Enhanced Disturbance Rejection Research Articles

Continuous-time robust frequency regulation in isolated microgrids with decentralized fixed structure μ-synthesis and comparative analysis with PID and FOPID controllers

Isolated microgrids, which are crucial for supplying electricity to remote areas using local energy sources, have garnered increased attention due to the escalating integration of renewable energy sources in modern microgrids. This integration poses technical challenges, notably in mitigating frequency deviations caused by non-dispatchable renewables, which threaten overall system stability. Therefore, this paper introduces decentralized fixed structure robust μ-synthesis controllers for continuous-time applications, surpassing the limitations of conventional centralized controllers. Motivated by the increasing importance of microgrids, this work contributes to the vital area of frequency regulation. The research challenge involves developing a controller that not only addresses the identified technical issues but also surpasses the limitations of conventional centralized controllers. In contrast to their centralized counterparts, the proposed decentralized controllers prove more reliable, demonstrating enhanced disturbance rejection capabilities amidst substantial uncertainties, represented through normalized co-prime factorization. The proposed controllers are designed using the D-K iteration technique, incorporating performance weight filters on control actions to maintain low control sensitivity and ensure specific frequency band operation for each sub-system. Importantly, the design considers unstructured uncertainty up to 40%, addressing real-world uncertainties comprehensively. Rigorous robust stability and performance tests underscore the controller's superiority, demonstrating its robustness against elevated uncertainty levels. Robust stability is verified for all controllers, with the proposed controller showing robust stability against up to 171% of the modeled uncertainty. Notably, the controller boasts a fixed structure with lower order compared to other H-infinity controllers, enhancing its practical implementation. Comparative analyses against Coronavirus Herd Immunity Optimizer tuned Proportional-Integral-Derivative (CHIO-PID) controller and CHIO tuned Fractional-Order Proportional-Integral-Derivative (CHIO-FOPID) controller further validate the superior performance of the proposed solution, offering a significant step towards ensuring the stability and reliability of microgrid systems in the face of evolving energy landscapes.

Fractional-based iterative learning-optimal model predictive control of speed induction motor regulation for electric vehicles application

Introduction. A new control strategy based on the combination of optimal model predictive control (OMPC) with fractional iterative learning control (F-ILC) for speed regulation of an induction motor (IM) for electric vehicles (EVs) application is presented. OMPC uses predictive models to optimize speed control actions by considering the dynamic behavior of the IM, when integrated with the F-ILC, the system learns and refines the speed control iteratively based on previous iterations, adapting to the specific characteristics of the IM and improving performance over time. The synergy between OMPC and F-ILC named F-ILC-OMPC enhances the precision and adaptability of speed control for IMs in EVs application, and optimizes the energy efficiency and responsiveness under varying driving conditions. The novelty lies in the conjunction of the OMPC with the ILC-based on the fractional calculus to regulate the speed of IMs, which is original. Purpose. The new control strategy provides increased performance, robustness and adaptability to changing operational conditions. Methods. The mathematical development of a control law that mitigates the disturbance and achieves accurate and efficient speed regulation. The effectiveness of the suggested control strategy was assessed via simulations in MATLAB conducted on an IM system. Results. The results clearly show the benefits of the F-ILC-OMPC methodology in attaining accurate speed control, minimizing steady-state error and enhanced disturbance rejection. Practical value. The main perspective lies in the development of a speed control strategy for IMs for EVs and the establishment of reliable and efficient electrical systems using ILC-OMPC control. This research has the prospect of a subsequent implementation of these results in experimental prototypes. References 24, tables 2, figures 9.

Design and Implementation of Robust H∞ Control for Improving Disturbance Rejection of Grid-Connected Three-Phase PWM Rectifiers

In response to the high performance requirements of pulse width modulation (PWM) converters in grid-connected power systems, H-Infinity (H∞) control has attracted significant research interest due to its robustness against parameter variations and external disturbances. In this work, an advanced robust H∞ control is proposed for a grid-connected three-phase PWM rectifier. A two-level control strategy is adopted, where cascaded H∞ controllers are designed to simultaneously regulate the DC bus voltage and input currents even under load disturbances and non-ideal grid conditions. As a result, unit power factor, stable DC bus voltage, and sinusoidal input currents with lower harmonics can be accurately achieved. The design methodology and stability of the proposed controller are verified through a comprehensive analysis. Simulation tests and experimental implementation on a dSPACE 1103 board demonstrate that the proposed control scheme can effectively enhance disturbance rejection performance under various operating conditions.

