNO kit. Open loop and closed loop stability analysis is done for the longitudinal dynamics of winged small sized hybrid airship. Internal model compensator is required to make overall system as a stable system. A Simulink model for longitudinal dynamics of the hybrid airship with controllers and compensators is developed and result is analyzed and verified with open literature. Overshoot of u is the problem, although it settles to zero trim values within 30 sec. Except that all other parameters of longitudinal dynamics settle to equilibrium points within few seconds. Altair Embed software is used for HIL development. [ABSTRACT FROM AUTHOR]

The problem of load frequency control (LFC) for power grids has received widespread attention in power industrial control. Ensuring the stability of the frequency is the primary concern that constrains the development of the electric power system. This paper presents a novel internal model control (IMC)- proportional-integral-derivative (PID) controller design method for LFC control systems, centered on pole-zero conversion. This method aims to simplify the system model's complexity and improve the system's performance. The IMC controller is approximated as a PID series compensator (high-order PID), with exact tuning formulas provided for various scenarios. These include single-area without or with reheat turbines, hydro turbines with transient droop compensators, wind turbines, and gas turbines. The tuning formulas are characterized by a single parameter, determined under robustness constraints and integrated time absolute error (ITAE). The proposed tuning method considers the generator rate constraint (GRC) and applies to multi-area single-source and multi-area multi-source power systems. The results of the simulation confirm that the controller tuning method presented in this paper has significant advantages over the existing design methods concerning robustness and anti-interference performance.

This paper investigates integration of distributed energy resources (DERs) in microgrids (MGs) through two-stage power conversion structures consisting of DC-DC boost converter and DC-AC voltage source converter (VSC) subsystems. In contrast to existing investigations that treated DC-link voltage as an ideal constant voltage, this paper considers the non-ideal dynamic coupling between both subsystems for completeness and higher accuracy, which introduces additional DC-side dynamics to the VSC. The analysis shows parameters of the boost converter's power model that impact stability through the DC-link. Carefully selecting these parameters can mitigate this effect on stability and improve dynamic performance across the DC-link. Hence, an optimization framework is developed to facilitate in selecting adequate boost converter parameters in designing a stable voltage source converter-based microgrid (VSC-MG). The developed optimization framework, based on particle swarm optimization, considers dynamic coupling between both subsystems and is also effective in avoiding inadequate boost converter parameters capable of propagating instability through the DC-link to the VSC. Simulations are performed with MATLAB/Simulink to validate theoretical analyses.

Control of time-delay processes can be achieved by using industrial PID or implementing Internal Model based Controllers (IMC). During the last century, several methods have been proposed in the literature for tuning such controllers based on models obtained by open-loop tests. The model approximation is typically a first-order plus time-delay (FOPTD) or a delayed integration process (DIP). This paper presents a comparative analysis of popular methods used in PID, robust IMC control and Sliding Mode Control (SMC). The study includes, for each method, the analysis of the impact of model mismatch on performance, their ability to reject input and output disturbances, and their complexity. The paper provides results of numerical simulations and experiments in a cascade control loop of a pump-valve-tank system where the system is presented as two cascaded FOPTD models representing, respectively, the actuator and the tank.

The growing scale and complexity of safety-critical control systems underscore the need to evolve current control architectures aiming for the unparalleled performances achievable through state-of-the-art optimization and machine learning algorithms. However, maintaining closed-loop stability while boosting the performance of nonlinear control systems using data-driven and deep-learning approaches stands as an important unsolved challenge. In this paper, we tackle the performance-boosting problem with closed-loop stability guarantees. Specifically, we establish a synergy between the Internal Model Control (IMC) principle for nonlinear systems and state-of-the-art unconstrained optimization approaches for learning stable dynamics. Our methods enable learning over specific classes of deep neural network performance-boosting controllers for stable nonlinear systems; crucially, we guarantee $\mathcal {L}_{p}$ closed-loop stability even if optimization is halted prematurely. When the ground-truth dynamics are uncertain, we learn over robustly stabilizing control policies. Our robustness result is tight, in the sense that all stabilizing policies are recovered as the $\mathcal {L}_{p}$ -gain of the model mismatch operator is reduced to zero. We discuss the implementation details of the proposed control schemes, including distributed ones, along with the corresponding optimization procedures, demonstrating the potential of freely shaping the cost functions through several numerical experiments.

