Fast Disturbance Rejection Research Articles

Malmquist orthogonal functions based Tube model predictive control with sliding mode for DC motor servo system

This paper introduces a novel approach to the conventional model predictive control design within a tube model predictive control framework for a DC motor servo system that is an important component of various control systems in process industries. Tube model predictive control proves to be an effective method in the formulation, analysis, and implementation of robust control strategies. The objective is to include all possible trajectories of an uncertain system within a tube of the nominal system trajectories. Therefore, the proposed method incorporates discrete-time generalized Malmquist orthogonal functions for nominal model predictive controller design, which is the first time that these functions are used for this purpose in combination with the auxiliary sliding mode controller. The sliding mode controller has a crucial role in determining the robust dynamics of a closed-loop system in the presence of disturbances and plant nonlinearities. Experimental results of DC servo motor angular position control are presented and discussed for two different sliding mode control algorithms. The analysis shows improved performance in terms of fast reference tracking and disturbance rejection.

Dynamic modeling and model predictive control for printed-circuit heat exchanger in supercritical CO2 power cycle

The supercritical carbon dioxide (sCO2) Brayton cycle, known for its superior thermal efficiency and compact turbomachinery size, can utilize various heat sources. The printed-circuit heat exchangers (PCHE) used in the power cycle, particularly the recuperators and cooler, significantly influence the thermal efficiency of the cycle. However, they exhibit intricate characteristics attributed to large thermal inertia and nonlinear heat transfer. This paper explores the one-dimensional dynamic modeling and control issues for PCHE. The established dynamic PCHE models are verified through different scenarios. Then, a novel control strategy is proposed for fast temperature reference tracking and disturbance rejection. The composite controller includes three parts: the main control is based on the principle of model predictive control (MPC); Gaussian process (GP) regression modeling is incorporated as the feedforward; and the disturbance observer (DOB) is introduced for unexpected disturbance estimation and compensation. Compared with traditional controllers, simulations demonstrate that for reference tracking the settling time of the proposed method can be saved by more than 50%, and for disturbance rejection the recovery time can be reduced by more than 30%. The results indicate the presented strategy can ensure the safe and effective operation of the sCO2 power cycle.

Advanced Controllers for Heat Transfer Fluid Mass Flow Rate Control in Solar Tower Receivers

Efficient control strategies for managing the mass flow rate (MFR) of heat transfer fluids (HTF) during cloud transients in Solar Tower receivers play a pivotal role in optimizing plant profitability and receiver durability. This study focuses on the performance and durability of Solar Tower receivers during cloud transients. It evaluates adaptive feedback and feedforward control methods, which adjust the flow rate of heat transfer fluids based on real-time measurements of direct normal irradiance (DNI), receiver outlet and receiver panel outlet temperatures. The effectiveness of an aggressive all-sky and conservative clear-sky control strategy is explored against a conventional PI controller, emphasizing energy efficiency and receiver longevity. Simulations using a thermal Modelica model resembling a 100 MWel Crescent Dunes-like solar tower plant reveal that both advanced controllers provide precise setpoint tracking, while the PI controller struggles. The conservative controller which has a cloud standby mode prevents overheating during cloud transients by using a clear sky mass flow rate, while the aggressive controller uses the receiver panel outlet temperatures to correct for upstream tube temperature variations allowing for fast tracking correction and disturbance rejection, albeit with slight overshoots. Furthermore, the controllers significantly decrease the creep-fatigue damage accumulated in the receiver panels during cloudy days, due to limiting the increase in wall temperature spikes when cloud events end. Overall, this study underscores the pivotal role of HTF mass flow rate control systems in influencing receiver system failure modes and longevity and offers a new tool in controller design and operation assessment.