Fast Terminal Sliding Mode Control of DC–DC Boost Converters With Enhanced Disturbance Rejection

Fast Terminal Sliding Mode Control of DC–DC Boost Converters With Enhanced Disturbance Rejection

Linear-Rotary Position Control System With Enhanced Disturbance Rejection for a Novel Total Artificial Heart

Linear-Rotary Position Control System With Enhanced Disturbance Rejection for a Novel Total Artificial Heart

RelaxC controller and PID for time delay systems: Experimental test results on Boiler pilot plant

In this paper a novel method of RelaxC controller design is introduced for time delay systems, offering significant implications for process industry. RelaxC’s new technology involves the use of two significant concepts: generating functions and reactivity time. The designed RelaxC controller is applied to First Order Plus Dead Time (FOPDT), Second Order Plus Dead Time (SOPDT), second order integrating, multivariable and nonlinear systems using MATLAB simulations. The key parameters of RelaxC are set, by the designer’s expertise. Proportional Integral Derivative (PID) control is utilized to compare results in particular cases. This method addresses inherent limitations of traditional PID. The RelaxC controller effectively mitigates the adverse effects of time delays, providing more precise setpoint tracking, enhanced disturbance rejection and reduced control effort. The findings emphasize potential of adopting the RelaxC controller for many industrial applications. The experimental results of a real-time boiler pilot plant for temperature and drum level control are presented to demonstrate the efficacy of the proposed method.

Improved fractional order speed controller with non-linear VSI-IM model to enhance the load disturbance capability

The conventional PI-based speed controllers are susceptible to speed tracking error and limited load rejection capability. This paper presents the high-performance fractional-order PI speed controller (FOPI) for field oriented control of induction motor (FOC-IM) drives with enhanced disturbance rejection capability. The design of FOPI involves third-order voltage source inverter fed induction motor (VSI-IM) model identification, fitting it into the required phase margin and gain margin constraints and Oustaloups fractional element approximation. The identification algorithm using the hardware-in-loop system is provided. The non-linear integer order VSI-IM model improves the tracking and dynamic performance of the drive. The designed FOPI speed controller performance is compared with the literature’s existing FOPI controller design methods. The experimental analysis found that, in terms of speed tracking, parameter variations, inertia variations, and disturbance rejection capabilities, the suggested controller is more effective and resilient than existing tuning approaches.

Composite Antidisturbance Control for Non-Gaussian Stochastic Systems via Information-Theoretic Learning Technique.

In this article, a novel composite hierarchical antidisturbance control (CHADC) algorithm aided by the information-theoretic learning (ITL) technique is developed for non-Gaussian stochastic systems subject to dynamic disturbances. The whole control process consists of some time-domain intervals called batches. Within each batch, a CHADC scheme is applied to the system, where a disturbance observer (DO) is employed to estimate the dynamic disturbance and a composite control strategy integrating feedforward compensation and feedback control is adopted. The information-theoretic measure (entropy or information potential) is employed to quantify the randomness of the controlled system, based on which the gain matrices of DO and feedback controller are updated between two adjacent batches. In this way, the mean-square stability is guaranteed within each batch, and the system performance is improved along with the progress of batches. The proposed algorithm has enhanced disturbance rejection ability and good applicability to non-Gaussian noise environment, which contributes to extending CHADC theory to the general stochastic case. Finally, simulation examples are included to verify the effectiveness of theoretical results.

Adaptive Sensorless PI+Passivity-Based Control of a Boost Converter Supplying an Unknown CPL

This paper presents an adaptive control to stabilize the output voltage of a DC–DC boost converter that feeds an unknown constant power load (CPL). The proposed controller employs passivity-based control (PBC), which assigns a desired system energy to compensate for the negative impedance that may be generated by a CPL. A proportional-integral (PI) action that maintains a passive output is added to the PBC to impose the desired damping and enhance disturbance rejection behavior, thus forming a PI+PBC control. In addition, the proposed controller includes two estimators, i.e., immersion and invariance (I&I), and disturbance observer (DO), in order to estimate CPL and supply voltage for the converter, respectively. These observers become the proposed controller for an adaptive, sensorless PI+PBC control. Phase portrait analysis and experimental results have validated the robustness and effectiveness of the adaptive proposed control approach. These results show that the proposed controller adequately regulates the output voltage of the DC–DC boost converter under variations of the input voltage and CPL simultaneously.

