Robust Model Reference Adaptive Control Research Articles

A novel strategy towards efficient and reliable electric vehicle charging for the realisation of a true sustainable transportation landscape

This paper proposes an innovative approach for improving the charging efficiency of electric vehicles (EVs) by combining photovoltaic (PV) systems with AC–DC Power Factor Correction (PFC). The proposed approach employs bi-directional power flow management within the PFC system, allowing for enhanced resource utilization and EV battery capacity under a variety of environmental circumstances. A modified Lyapunov-based robust model reference adaptive controller (M-LRMRAC) is developed to provide real-time Maximum Power Point Tracking (MPPT) for the PV array. By quickly recording the MPP, this controller skilfully adjusts to shifting radiation and temperature dynamics. A noteworthy accomplishment is that the M-LRMRAC outperforms traditional Perturb and Observe (P&O) techniques by achieving quick MPP convergence (0.54 s). Additionally, the benefits of this integrated system go beyond effective MPPT. The method achieves operating at unity power factor and reduces total harmonic distortion, which results in improved power quality when charging EV Batteries (EVB). The entire solution provided by this multifaceted architecture improves the quality of electricity delivered to EV batteries while also increasing energy efficiency. This research helps to the evolution of sustainable and dependable EV charging infrastructure by solving difficulties and optimising performance. The combination of PV systems with AC–DC PFC, aided by the M-LRMRAC technology, presents a viable route for attaining efficient, clean, and high-quality EV charging, hence supporting the shift to a greener and more sustainable transportation landscape.

A robust finite–time model reference adaptive controller for arbitrary order disturbed LTI systems

This manuscript deals with the trajectory-tracking problem for linear time-invariant systems with parameter uncertainties and time-dependent external perturbations. A robust finite-time model reference adaptive controller is proposed. In the absence of external perturbations, the proposed controller ensures finite-time convergence to zero of the tracking and parameter identification errors. In presence of time-dependent external perturbations, the tracking and parameter identification errors converge to a region around the origin in a finite time. The convergence proofs are developed based on Lyapunov and input-to-state stability theory. Finally, simulation results in an academic example and a flexible-joint robot manipulator show the feasibility of the proposed approach.

A new robust nonlinear control strategy for UIPC in isolated hybrid microgrids

This paper focuses on the control of unified interphase power controller (UIPC) in isolated hybrid microgrids (HmGs), where the UIPC is used as the main component for interconnecting of AC and DC sub-grids. The investigated HmG encompasses two AC sub-grids and one purely storage DC sub-grid (PSDC) and multiple adjustable loads. A robust nonlinear model reference adaptive control (NMRC) strategy is offered for controlling the UIPC, keeping an acceptable two-way power exchange control with uncomplicated topology. Further, a novel configuration for the DC link power converter is suggested using the dual-active-bridge topology. Also, a harmonic-based modeling method is used to model the UIPC's power converter. The proposed configuration provides bidirectional power flow, increased power density, straightforward adaptation of zero-voltage switching, and direct access to cascading and parallelism to increase the ratings and reliability of UIPC. The simulation results illustrate the feasibility of the suggested topology for isolated HmGs.

Cooperative Tracking Control of Unknown Discrete-Time Linear Multiagent Systems Subject to Unknown External Disturbances.

This article studies the tracking problem of a class of heterogeneous linear minimum-phase discrete-time multiagent systems (MASs) with unknown agent parameters in the presence of bounded disturbances. By introducing a distributed adaptive observer and a reference model, a novel framework is proposed to convert the complicated cooperative tracking problem of unknown heterogeneous MASs into a cooperative tracking problem of the reference models to the leader and a local robust model reference adaptive control problem. It is shown that under the adaptive controller designed based on the proposed framework, the tracking errors between the outputs of all the agents and the output of the leader converge to a residual set. It is also shown that the tracking errors will converge to zero asymptotically when the disturbances are absent. Compared with the existing related works, our main contribution is that the proposed framework could deal with the unknown MASs with arbitrary individual relative degrees and do not rely on any global graph information. Finally, the effectiveness of the proposed controller is illustrated by an example.