Multiloop voltage-controlled virtual synchronous generator (VSG) based control scheme is recently popular in forming stable microgrids. This scheme deploys traditional VSG (TVSG) control for power controllers in the outermost loop and proportional-integral synchronous reference frame-based voltage-current (PIVA) controllers in the inner loop (named TVSG-PIVA scheme). But, this scheme usually exhibits larger deviations and longer settling times in transient response under large active power demands. This poor transient response would further lead to unnecessary tripping which is referred to as nuisance tripping in the literature. This hampers the system’s stability even though there is no genuine fault. Thus, to address this problem, this paper proposes a modified VSG (MVSG) power controller based on adjusting the gain constant of the speed governor in the TVSG through an equalizing factor. From simulations, it is found that this MVSG supported by PIVA controllers (named MVSG-PIVA scheme) successfully avoided undesired trips under large active power demands, but, is susceptible to nuisance tripping under large reactive power demands. Thus, to effectively improve transient response and reduce the chances of nuisance trips under both large active/reactive power loads, this paper proposes a hybrid control scheme by deploying the MVSG power controller and internal model control-based VA controllers (named MVSG-IMCVA scheme). The efficacy of the proposed MVSG-IMCVA scheme is compared with the MVSG-PIVA scheme and conventional TVSG-PIVA scheme under different power factor loadings. From the results, it is proved that the proposed scheme improved the transient response and reduced unnecessary trips. Thus, the proposed modifications demonstrate the empowerment of the multiloop voltage-controlled VSG scheme, thereby ensuring system stability during dominant load changes.

This paper considers the pursuit problem of a moving target by a swarm of drones through a flexible-configuration formation. The drones are modeled by second-order systems subject to uncertain damping ratios, whereas the moving target follows a polynomial-type trajectory whose coefficient vectors are fully unknown. Due to location denial, drones cannot obtain their absolute positions, but they can obtain their positions relative to other neighboring drones and the target. To achieve a robust formation pursuit, a robust cooperative control protocol is synthesized, which comprises three key components, namely, the pseudo drone position estimator, the pseudo target position estimator, and the local internal model control (IMC) law. The pseudo drone position estimator and the pseudo target position estimator aim to recover for each drone the position of itself and the target, respectively, but are subject to some common unknown constant bias in a distributed manner. By subtracting the pseudo target position from the pseudo drone position, each drone can acquire its position relative to the target, which facilitates the design of a local IMC law to fulfill formation pursuit in the presence of system parametric uncertainties. Both pure numerical simulation and hardware-in-the-loop (HIL) simulation are performed to verify the effectiveness of the proposed control protocol.

Aiming at the problem of motor control performance degradation caused by the cross-coupling and low switching frequency condition in the high-power direct-drive permanent magnet synchronous motor (PMSM) control system, a robust current control of PMSM based on internal model control (IMC) and hybrid pulse width modulation (PWM) is proposed and applied to the control of a MW-level direct-drive PMSM in electric locomotive traction system. Firstly, combined with the characteristics of the low switching frequency of the electric locomotive inverter, a hybrid PWM strategy is adopted. Secondly, the IMC of PMSM is designed, and the IMC is adopted to solve the problems of more control parameters and cross-coupling of direct-drive PMSM in the d-q axis under low switching frequency, which improves the robustness of the whole locomotive system. Finally, the experiments have been carried out on a 1.2 MW direct-drive PMSM for traction system in electric locomotive, the correctness and effectiveness of IMC and hybrid PWM strategy are verified.

Multilevel buck converter has attracted much attention in power electronic systems for their advantages of low switching voltage stress, small filter size and easy capacity expansion. However, this kind of converter has the characteristics of multivariable, strong coupling and nonlinearity, which challenges the voltage balance of flying capacitor and the stability of output voltage. Meanwhile, a large number of electronic loads are connected to the multilevel buck converter. These loads are usually regarded as constant power loads (CPLs) with negative impedance characteristics, which seriously degrades the stability of the power system. This paper proposes an inverse decoupling internal model control strategy for a multilevel buck converter with CPL. A nonlinear mathematical model of the multilevel buck converter with CPL is built, and the reversibility of the model is analyzed based on the inverse system theory. The inverse system expression is derived, and the model is linearized and decoupled into multiple pseudo-linear subsystems, which offsets the effect of the negative impedance characteristics. By selecting filters, internal model controllers are designed for the pseudo-linear subsystems. Furthermore, the stability and robustness of the control system are explored. Compared with other control methods, experimental results show that the proposed control strategy has better dynamic regulation performance and stronger robustness against disturbances.