Extended State-Based OSG Configurations for SOGI PLL With an Enhanced Disturbance Rejection Capability

Changes in the orthogonal signal generator (OSG) configuration of the standard second-order generalized integrator-based phase-locked loop (S-SOGI PLL) have shown to offer an improved low-voltage ride-through capability. However, the resulting PLLs: highpass SOGI (H-SOGI) and lowpass SOGI (L-SOGI) PLLs have no dc-offset estimation capability and lack robustness to disturbances. Therefore, this article focuses on maximizing the merits of H-SOGI and L-SOGI PLLs for grid and industrial applications by incorporating dc-offset estimation and enhancing their disturbance rejection capability. Accordingly, two varieties of SOGI PLLs, namely: extended state highpass SOGI (ES-H-SOGI) and extended state lowpass SOGI (ES-L-SOGI) PLLs are proposed. In the proposed PLLs, states of the OSGs are extended to achieve dc-offset estimation and rejection, while frequency-adaptive implementation of the moving average filter (MAF) is developed to achieve complete harmonic rejection at off-nominal frequencies of the input voltage. To alleviate the undesirable effect of the MAF in terms of the PLL's slow transient response, frequency-adaptive implementation of a phase-lead compensator is introduced. In this article, design guideline that achieves an optimal tradeoff between disturbance rejection and dynamic performance in the ES-H-SOGI and ES-L-SOGI PLLs is presented. Finally, experimental comparison between the proposed ES-H-SOGI and ES-L-SOGI PLLs and their ES-S-SOGI PLL counterpart is carried to show that the proposed PLLs outperform the ES-S-SOGI PLL in terms of dynamic performance while achieving enhanced disturbance rejection capability.

Fast Harmonic compensation in hybrid HVDC offshore system

Hybrid HVDC systems have been proposed as an alternative for nominal VSC-Based HVDC for offshore applications. Hybrid HVDC systems consist of an offshore power station composed of the connection of high-power diode rectifiers in series with a fractional power VSC-HVDC. This hybrid configuration allows large power transfer from offshore sites, with the added robustness, simplicity and efficiency of uncontrolled rectifiers. In this research, a robust and fast-acting controller, the Two Degrees of Freedom Internal Model controller (2DF-IMC), is used to control the active power filter features of the fractional-power VSC-HVDC system, resulting in a much faster overall THD reduction in the offshore AC currents in dynamic conditions (i.e. time-varying wind power) when compared with standard active power filter controllers. This improvement is the direct consequence of the fast closed-loop dynamics of the 2DF-IMC controller that do not require filtering stages. Additionally, the increased closed-loop response time did not affect the overall robustness of the control system, thanks to the enhanced disturbance rejection capabilities of the 2DF-IMC configuration.

Adaptive Uncertainty Estimator-Based Sliding Mode Control for a Spherical Robot: Methodology and Verification

Abstract This paper presents an adaptive uncertainty estimator-based proportional-integral (PI) type sliding mode control for a spherical robot with structural uncertainties and external disturbance. By projection method, the 3D robot dynamic model with structural asymmetry is decoupled into the balance subsystem and velocity subsystem, and the kinetics equations are established based on Newton–Euler's law. To estimate the unknown structural dynamics in the balance subsystem and external disturbance in the velocity subsystem, adaptive law containing both control and estimation error information is proposed for the uncertainty estimator (UE) design. Then, an uncertainty estimator-based PI type uncertainty estimator sliding mode controller (UESMC) is introduced for balance and velocity control, leading to enhanced disturbance rejection capability and a reduced steady-state error. Simulations and experiments on a real spherical robot are conducted to demonstrate the efficacy of the proposed control strategies.