Driving an asynchronous motor powered by PV‐MPPT using equivalent RST controller of fractional order PI and IP, based on generalized predictive control

AbstractThe article introduces a new model of a Reference Signal Tracking (RST) controller for the fractional order quantities. The controller is applied to an indirect field‐oriented control (IFOC) system used for the speed control of an asynchronous motor powered by a photovoltaic (PV) generator with a maximum power point tracking (MPPT) algorithm. This model utilizes two fractional order controllers: the fractional order proportional‐integral (FOPI) regulator and the fractional‐order integral‐proportional (FOIP) regulator. These controllers are used with the generalized predictive control (GPC) technique. The first step in the approach is to derive the equivalent digital RST controller's model from the FOPI and FOIP controller's transfer functions. The GPC technique converts the continuous‐time FOPI (and FOIP) controller into a discrete‐time version. This conversion ensures a fast response and effective disturbance rejection. Simulation tests are conducted to analyze the rotor speed and stator current ripples to evaluate the performance of the proposed method. The results demonstrate the effectiveness of the introduced scheme in achieving improved control performance in terms of response speed and disturbance rejection. The article presents a modified RST controller model based on the fractional order approach applied to an IFOC system for motor speed control driven by a photovoltaic generator. Using FOPI, FOIP controllers, and GPC contributes to enhanced control performance, as evidenced by the simulation results.

Internal model control of cumene process using analytical rules and evolutionary computation

Cumene is a precursor for producing many organic chemicals and is thinner in paints and lacquers. Its production process involves one of the large-scale manufacturing processes with complex kinetics. Different classical control strategies have been implemented and compared in this process for the cumene reactor. As a system with large degrees of freedom, a novel approach for extracting the state space model from the COMSOL Multiphysics implementation of the system is adopted here. Internal Modern Control (IMC) based PI and PID controllers are derived for the system. The system is reduced to the FOPDT and SOPDT model structure to derive the controller setting using Skogestad half rules. The integral time is modified for excellent set point tracking and faster disturbance rejection. From the analysis, it can be stated that the PI controller suits more for this specific process. The particle swarm optimization (PSO) algorithm, an evolutionary computation technique, is also used to tune the PI settings. The PI controllers with IMC, Zeigler Nichols, and PSO tuning are compared, and it can be concluded that the PSO PI controller settles at 45 s without any oscillations and settles down faster for the disturbance of magnitude 0.5 applied at t = 800 s. However, it is computationally intensive compared to other controller strategies.

Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation

This comprehensive research addresses a gap in the literature by providing an extensive examination of a single-component single-stage vaporizer process. The research involves sophisticated analyses such as dynamic modeling, comprehensive control system design and performance evaluation. The study systematically derives a linear state-space model from complex nonlinear dynamic models, laying the basis for the development of two highly effective control systems specifically designed for vaporizer level and temperature control. The simulations of these control structures demonstrate notable properties, including fast disturbance rejection, minimal overshoot, and virtually no steady-state error, emphasizing their robustness and precision. This research focuses on the stability and response of the system and provides insight into its transient behavior during disturbances and setpoint changes. The study's broad implications extend beyond the results and provide a path for future improvements. The results indicate ways to refine the start-up stage, minimize initial overshoot during system initialization, and further improve control strategies. This work has the potential to make a difference in advancing the field of vaporization processes, providing engineers and researchers with the tools and insights needed to improve system reliability and performance in industrial applications.

Non-integer disturbance observer-aided resilient frequency controller applied to hybrid power system