With the aim of attenuating thrust ripples in ultraprecision air-bearing linear feed systems, a simple and effective internal model control (IMC) system is herein presented based on a modified modeling and identification method of permanent magnet linear synchronous motors (PMLSMs). First, flux linkage equations were used to describe the volt–ampere characteristics of PMLSMs and provide a thrust expression in a differential form based on the principle of virtual work. Then, an analytical formula was obtained through derivation based on the condition of field-oriented control. On this basis, an IMC compensator was designed using an inverse model to attenuate nonlinear thrust effects, and an extended Kalman filter (EKF) was adopted to estimate the actual current in an analog linear amplifier. The boundedness of the nonlinear system was analyzed based on the convergence condition; furthermore, the stability of the proposed IMC compensator with EKF could be guaranteed. Then, an accurate model and thrust parameters were obtained using an identification experiment on an air-bearing linear platform driven by a linear analog amplifier. To demonstrate the coupling effect of current on thrust and confirm the effectiveness of the proposed method, both simulations and experiments were performed at a uniform velocity under extra loads of different weights; then, an extended state observer (ESO) was introduced as a comparative method. Finally, the results of the following error indicated that the proposed method demonstrated improved performance in terms of overcoming the influence of nonlinearity and that it results in smooth velocities in steady states. • An effective and simple internal model control system was proposed based on a modified modeling method of PMLSMs. • An analytic thrust's formula was obtained through derivation based on the flux linkage equations of field-oriented control. • An IMC compensator was designed to attenuate nonlinear thrust and anEKF was used to estimate the current in the amplifier. • The experimental and simulation results showed the proposed method has great performance in overcoming the velocity ripples. [ABSTRACT FROM AUTHOR]

In this paper, we present a new automatic tuning methodology for proportional-integral-derivative-acceleration controllers. In particular, a (possibly high-order) model of the process is obtained by means of a relay-feedback test. Then, the four parameters of the controller are determined by approximating the general feedback internal model controller with a truncated Maclaurin series. In this context, the user can select a parameter that determines the speed of the response of the closed-loop system and implicitly handles the trade-off between aggressiveness and robustness. It is shown that the additional acceleration action allows an improvement of the performance with respect to a traditional proportional-integral-derivative controller and represents an effective solution for the control of high-order systems. [ABSTRACT FROM AUTHOR]

Concerning global warming, an energy-efficient power source must produce low or no pollutant emissions and provide an unlimited fuel supply. Proton Exchange Membrane fuel cell (PEMFC) is an electrochemical device that transforms chemical energy into electrical energy. The performance and durability of PEM fuel cells are affected by voltage reversals and fuel starvation. Oxygen Excess Ratio (OER) is a crucial factor in controlling the fuel starvation of the PEMFC system. First, this work identified the PEMFC as an integer order and fractional-order first order plus time delay models using the predictor error method and Grunwald–Letnikov simulation method based on a trust-region-reflect algorithm, respectively. Fractional order models more accurately represented the PEM fuel cell system dynamics. Then, robust fractional filters cascaded with PID controllers based on the Internal Model Control scheme (IMC) are designed for identified integer and fractional order models to regulate the OER by compressor voltage manipulation. The genetic Algorithm (GA) optimization technique is used to find the optimal fractional filter tuning parameters. The proposed controller's performance regarding Integral Absolute Error (IAE) and Total Variance (TV) is analyzed. Furthermore, the robustness of a perturbed plant and fragility with perturbed controllers are elucidated. The results show that a fractional filter cascaded with fractional order PID controller improves the performance compared to a fractional filter cascaded with integer order PID controllers. [ABSTRACT FROM AUTHOR]

A multi-degree-of-freedom (multi-DOF) control method is proposed in this paper for the optoelectronic platform affected by internal and external disturbances. First, internal model control (IMC) is used to track the desired signal, and combined with radial basis function neural network (RBFNN)-based sliding mode control (SMC) to compensate for friction torque and weaken model uncertainty. Then, linear active disturbance rejection control (LADRC) is introduced to observe and compensate for sensor noise as well as external unknown disturbances, so that the optoelectronic platform can operate under complex working conditions. The input and disturbance sensitivity functions in a pure feedback control system cannot reach their minimum values in the same frequency band, so there is an inherent contradiction between their tracking and disturbance rejection performance. Combining IMC-SMC-RBFNN with LADRC as a multi-DOF controller can guarantee both tracking and disturbance rejection performance. Lyapunov theory and Barbalat lemma prove the asymptotic stability of the control system. Simulations show that the multi-DOF controller has a good control effect under the mixed disturbances such as parameter perturbation, friction torque and sensor noise, which has reference value for the development of practical optoelectronic platform systems. [ABSTRACT FROM AUTHOR]