Event-triggered robust model reference adaptive control for drag-free satellite

Aiming at the requirement of bounded disturbance suppression for low-frequency space gravitational wave detection satellite, a robust model reference adaptive drag-free control scheme is proposed in this paper via linear matrix inequalities (LMIs) approach. The multivariable model reference adaptive control (MRAC) scheme is applied to the drag-free control system with parameter uncertainties, which realizes the adaptive tracking to the reference state. The LMI system is established as an adaptive compensation term, which provides robustness against nonlinear disturbances. To reduce the communication burden of the actuation information and further save the total energies, an event-triggered mechanism (ETM) is introduced, with both the actuation inputs and the adaptive laws of the feedback gains updated only at the triggering time instants. The ultimately uniformly boundedness of the closed-loop signals is proved by Lyapunov analysis, with each system state convergence. From the feasibility analysis, Zeno behavior can be further proved to be strictly excluded. The numerical simulation verifies that the proposed scheme has efficient robustness to nonlinear disturbances with low energy cost, and achieves good effect in response to the requirements of space gravitational wave detection mission.

An optimal initialisation for robust model reference adaptive PI controller for grid-tied power systems under unbalanced grid conditions

This paper presents an Optimal Robust Model Reference Adaptive Proportional–Integral controller for grid-tied power systems, which is automatically parametrised using a Genetic Algorithm. The task of choosing the adaptation rate and the controller’s initial gains set is now performed in a computational and automatic way, saving design time and ensuring satisfactory transient regimes.The use of a Genetic Algorithm for complete parametrisation of robust adaptive controllers applied to renewable energy power generation systems with LCL filter is first here explored. Five cost functions are considered in the optimisation process. A comparison of simulation results applying the optimised controller in a grid-tied Voltage Source Inverter with LCL filter points out the benefits and drawbacks of using each cost function. A framework for performance analysis and an in-depth discussion are provided. The function determined as the best one, which is integral of absolute error, is used in the controller implemented experimentally, ensuring suitable tracking of grid current references and rejection of grid voltage harmonics, even under unbalanced grid voltage conditions. An experimental comparison in a three-phase 6.75 kW power converter with the non-optimised controller is also provided, where the optimised controller obtains a reduction in the overshoot in all transient regimes and smaller tracking error, resulting in a reduction in the mean error of 14.31% and 60.30% in α and β coordinates, respectively. In addition, the optimised controller reduces total harmonic content, improving energy quality. This parametrisation procedure can be immediately extended to the control of any other power converter systems.

A hybrid robust model reference adaptive controller and proportional integral controller without reference model for partially modeled systems

SummaryThis work presents the discrete‐time stability analysis of a hybrid robust model reference adaptive controller and proportional‐integral controller (MRAC‐PI) controller using Lyapunov criterion. The control structure merges the classical PI controller with a robust model reference adaptive control, resulting in an adaptive and robust control strategy, where the gains unite both control techniques in a unique structure and it does not require the design of a reference model, being able to track straightforwardly the reference signal. The adaptive gains are updated continuously by a modified gradient algorithm regarding control action, regulation error, and the system output. The stability analysis provides the controller design constraints, while also demonstrate the tendency of regulation error to a residual set, and proves the boundedness of all closed‐loop signals. Furthermore, as the controller is robust to unmodeled dynamics, it is feasible to control partially modeled systems. Simulation results in a real‐world engineering application are presented to corroborate the robustness of this controller and show its fast response in the face of critical exogenous system perturbations.

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological, economic, and environmental benefits of photovoltaic (PV) systems have led to their widespread adoption in recent years as a source of electricity generation. However, precisely identifying a PV system's maximum power point (MPP) under normal and shaded weather conditions is crucial to conserving the maximum generated power. One of the biggest concerns with a PV system is the existence of partial shading, which produces multiple peaks in the P–V characteristic curve. In these circumstances, classical maximum power point tracking (MPPT) approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point (GMPP). To overcome such obstacles, a new Lyapunov-based Robust Model Reference Adaptive Controller (LRMRAC) is designed and implemented to reach GMPP rapidly and ripple-free. The proposed controller also achieves MPP accurately under slow, abrupt and rapid changes in radiation, temperature and load profile. Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods, i.e., ANFIS, INC, VSPO, and P&O. MPP and GMPP are accomplished in less than 3.8 ms and 10 ms, respectively. Based on the results presented, the LRMRAC controller appears to be a promising technique for MPPT in a PV system.