This work made the earliest effort to investigate the performance of a non-integer disturbance observer (NiDob)-aided non-integer sliding mode controller (NiSMC)/second-order SMC (SOSMC) for frequency regulation of an islanded hybrid power system with matched/mismatched uncertainties. The unavoidable presence of unknown system disturbances, uncertainties, and practical limitations of control inputs are considered while developing the proposed resilient nonlinear controllers. Firstly, a NiDob is designed to estimate unknown bounded aggregated plant uncertainties. Subsequently, an improved NiSMC/SOSMC is developed by conveniently augmenting disturbance estimation. Quasi-oppositional marine predators' algorithm (QOMPA) is applied to obtain the near-optimum gains of the proposed frequency controllers minimizing an integral error-based objective function. The finite-time convergence of NiDob and closed-loop asymptotic stability of the studied power system has been established using the Mittag-Leffler/Lyapunov argument. The usefulness and practicability of the applied frequency have been demonstrated by performing a comparative study with SMC, NiSMC (without NiDob), NiDob-aided NiSMC, and other results reported in the literature. The numerical simulations showcase the efficacy of the applied control methodology regarding minimal chattering, faster disturbance rejection, and improved transient performance. The proficiency of the developed control methodology is validated on an IEEE-39/IEEE-68 bus testbed. Finally, the ability of the suggested resilient control algorithm in the detection and mitigation of deception-type cyber-attacks has been tested and affirmed in cyber-physical environments.

Robust Adaptive Control Strategy for a Bidirectional DC-DC Converter Based on Extremum Seeking and Sliding Mode Control

This paper presents a new control strategy that combines classical control and an optimization scheme to regulate the output voltage of the bidirectional converter under the presence of matched and mismatched disturbances. In detail, a control-oriented modeling method is presented first to capture the system dynamics in a common canonical form, allowing different disturbances to be considered. To estimate and compensate for unknown disturbances, an extended state observer (ESO)-based continuous sliding mode control is then proposed, which can guarantee high tracking precision, fast disturbance rejection, and chattering reduction. Next, an extremum seeking (ES)-based adaptive scheme is introduced to ensure system robustness as well as optimal control effort under different working scenarios. Finally, comparative simulations with classical proportional-integral-derivative (PID) control and constant switching gains are conducted to verify the effectiveness of the proposed adaptive control methodology through three case studies of load resistance variations, buck/boost mode switching, and input voltage variation.

Experimental Performance Comparison of Bidirectional Actuator Configurations for Suspended Aerial Platforms

Suspended payload requires bidirectional thrust actuation to control their motion. Such systems, like the small suspended aerial cliff sampling system considered in this letter, require strong bidirectional actuators capable of fine positioning and fast disturbance rejection to fight wind gusts. This letter presents a detailed experimental comparison of three bidirectional thrust actuator configurations (i.e., reverse thrust, antagonist thrusters, and variable pitch propeller) to understand their characteristics at the scale of small aerial systems. Five tests highlight the strengths and weaknesses of each configuration regarding static thrust capabilities, large and small step response, and bandwidth capabilities. This information is then used to select the best configuration for the suspended aerial cliff sampling system described, which in turn was able to sample rare cliff plants in Kaua'i in winds gusts of up to 37 km/h. The results will also help aerial roboticists make better-informed design decisions.

Design of a 2-DOF-PID controller using an improved sine–cosine algorithm for load frequency control of a three-area system with nonlinearities

This paper proposes an improved sine–cosine algorithm (ISCA) based 2-DOF-PID controller for load frequency control. A three-area test system is built for study, while some physical constraints (nonlinearities) are considered for the investigation of a realistic power system. The proposed method is used as the parameter optimizer of the LFC controller in different scenarios. The 2-DOF-PID controllers are used because of their capability of fast disturbance rejection without significant increase of overshoot in set-point tracking. The 2-DOF-PID controllers’ efficacy is observed by examining the responses with the outcomes obtained with PID and FOPID controllers. The simulation results with the suggested scheme are correlated with some of the existing algorithms, such as SCA, SSA, ALO, and PSO in three different scenarios, i.e., a disturbance in two areas, in three areas, and in the presence of physical constraints. In addition, the study is extended to a four-area power system. Statistical analysis is performed using the Wilcoxon Sign Rank Test (WSRT) on 20 independent runs. This confirms the supremacy of the proposed method.