Traditional sliding mode control tends to generate big jitters and large control gains. In this paper, a sliding mode PI hybrid control strategy based on a new reaching law is proposed. Based on the traditional exponential reaching law, a hybrid control strategy based on a new reaching law to address the system jiUers is designed. As the motor starts, it works together with PI regulator to reduce the starting current. Since the salient pole effect and model error affect the performance of three-phase permanent magnet synchronous motor, the decoupled current PI control strategy is proposed. The feedforward decoupling compensation is introduced in the current loop, and the parameters of the current loop are adjusted by internal model control to improve the robustness and decoupling performance of the control system. The results of the simulation and experiment show the proposed control strategy improves the control precision and stability. [ABSTRACT FROM AUTHOR]

In recent years, the use of renewable energy in power systems has increased significantly. This affects the inertia of the system. Also, the intermittent nature of renewable energy sources causes voltage and frequency fluctuations. This study suggests electric vehicles (EVs) as energy storage options for the diverse sources of an interconnected power system to resolve these issues. This paper also introduces the internal model control controller for load frequency control of an interconnected power system considering flexible AC transmission system and energy storage devices. The present study considers a two-area interconnected power system with thermal, hydro, and gas-generating units. The gain of the proposed controller is optimized using the particle swarm optimization technique. The advantages of the proposed controller have been highlighted by analyzing the results with conventional proportional–integral–derivative and proportional–integral–derivative with filter controller. The model includes superconducting magnetic energy storage (SMES), capacitive energy storage (CES), and redox flow batteries to support the voltage and frequency changes. A static synchronous series compensator compensates the tie-line. The performance of the SMES and CES units is compared with the proposed EVs used as energy storage units in this paper. The simulation results show that system performances improve significantly in the presence of the proposed energy storage unit. The behavior of the proposed controller is also analyzed under equal and unequal apf values. Finally, the sensitivity of the proposed controller is examined by varying the system parameters in a wide range. [ABSTRACT FROM AUTHOR]

A suspension flux internal model control method is proposed to address the problem of the strong coupling of a single-winding bearingless flux-switching permanent magnet motor leading to a significant ripple of the rotor radial displacement. Firstly, based on air-gap magnetic field modulation theory, the stator flux equation considering rotor dynamic eccentricity is established to reveal the relationship between the eccentric rotor and the magnetic field. Secondly, according to the dynamic characteristics of the motor and the variation law of the air-gap magnetic field, the suspension-plane flux is substituted into the rotor dynamic model, and the suspension flux-dynamics internal model and corresponding output are constructed, respectively. Finally, a complete control strategy is established, and the rotor is stably suspended by PWM control. The simulation and experimental results show that the proposed method has better steady-state and dynamic performance than traditional PID control, and the maximum radial displacement ripples of the rotor are reduced by 53% and 50% in steady-state and dynamic operation. [ABSTRACT FROM AUTHOR]

Pulp batch cooking is performed in a sealed high-temperature and high-pressure digester and is a complex black-box process. Based on the analysis of the mechanism of batch cooking, a model with nonlinear characteristics was established. To optimize the nonlinear part of the model, function fitting and numerical approximation were used for the simple cooking process. A novel fractional-order model is proposed to solve the problems of model inaccuracy and uncertain system parameters during batch cooking. For fractional-order systems, a two-degree-of-freedom fractional-order PID (FO-PID) controller based on internal model control is designed. The internal model control simplifies the number of parameter settings of the fractional-order controller and allows accurate adjustment of the adjustable parameters of the FO-PID controller based on the maximum sensitivity and stability margin. The simulation results show that the fractional-order internal model control in the batch cooking process is superior to the integer-order control in terms of overshoot, response speed, and robustness. Compared to internal model control, it provides better setpoint tracking dynamics and better robustness to system parameter disturbances. The practical application results in paper mills are given to illustrate the effectiveness of the method.