Self-tuning methodology for adaptive controllers based on genetic algorithms applied for grid-tied power converters

The performance and stability of adaptive controllers is highly dependent on its parameter initialization. For non-expert designers, the parametrization of these controllers can be highly time consuming and an exhausting task. In order to improve the response of adaptive controllers without needing more specialized knowledge, this work proposes a procedure for self-tuning (optimal parametrization) of direct type adaptive controllers using a genetic algorithm. The proposal does not harm any property of stability and convergence of the adaptive strategy, only adding an off-line stage of parameter selection, which is carried out in a reasonable computational time. As a case study, this self-tuning procedure is applied for initialization of nine parameters of a Robust Model Reference Adaptive Controller and Adaptive Super-Twisting Sliding Mode, a known adaptive structure from the literature, suitable for current regulation of three-phase voltage source converters operating under grid impedance variations. For comparison with the proposed self-tuning, a similar procedure using fmincon and simulated annealing algorithms are also tested. The experimental results show that the proposed procedure using Genetic Algorithm can provide lower tracking error, faster regulation dynamics and reduced settling time, leading to better performance than the same controller with parameters initialized empirically.

Performance comparison of discrete-time robust adaptive controllers for grid-tied power converters under unbalanced grids

Renewable energy generation systems largely use grid-tied power converters with LCL filters. A well-known issue in this kind of system is the resonance of the LCL filter, whose frequency is straightforwardly affected by grid condition. Variations on grid impedance tends to make the controller performance poor and until turn the closed-loop unstable. Therefore, some controllers are designed for specific operation ranges to ensure performance and global stability. However, a deep study of Model Reference Adaptive-based Controllers for this kind of issue was not conducted yet. The aim of this paper is to fit this research gap. Thus, this paper presents a performance comparison of feasible discrete-time robust adaptive controllers, based on reduced order reference model, for grid-tied power converters with LCL filter under unbalanced grid conditions, providing an assessment of the benefits and drawbacks of each considered control strategy. The evaluated control laws are: Robust Model Reference Adaptive Controller, Robust Model Reference-based Adaptive Super-Twisting Sliding Mode Controller, Robust Adaptive One Sample Ahead Preview Controller, and Robust Adaptive Proportional-Integral Controller. Through performance comparison, it can be defined what controller is more adequate in face of grid condition, taking into consideration grid-injected currents quality and design complexity of controller. Experimental results of grid-injected current control of a grid-tied 5.8 kW Voltage-Source Inverter with LCL filter considering relevant grid voltage unbalance are presented to corroborate the controllers’ performance and discuss their reference tracking response, robustness to the parametric variation, exogenous disturbance rejection, parameters adaptability, and global stability. In evaluated scenarios, Robust Adaptive Proportional-Integral controller presented slower regulation dynamics between compared adaptive structures, but reduced tracking error, as well as lower total harmonics distortion, while Robust Model Reference-based Adaptive Super-Twisting Sliding Mode Controller has the smaller overshoot in the initial transient regime, as well as the shorter transient regime.

Implementation of a novel robust model reference adaptive controller-based MPPT for stand-alone and grid-connected photovoltaic system

ABSTRACT The fast advancement of photovoltaic (PV) power generation technologies led to the integration of solar-based generation systems into several modes of transportation, including aircraft, automobiles, and trains. In these PV systems, solar irradiation levels fluctuate significantly and invalidate specific maximum power point (MPP) tracking (MPPT) control strategies, lowering the energy conversion efficiency. It is evident that the new robust model reference adaptive control (MRAC) proposed in this paper alleviates these problems by reducing tracking direction loss and oscillations near MPP. To evaluate the proposed controller’s performance, MATLAB/Simulink is utilized and compared with well-known techniques (P&O, VSPO, INC, ANFIS, and swarm-based MPPT) under three different modes, i.e. stand-alone, grid-connected, and real-time mode. The proposed scheme has tracking efficacy lies between 99.02% and 99.96% and achieved MPP in just 4 msec under highly fluctuating radiation and temperature conditions. It takes only 0.08 sec to capture the global MPP, which is on average two times faster than swarm-based global MPPT methods. Furthermore, the effectiveness is tested in a 50 kW three-phase grid-connected mode with and without cloud effects in realistic weather situations. Finally, real-time validation on the OPAL-RT simulator demonstrates the proposed technique’s practicality in real-world applications.