Fundamental frequency sequence amplitude estimator for power and energy applications

A grid-synchronization-based fundamental frequency positive-sequence (FFPS) and negative-sequence (FFNS) amplitudes estimation technique is proposed for unbalanced and distorted grid. In this technique, the sequence amplitudes are extracted by extracting the phase-angle of the FFPS and FFNS components. The extracted phase-angles have DC and double frequency AC components. The AC component is filtered out by using a Moving Average Filter (MAF) of appropriate window length. From the extracted phase-angle, the unknown frequency can be estimated by using a suitable controller. A frequency-fixed equidistant samples-based pre-loop filter is also applied to eliminate the effect of measurement offset. The proposed technique has a very simple structure and is easy to tune. Small-signal modeling-based stability analysis and gain tuning procedure are also provided. The proposed technique strikes a good balance between fast convergence and disturbance rejection capability. Comparative numerical simulation and experimental results with similar other techniques demonstrate the suitability and performance enhancement by the proposed technique.

Frequency Regulation of Nonlinear Power Systems using Neural Network Observer-Based Optimized Resilient Controller

This study introduces a resilient frequency controller for nonlinear interconnected power systems to counteract endogenous/exogenous system disturbances. A neural network-based observer (NNO) is intended to estimate lumped system disturbances, such as unmodelled dynamics and unknown disturbances. The estimated NNO’s output is incorporated with a second-order sliding mode controller (SOSMC) to minimize chattering in the control effort and improve the nominal performance of the undertaken plant. The design parameters of SOSMC have been optimally identified by applying Harris hawk optimization (HHO), exercising integral error-based objective function. HHO has demonstrated superior tuning capabilities than other well-known optimization methodologies in terms of convergence rate and transient measurements of system outputs. The asymptotic convergence of estimated error and overall stability of the system has been established employing the Lyapunov argument. System outputs are compared with the results reported in the literature to validate the efficacy of the proposed resilient frequency controller. Presented results showcase the mastery of the applied NNO-based SOSMC over its counterparts in weaker chattering, fast disturbance rejection, and a high degree of robustness against endogenous/exogenous disturbances.

Robust finite-time consensus control for Euler–Lagrange multi-agent systems subject to switching topologies and uncertainties

Euler–Lagrange (EL) system is a typical nonlinear system widely used to model robot systems. Although consensus of EL multi-agent systems has been extensively studied in recent years, how to achieve better consensus performance under constraints such as switching topologies and uncertainties is still an open issue. Aiming at fast convergence and effective disturbance rejection, this paper studies the integral sliding mode control problem for robust finite-time consensus of EL multi-agent systems subject to switching topologies and uncertainties. A basic integral sliding mode control (SMC) scheme is first presented for finite-time consensus of EL multi-agent systems subject to undirected topologies and uncertainties. It is shown that the proposed consensus protocol reaches good disturbance rejection and achieves robust finite-time consensus while avoiding the singularity problem in the existing studies. The proposed integral sliding mode control scheme is further extended to finite-time consensus of EL multi-agent systems subject to directed and switching topologies. Compared with the existing algorithms, faster finite-time convergence is achieved. In the simulation studies, the obtained results demonstrate the effectiveness and efficiency of the proposed algorithm.

Adaptive fractional-order sliding-mode disturbance observer-based robust theoretical frequency controller applied to hybrid wind–diesel power system