This article presents the analysis and design of a cascade controller for regulation of output voltage in a non-ideal boost power converter. Non-ideal boost power converter is a well-known nonlinear non-minimum phase system. Hence it is chosen to show the ability of the proposed control technique. The proposed technique involves sliding mode current loop and internal model-based voltage loop. Cascade controller based non-ideal boost power converter exhibits fast dynamic response, excellent tracking, and rejection of disturbances even though input voltage, load and parameters of the converter are uncertain. Validation on an experimental prototype followed by detailed analysis of results is presented. [ABSTRACT FROM AUTHOR]

Designing an effective, robust controller is vital for regulating system frequency corresponding to the load demand variations in a traditional interlinked power system. Hence, load frequency control plays a critical role in countering load disturbances and minimizing unscheduled power flow between interlinked areas. This paper proposes a novel teaching-learning optimization (TLO) based dual-loop load frequency control approach aided by fractional-order proportional-integral-derivative controller (FO-PID). The inner control loop of the presented method employs internal model control and model approximation. On the other hand, the external loop uses a TLO-tuned FO-PID controller to improve the outcomes of the proposed approach. The proposed method is validated using a 1-area multi-stage reheat hydrothermal power system (RHTPS), 2-area reheat thermal power system (RTPS), and 2-area multi-stage RHTPS. The robustness of the proposed method is demonstrated by executing sensitivity analysis. It is established from the simulation results that the proposed approach enhances the dynamic response of the test systems substantially. [ABSTRACT FROM AUTHOR]

This article proposes an enhanced control of integrating cascade processes. The importance of the scheme shows by controlling a double integrating process with time delay under significant parametric uncertainties and load disturbances. A novel design is proposed based on the Smith predictor principle and uses a fractional-order internal model controller in the outer loop. The required fractional-order tuning parameter follows the desired gain and phase margins. At the same time, another tuning parameter, such as the fractional filter's time constant, is calculated from the desired performance constraint. Numerical analysis and comparison are performed to showcase the feature of the hybrid structure. The simulation results show that the fractional-order internal model controller–based scheme provides enhanced tracking and faster regulation capabilities and works well under nominal and parameter uncertainty conditions. [ABSTRACT FROM AUTHOR]

Summary: A controller design method based on effective open‐loop transfer function (EOTF) and internal model control (IMC) is proposed for square multivariable systems with uncertain parameters. In this paper, two equivalent substitutions are used to deal with the multivariable system with uncertain parameters. In the first equivalent substitution, the EOTF method is used to solve the coupling problem of the system. In order to prevent the interval explosion problem of parameters, the affine algorithm is adopted in the decoupling process to determine the value region of system parameters. Then, the multivariable system with uncertain parameters is transformed into a set of single‐variable system with uncertain parameters. The second equivalent substitution is based on Kharitonov's theorem to process every single variable system with uncertain parameters and replace it by a set of boundary models. Meanwhile, in order to ensure that the tuning controller can not only make the system stable but also meet a certain degree of robustness, based on the idea of IMC, the maximum sensitivity is introduced to design the PID controller. Finally, numerical simulation results are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, an optimized Genetic Algorithm (GA) based internal model controller-proportional integral derivative (IMC-PID) controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase (NMP) behavior due to the presence of a right-half plane zero (RHPZ). This RHPZ limits the dynamic performance of the converter and leads to internal instability. The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameter ?. Also, this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop control. The conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic algorithm. Computed results suggested that GA-IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work, a current mode control has been proposed for output voltage regulation of DC–DC boost converter. The proposed controller has a cascade control structure with two feedback loops. And the internal model control scheme has been used in both the control loops. The advantageous feature lies in so as to adjust the performance and robustness of the closed-loop system as it has only one tuning parameter. The performance of the proposed internal model control based current mode control of DC–DC boost converter has been evaluated in hardware setup for set point as well as load disturbance response. The load disturbance response has been analyzed by considering random changes in input voltage and load. The faster transient response with a low-rise time and settling time has been observed in the proposed current mode control in comparison with voltage mode control as well as recently reported work. The robustness analysis of the proposed schemes has also been conducted using the small gain theorem and is further validated through hardware experiment. The proposed scheme is robustly stable up to 23% simultaneous change in inductance, capacitance and resistance.

In this research, control of the Direct Current motor is accomplished using a neuro controller in the Internal Model Control scheme. Two Feed Forward Neural Networks are trained using historical input-output data. The first neural network is trained to identify the object's dynamic behavior, and that model is used as an internal model in the control scheme. The second neural network is trained to obtain an inverse model of the object, which is applied as a neuro controller. Experiment is conducted on the real direct current motor in laboratory conditions. Obtained results are compared to those achieved by implementing the Direct Inverse Control method with the same neuro controller. It was demonstrated that the proposed control method is simple to implement and the system robustness is achieved, which is a great benefit, aside from the fact that no mathematical model of the system is necessary to synthesize the controller of the real object.