Uncertainty and disturbance estimator-based resilient tracking control design for fuzzy semi-Markovian jump systems

The focus of this paper is on solving the state tracking control problem for a class of fuzzy semi-Markovian jump systems with the aid of fuzzy modeling approach. Besides, the impact of both unexpected disturbances and uncertainties in fuzzy semi-Markovian jump systems is considered. In particular, the nonlinearity in the addressed system is represented by the T-S fuzzy model, wherein the disturbances and uncertainties are estimated by precisely considering uncertainty and disturbance estimator (UDE)-based control approach. Whilst, the desired fuzzy rule-based mode-dependent control law is formulated by exploiting the parallel distributed compensation strategy and estimated output of disturbances and uncertainties. In the proposed tracking control scheme, the resilient strategy is considered to overcome the impact of gain perturbations. Further, in terms of LMIs, a set of sufficient constraints is derived in accordance with the appropriate selection of mode-dependent fuzzy rule-based Lyapunov function. Under which, the asymptotic tracking and enhanced disturbance rejection performances are guaranteed for the system under consideration. Notably, the desired control gain matrices are determined by solving the derived sufficient conditions via MATLAB LMI toolbox. Conclusively, a single-link robot arm model is adopted to justify the practicability and efficacy of the theoretical findings.

Constrained Modulated Model Predictive Control for a Three-Phase Three-Level Voltage Source Inverter

In the last decade, model predictive control (MPC) has been widely studied in power converters, such as voltage source inverters (VSIs). Unfortunately, MPC often presents a high computational burden that limits their applicability, especially when driving multilevel inverters (MLIs) because of their higher number of switching combinations than two-level inverters. As a result, some strategies have been developed to reduce the computational complexity of MPC. One of the most relevant is the use of artificial neural networks (ANNs) to approximate the behavior of an MPC. However, ANNs require to be evaluated at bounded inputs. Otherwise, their response cannot be guaranteed to be a good approximation of the controller they learned from. Furthermore, when driving an LC-filtered VSI, the inductor current can present high peaks due to the cross-coupling effect between the inductor and the capacitor. These current peaks can cause physical damages and loss of performance of an ANN-emulated MPC. This paper presents a new constrained modulated MPC (M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PC), better suited for ANN emulation, to overcome these issues. The proposed strategy evaluates the cost function once per switching region, allowing easy and intuitive constraint inclusion. Additionally, an overmodulation stage is used to handle negative duty cycles and enhance disturbance rejection. Finally, the proposal is validated through simulations, using MATLAB-Simulink, taking into account different load conditions. Simulations show that the constrained M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PC keeps the inductor current below its desired limit while having a good performance (low harmonic distortions and fast dynamics) even when the inverter operates near its boundaries.

Adaptive Second-Order Sliding Mode Control for Grid-Connected NPC Converters With Enhanced Disturbance Rejection

In this article, a two-stage control scheme consisting of an adaptive-gain second-order sliding mode (SOSM) controller and a switched high-gain observer (HGO) is proposed for the three-level neutral-point-clamped (NPC) converter. The adaptive-gain SOSM control method is applied both in the voltage regulation loop and instantaneous power tracking loop, thus, the boundary of the disturbance derivative does not need to be known <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> . Compared with the fixed-gain SOSM, it provides a faster dynamic and a better steady-state response for the NPC converter. On the other hand, the conventional disturbance compensation observer used in the power system suffers from the adverse effects of measurement noise, which limits the performance of the observer. A switched HGO is combined with the adaptive-gain SOSM controller in the voltage regulation loop to address this issue. By using a switched observer gain, the switched HGO greatly diminishes the performance degradation induced by the inevitable measurement noise. Finally, several experiments between the representative extended state observer-based SOSM control scheme and the proposed control method are carried out for a comparison. The results demonstrate the feasibility and effectiveness of the proposed approach.

Neural network-based robust integral error sign control for servo motor systems with enhanced disturbance rejection performance

Uncertain dynamics and unknown time-varying disturbances always exist in servo systems and deteriorate tracking accuracy significantly. To tackle the problem, this paper presents a novel adaptive robust control scheme based on neural networks and the robust integral of the sign of the error (RISE) method. In the proposed scheme, a new neural network compensator is developed, where a reference-driven neural network and an error-driven neural network are employed to compensate for uncertain system dynamics and unknown time-varying disturbances, respectively. And an RISE-based robust feedback controller is designed to suppress uncompensated dynamics. Asymptotic tracking control of the servo system with uncertain dynamics and unknown time-varying disturbances is guaranteed by using the Lyapunov theory. Comparative experiments and simulations with different reference signals and various types of external disturbances were conducted based on a linear motor-driven stage. Experimental and simulational results verify the superior tracking performance and powerful disturbance rejection ability of the proposed method.