This work presents design and theoretical analysis of an adaptive fractional-order sliding-mode disturbance observer (FO-SM-DOB)-aided fractional-order robust controller for frequency regulation of a hybrid wind–diesel based power system, considering endogenous/exogenous system disturbances. Adaptive FO-SM-DOB is designed to estimate unknown/uncertain lumped system disturbances, including parametric uncertainty and exogenous disturbances. Afterwards, an improved fractional-order sliding mode controller (FOSMC) augmented with the estimated output of FO-SM-DOB is designed and applied to accelerate system dynamics with minimum chattering in the control effort. The Mittag-Leffler stability theorem affirms the finite-time convergence of disturbance estimation error. Moreover, the closed-loop asymptotic stability of the overall control system has been guaranteed by applying Lyapunov argument. The effectiveness of the suggested resilient fractional-order nonlinear frequency controller is theoretically validated by performing an extensive comparative study with SMC, FOSMC (without DOB), state observer-based SMC (SOB-SMC), second-order SMC (without DOB), and conventional integer/fractional-order controllers. Simulation results establish the supremacy of the proposed resilient fractional-order nonlinear frequency controller over its other counterparts concerning fast disturbance rejection, weaker chattering, and a high degree of robustness against unknown lumped system disturbances. Further, to demonstrate the practicability and validate the effectiveness of the proposed control strategy, magnetic levitation system and IEEE 39-bus New England power system are considered and successfully tested on MATLAB platform.

Optimized cascade fractional‐order 3DOF‐controller for frequency regulation of a hybrid power system using marine predators algorithm

AbstractThis article investigates the competence of a cascade fractional‐order three‐degree‐of‐freedom (CC‐FO‐3DOF) controller for power‐frequency regulation of a hybrid wind‐diesel (hyWD) power system subjected to continuous load variation and unknown/uncertain wind power perturbation. The proposed cascade controller utilizes fractional‐order 3DOF‐PID and tilt‐integral‐derivative controllers as slave and master controllers, respectively, to ensure fast disturbance rejection and high damping of power‐frequency oscillations. A disturbance observer is designed to estimate system states and unknown/uncertain wind velocity. Subsequently, an improved control law is designed by augmenting the disturbance estimation, which ensures a higher degree of robustness of the closed‐loop system against disturbances. Marine Predators algorithm (MPA) is applied to search near‐optimum settings of the proposed controller, exercising an integral error‐based objective function. The effectiveness of the proposed controller is demonstrated by comparing results with the outputs of other prevalent controllers reported in the state‐of‐art. Extensive analysis of the presented results establishes the superiority of the MPA‐tuned CC‐FO‐3DOF controller in terms of maximum peak overshoot, frequency nadir, speed of response, and steady‐state accuracy. Finally, the robust closed‐loop stability of the investigated hyWD system has been affirmed applying Kharitonov's stability method, considering dynamic variation in system parameters.

Model Predictive Control for ARC Motors Using Extended State Observer and Iterative Learning Methods

The arc permanent magnet motor (arc motor) is widely used in large telescope for its high efficiency and high power density. Due to the unique structure, the periodic end torque, cogging torque and flux harmonics will cause certain speed ripples which can affect the performance of the drive system. To solve these problems, the paper proposes a novel model predictive control (MPC) based on extended state observer and iterative learning control, where the MPC is equipped in speed loop and the disturbances estimated by the conventional extended state observer (ESO) are fed forward to the controller to improve the ability of disturbance rejection. A position dependent iterative learning control (ILC) is used to estimate the periodic disturbances at different speeds. The MPC calculates the q axis current reference with the compensation of ESO and ILC, which can have a fast response and disturbance rejection ability for periodic and nonperiodic disturbances. The stability of the proposed method is demonstrated by theoretical analysis. The experimental results validate the effectiveness of the proposed method at different speeds.

Refined Disturbance Rejection-Based Composite Control of Flexible Spacecrafts for Tracking a Tumbling Non-Cooperative Target

When tracking a tumbling non-cooperative target, the position and attitude maneuver control with high-precision as well as fast-response performances is required for flexible spacecrafts. However, the unknown rigid-flexible coupling and model uncertainties will degrade the control performances significantly. Therefore, this paper proposes a refined disturbance rejection-based composite control method for spacecraft position and attitude tracking. First of all, the disturbances including the rigid-flexible coupling and model uncertainties are described by an exogenous model by fully using the partially known disturbance information (e.g., modal frequency and damping). Then, a novel exogenous model-based sliding mode disturbance observer (SMDO) is proposed to achieve the refined disturbance estimation. Next, by combining the SMDO in the feedforward loop and an adaptive terminal sliding mode control (ATSMC) in the feedback loop, a finite-time composite control law is proposed to ensure the fast disturbance rejection and position/attitude tracking simultaneously. In the composite controller, a novel nonsingular terminal sliding mode surface with arctangent function is proposed. Moreover, a time-varying boundary Lyapunov function (BLF) is designed to preassign the transient and steady-state performances of sliding mode surface. Finally, the effectiveness of proposed method is verified via numerical simulation.