Among hybrid energy storage systems (HESSs), battery-ultracapacitor systems in active topology use DC/DC power converters for their operations. HESSs are part of the solutions designed to improve the operation of power systems in different applications. In the residential microgrid applications, a multilevel control system is required to manage the available energy and interactions among the microgrid components. For this purpose, a rule-based power management system is designed, whose operation is validated in the simulation, and the performances of different controllers are compared to select the best strategy for the DC/DC converters. The average current control with internal model control and real-time frequency de-coupling is proposed as the most suitable controller according to the contemplated performance parameters, allowing voltage regulation values close to 1%. The results are validated using real-time hardware-in-the-loop (HIL). These systems can be easily adjusted for other applications such as electric vehicles.

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. [ABSTRACT FROM AUTHOR]

Control of MIMO systems offers a challenging problem due to the cross coupling effects present between the inputs and the outputs of MIMO systems. In order to achieve an efficient control decouplers are introduced which eliminate these cross-coupling effects present in MIMO systems. With decouplers properly designed, it is possible to derive control inputs for fully-actuated and over-actuated MIMO systems to achieve reference tracking of the individual outputs. However, the reference tracking for individual outputs is almost unachievable in under-actuated MIMO systems with decoupling control methods. In dealing with this, the present work proposes an internal model control (IMC) applicable as appropriate to all classes of MIMO systems without incorporating any decoupling technique. This paper extends with two unique design methods of the IMC technique. These proposed methods enable one to attain perfect reference tracking of the individual outputs even in presence of the cross-coupling present in the MIMO systems. The conditions for the perfect reference tracking of multi outputs for under-actuated MIMO systems are derived. Different examples are considered to test the efficiency of the methods. The proposed methods are implemented on an experimental test set-up of highly non-linear and unstable cart-inverted pendulum system. The reference tracking goal and disturbance rejection capability of the control scheme are examined well in real-time. The experimental results are portrayed to establish the efficacy of the theoretical claim made. [ABSTRACT FROM AUTHOR]

In a thermal plant, the combustion system of the coal-fired boiler is a nonlinear time-varying system, which leads to undesired responses, if traditional proportional-integral-derivative controllers are utilized. Internal process delay is an important characteristic of the steam pressure in the boiler of coal-fired power plants, which affects the closed-loop dynamics. To compensate for this significant delay and reach the desired performance, a novel control strategy based on a combination of an optimal fractional-order proportional-integral-derivative (OFOPID) controller with a Smith predictor (SP) structure is suggested in this paper that achieves the desired control performance required for the optimal operation of the boiler. The simulation results of a coal-fired power plant boiler with the power of 300 MW show that the performance is improved considerably by having lower overshoot and lower rise and settling times, as well as a lower mean square error during the operation of the power plant Boiler. [ABSTRACT FROM AUTHOR]

Gestational weight gain outside of Institute of Medicine guidelines poses a risk to both the mother and her unborn child. Behavioral interventions such as Healthy Mom Zone (HMZ) that aim to regulate gestational weight gain require self‐monitoring of energy intake, which is often significantly under‐reported by participants. This article describes the use of a control systems approach for energy intake estimation during pregnancy. It relies on an energy balance model that predicts gestational weight based on physical activity and energy intake, the latter treated as an unmeasured disturbance. Two control‐based observer formulations relying on Internal Model Control and Model Predictive Control, respectively, are presented in this article, first for a hypothetical participant, then on data collected from four HMZ participants. Results demonstrate the effectiveness of the method, with generally best results obtained when estimating energy intake over a weekly time period. [ABSTRACT FROM AUTHOR]

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Since the hysteresis property inherently exists in the rubber material, it is necessary to deal with the control issues for the micro‐hand by considering the hysteresis property. Therefore, in this paper, the robust tracking control for the micro‐hand systems is discussed from the aspect of the Prandtl–Ishlinskii hysteresis property which is more applicable for the real applications. Firstly, a new model is obtained by combining the dynamic model of the micro‐hand with Prandtl–Ishlinskii hysteresis property. Secondly, a new stability condition based on bounded input and bounded output stability is proposed for the Prandtl–Ishlinskii hysteresis modeled micro‐hand system from two different cases. Thirdly, by designing the robust controllers based on the internal model control method, the tracking performance can be improved by eliminating the effect from the disturbance. Finally, simulation is used to further demonstrate the effectiveness of the proposed design scheme. [ABSTRACT FROM AUTHOR]