An exponentially convergent adaptive robust based space manipulator noise control method

Because most of the traditional nonlinear control methods are model-based control methods, it will dramatically increase the parameter identification burden of multi-rigid-body system dynamic model. Meanwhile, Unmodeled dynamics, parameter drift, model uncertainty, complex motor hysteresis characteristics, etc are unfortunately in the practical systems, which makes it very hard to accurately build the noise model and identify the model parameters. Among them, the accurate values of the viscous friction coefficient, elastic friction coefficient, the distance between the centroid and the rotation center of the connecting rod, the inertial moment and products of each joint, these exact values can hardly be obtained. In this paper, direct adaptive control and the robust model reference adaptive control based on Lyapunov direct method are adopted, which can make the noise error close to zero under the condition of parameter uncertainty and unknown nonlinear friction characteristics.

A Hybrid Robust Adaptive Sliding Mode Controller for partially modelled systems: Discrete-time Lyapunov stability analysis and application

This work presents a new discrete-time Hybrid Robust Adaptive Sliding Mode Controller, developed from the union of a Robust Model Reference Adaptive Controller, an Adaptive Sliding Mode Controller, and an Adaptive One Sample Ahead Preview Controller in an unique control structure. Robust Model Reference Adaptive Controller is an adequate direct adaptive control strategy to control partially known plants, but can present slow closed-loop response to ensure global stability. Therefore, an adaptive One Sample Ahead Preview controller is incorporated to accelerate transient regimes, once it tries to track reference signal in one sample. Furthermore, an adaptive Sliding Mode Controller is also merged in the controller structure to help controller performance in transient regime and it also improves relevantly the steady state response in a scenario of several unmodelled dynamics Stability analysis of this controller using Lyapunov criterion and its robustness proof are provided, considering the plant subjected to unmodelled dynamics, which provides controller design constraints. These proofs show the controller is globally stable, and the tracking error tends to a residual set in steady state, even in the presence of matched and unmatched dynamics. Numerical simulations of the Hybrid Robust Adaptive Sliding Mode Controller applied on an unstable nonminimum-phase plant are presented, where only part of the overall plant is take into consideration for controller design. Results corroborate the feasibility and robustness of the developed control strategy and the performance superiority when compared to an adaptive One Sample Ahead Preview controller, with a 75% tracking error reduction in a scenario of several unmodelled dynamics.

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

Lyapunov stability analysis of a robust model reference adaptive PI controller for systems with matched and unmatched dynamics

In this paper, the discrete-time Lyapunov stability analysis of a Robust Model Reference Adaptive PI (Proportional-Integral) Controller is presented. The mathematical development of this controller is grounded on Robust Model Reference Adaptive Control philosophy, which provided boundedness of all closed-loop system signals and ensures its global stability. The resulting controller shows robustness characteristics to matched and unmatched dynamics, it guarantees the convergence of adaptive gains to a solution set and the convergence of tracking error to a residual set on steady state. Besides, to implement it, the only required information about the plant are its relative degree and the signal of its gain. Simulation results of the controller are provided, applying it on an unstable nonminimum-phase plant and in a practical plant. Besides, it was also compared with a Robust Model Reference Adaptive Controller and presented higher performance.

A Direct Discrete-Time Output Feedback-based LS-RMRAC for Grid-tied Current Control Loop of a Static 3-Wire Converter under Unbalanced Grid Voltage Conditions

Nowadays, renewable energy generation is a worldwide tendency. These clean sources are generally tied to the grid by voltage-fed static converters. In this work, a direct discrete-time Output Feedback-based LS (Least Squares)-RMRAC (Robust Model Reference Adaptive Control) is proposed for grid-side current loop control of a static 3-wire converter connected to the grid through LCL filter. The proposed control method mitigates the LCL filter resonance,rejects grid disturbances without needing Resonant Controllers implementation, and deals properly with grid uncertainties and parametric variations, being suitable for grids with unbalanced voltage conditions. Simulation results of proposed controller are presented. Keywords: Robust Adaptive Control. Grid-tied converter. LCL filter.