Robust Load Frequency Control Using Fractional-order TID-PD Approach Via Salp Swarm Algorithm

To preserve frequency and tie-line power flow within a tolerable range in modern intricate and renewable energy sources (RES) integrated power system, an intelligent, expert, and robust load frequency control (LFC) scheme is requisite. This paper proposes a new load frequency control (LFC) approach using a dual-stage controller composed of fractional-order tilted-integral-derivative (TID) and integer-order proportional-derivative (PD) controllers. The recently developed salp swarm algorithm has tuned the parameters of the controller. The proposed scheme exhibits robustness and fast disturbance rejection performance because the tilted-integral-derivative controller is structured in a fractional-order framework, and transient response is improved due to the proportional-derivative controller. The overall activity of the LFC has been further upgraded by incorporating the flexible AC transmission system (FACTS) device namely thyristor-controlled phase shifter (TCPS) unit and energy storage system called redox flow battery (RFB) units. The proposed control approach is applied to diverse types of multi-area multi-source power systems with thermal, hydro, and wind turbine units along with nonlinear functions namely generation rate constraint (GRC), governor dead band (GDB), and communication delay (CD). The simulation results yield improved frequency regulation activity with and without TCPS and RFB using the proposed control approach when compared with the recently developed LFC approaches. Sensitivity analysis also established the robustness of the proposed control approach.

Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode

The ionic polymer metal composite (IPMC) actuator is a kind of soft actuator that can work for underwater applications. However, IPMC actuator control suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, for underwater applications, they are highly exposed to parametric uncertainties and external disturbances due to the inherent characteristics and working environment. Those factors significantly affect the positioning accuracy and reliability of IPMC actuators. Hence, feedback control techniques are vital in the control of IPMC actuators for suppressing the system uncertainty and external disturbance. In this paper, for the first time an adaptive full-order recursive terminal sliding-mode (AFORTSM) controller is proposed for the IPMC actuator to enhance the positioning accuracy and robustness against parametric uncertainties and external disturbances. The proposed controller incorporates an adaptive algorithm with terminal sliding mode method to release the need for any prerequisite bound of the disturbance. In addition, stability analysis proves that it can guarantee the tracking error to converge to zero in finite time in the presence of uncertainty and disturbance. Experiments are carried out on the IPMC actuator to verify the practical effectiveness of the AFORTSM controller in comparison with a conventional nonsingular terminal sliding mode (NTSM) controller in terms of smaller tracking error and faster disturbance rejection.

Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

SummaryThis article presents the development and experimental validation of an emissions oriented model predictive controller for a diesel engine. The control objective is to minimize cumulative NOx and hydrocarbon emissions while limiting visible smoke production and without compromising fuel economy or torque response. This is accomplished by using a supervisory model predictive controller (SMPC) and nonlinear model predictive controller (NMPC) in tandem. The SMPC controller coordinates the exhaust gas recirculation (EGR) rate target and fuel supplied to the engine in real time to satisfy combustion quality constraints, while the NMPC controller tracks the EGR rate target by manipulating the EGR throttle, EGR valve, and variable geometry turbine. The NMPC controller uses MPC for feedforward and feedback in a novel configuration to simultaneously achieve fast tracking performance, disturbance rejection, and robustness. We demonstrate that the proposed diesel engine MPC controller is able to reduce cumulative emissions by 10% to 15% relative to a state of the art benchmark strategy when placed in closed loop with an engine on a transient dynamometer.