A generalized control scheme for system uncertainty estimation and cancellation

This paper addresses the control of a continuous-time system with possibly large uncertainty of unknown internal dynamics or external disturbance. A novel control scheme is proposed to estimate and cancel the system uncertainty effectively so as to enhance disturbance rejection (DR) performance. Unlike asymptotic analysis with infinite gain in the literature, the estimation transient analysis is carried out for the proposed scheme with a finite estimator gain and the precise error formulas are derived, based on a classical low-order plant description. The control performance associated with a realizable gain is quantified by tight bounds with respect to the ideal case, which enables easy parameter tuning. The necessary and sufficient condition for the internal stability of the control system is established, along with a D-decomposition method for determining the complete set of the gain intervals that could internally stabilize the plant. In the presence of measurement noise, a low-pass filter is introduced to attenuate its adverse effect. Simulations and semi-realistic experiments are performed to demonstrate the effectiveness of the proposed scheme, which shows evident improvement on DR performance over the well-known active DR control.

Cascade control for heterogeneous multirotor UAS

PurposeDespite of the numerous characteristics of the multirotor unmanned aircraft systems (UASs), they have been termed as less energy-efficient compared to fixed-wing and helicopter counterparts. The purpose of this paper is to explore a more efficient multirotor configuration and to provide the robust and stable control system for it.Design/methodology/approachA heterogeneous multirotor configuration is explored in this paper, which employs a large rotor at the centre to provide majority of lift and three small tilted booms rotors to provide the control. Design provides the combined characteristics of both quadcopters and helicopters in a single UAS configuration, providing endurance of helicopters keeping the manoeuvrability, simplicity and control of quadcopters. In this paper, rotational as well as translational dynamics of the multirotor are explored. Cascade control system is designed to provide an effective solution to control the attitude, altitude and position of the rotorcraft.FindingsOne of the challenging tasks towards successful flight of such a configuration is to design a stable and robust control system as it is an underactuated system possessing complex non-linearities and coupled dynamics. Cascaded proportional integral (PI) control approach has provided an efficient solution with stable control performance. A novel motor control loop is implemented to ensure enhanced disturbance rejection, which is also validated through Dryden turbulence model and 1-cosine gust model.Originality/valueRobustness and stability of the proposed control structure for such a dynamically complex UAS configuration is demonstrated with stable attitude and position performance, reference tracking and enhanced disturbance rejection.

Composite Robust Quasi-Sliding Mode Control of DC–DC Buck Converter With Constant Power Loads

To address the stability issues aroused by the negative-resistance effect of constant power loads (CPLs), this article proposes a composite robust discretized quasi-sliding mode control (DQSMC) scheme for stabilization of buck-converter fed dc microgrids with CPLs. In the outer control loop, a robust DQSMC voltage controller is proposed. First, a discrete integral sliding surface is designed to obtain a fast and robust dynamic response of dc-bus voltage. Then, to tackle the varying load disturbances and model uncertainties, a second-order sliding mode disturbance observer is embedded in the voltage controller for disturbance estimation and compensation. The resulting composite DQSMC scheme features enhanced disturbance rejection, inherent chattering suppression, and guaranteed dynamics. Meanwhile, a PI current controller is retained in the inner control loop to realize the current control and limitation. Robustness and stability analysis of the whole composite controller is proved to assure large-signal stability. Simulation and experimental results confirm the superiority of the presented approach.

Enhanced predictive control strategy for unstable parallel cascade processes with time delay

The dynamics of runaway processes are unstable in nature and to control such processes with measured disturbances, an advanced regulatory control scheme such as cascade control is required. In this research, a control structure is suggested based on a generalized predictor scheme for controlling unstable processes in parallel cascade control architecture. The scheme is developed with two loops. An IMC controller is designed for the inner (secondary) loop and a PID controller with a lag compensator is designed for the outer (primary) loop. Along with a servo tracking controller, the primary loop consists of a generalized predictor structure having two filters capable of providing enhanced disturbance rejection and time delay compensation. The complexity associated with the suggested predictor is lesser on account of the fact that only a single tuning parameter needs to be tuned so as to attain a trade-off between regulation capabilities and performance under uncertainties. Simulation analysis is performed on different integrating as well as unstable parallel cascade processes. Obtained performances with the devised control strategy are compared with the existing methods. Quantitative evaluation in terms of the corresponding costs for output and input are carried out. The developed predictive strategy is found to deliver enhanced closed loop performances with a lesser control cost.