Design of continuous-time model reference adaptive and super-twisting sliding mode controller

This paper presents a continuous-time Robust Model Reference Adaptive and Super-Twisting Sliding Mode controller and its stability analysis by means of Lyapunov stability theory. The controller law is composed by two control structures: a Robust Model Reference Adaptive Controller (RMRAC) and an Adaptive Super-Twisting Sliding Mode (STSM) Controller. The main benefit of this novel control algorithm is to present, simultaneously, high robustness and fast dynamic response, which are conflicting with each other in conventional adaptive algorithms. Furthermore, as the STSM Controller is also adaptive, the dynamic response has relevant chattering mitigation without additional efforts on controller design, implementation, or execution. Besides, the union of the STSM with RMRAC also improved sliding accuracy in steady state. Thereby, in steady state, the STSM control contribution is almost zero, which avoids the chattering phenomenon, once it acts only in the transient regimes. The stability and robustness analysis of the control structure are presented, in continuous-time, considering the overall plant, that is, in presence of matched and unmatched dynamics. The continuous-time stability analysis is important in an adaptive system, since it features an intermediary step for control system stability analysis in discrete-time and its application in real plants. In addition, to present the feasibility and benefits of the proposed controller, simulations results of two case studies are presented: one is the controller application in an unstable non-minimum phase plant, and the second is its application for current regulation of a single-phase grid-tied power converter with an LCL filter. Moreover, to corroborate the robustness and tracking performance of the proposed controller a comparison with an adaptive first order Sliding Mode is also presented.

Secure tracking control against sensor and actuator attacks: A robust model-reference adaptive control method

This paper is concerned with secure tracking control problems for cyber-physical systems subjected to a class of sensor and actuator attacks via the model-reference control techniques. The considered attack signals are the unknown bounded signals generated from any linear or nonlinear finite-L2-gain exogenous dynamical system. The auxiliary outputs produced from a high-gain approximate differentiator are first used in co-design for the inputs of the systems and introduced filter, so that the matching condition on the system input and output matrices in the existing results is relaxed. Furthermore, with the aid of the auxiliary outputs, attack’s property and small-gain control methods, a novel model-reference controller with a robust adaptive attack compensator is proposed, such that (a) the tracking error converges to a small set around zero where the set bound can be adjusted by the design parameters, and (b) the desired disturbance attenuation performance is obtained. Different from the existing results, the developed one not only compensates the effect of the attacks automatically by online adjusting the adaptive parameter, but also improves the robustness against the attacks efficiently. Finally, the developed method is validated by a simulation example.

A robust adaptive One Sample Ahead Preview controller for grid-injected currents of a grid-tied power converter with an LCL filter

This paper presents the development of a discrete-time Robust Adaptive One Sample Ahead Preview controller, based on the combination of a Robust Model Reference Adaptive Controller (RMRAC) with the One Sample Ahead Preview controller (OSAP), which is a particular case of the Deadbeat controller. This control structure is applied to grid-side current control of a grid-tied voltage-source inverter (VSI) with an LCL filter. The developed controller is robust enough to be designed considering the LCL filter as a first order model, which is commonly modelled as a third order transfer function, considering the neglected dynamics as unmodelled dynamics on controller design thanks to its adaptive identifier, which is a modified Gradient algorithm. Furthermore, the controller can deal properly with grid impedance uncertainties, which change the resonance peak frequency of the LCL filter, which affects the controller performance and can induce the closed-loop to instability, by incorporation of a majorant signal and the σ-function into the adaptive law, turning it robust. In addition, the predictive nature of the controller, which aims to regulate the current tracking in the minimum time possible (one sample) impacts straightforwardly in the reduction of harmonic distortion on grid-injected currents, improving energy quality, because the transient regime is reduced thanks to the fast dynamics of the adaptive predictive control strategy. To corroborate the controller’s performance and discuss its robustness, Hardware-in-the-Loop and experimental results using a grid-tied 5.5 kW VSI with an LCL filter are presented

A Robust Adaptive Super-Twisting Sliding Mode Controller applied on grid-tied power converter with an LCL filter

This paper presents a new robust adaptive controller, totally developed on discrete-time. This controller is composed by two control structures: a Robust Model Reference Adaptive Controller (RMRAC) and an Adaptive Super-Twisting Sliding Mode (STSM) Controller, constituting a new control structure, nominated Robust Adaptive STSM Controller. The main advantage of this new control proposal is its high adaptability and robust performance, with fast reference tracking without chattering. The stability and robustness analysis, in discrete time, are presented, considering the overall plant, that is, in presence of matched and unmatched dynamics. To evaluate its robustness performance, the proposed controller is designed for grid-injected current control of three-phase grid-tied power converter with an LCL filter under weak grid. To validate it, the plant was partially modeled as a first order transfer function, neglecting capacitor dynamics and considering it as an additive dynamics on control design. Experimental results are presented to corroborate the controller performance and the stability analysis by means of Lyapunov Theory is provided.