Conventional Linear Control Research Articles

Non‐linear coordinated control of LPMG‐based direct drive wave energy conversion system with supplementary energy storage system based on feedback linearization

AbstractThe linear permanent magnet generator (LPMG)‐based direct drive wave energy conversion system (DDWECS) works under perpetual fluctuations of ocean waves. Short‐term energy storage, such as electrochemical energy storage, is usually adopted in a supplementary energy storage system (SESS) to buffer power fluctuations. Since the investigated DDWECS consists of various non‐linear components such as insulated gate bipolar transistors (IGBTs)‐based power electronic converters, the unremitting changes of system working conditions caused by ocean wave effects will degrade the dynamic performance with conventional linear controllers which are implemented via local linearization around a single working condition. This paper proposes the multiple feedback linearization based non‐linear coordinated control (MFLNCC) scheme for coordinating non‐linear plants in DDWECS with SESS such as the machine‐side converter (MSC), the grid‐side converter (GSC) and DC/DC converter in SESS. The enhanced dynamic performance of the proposed MFLNCC in DDWECS with SESS is validated under different scenarios.

A maximum power point tracking control strategy of tidal energy conversion system based on fixed-time observer technology

To achieve maximum tidal current energy capture in complex and harsh marine environments, this paper proposes a nonlinear control based on fixed-time observer (NCFTO) for tidal energy conversion system (TECS). The TECS operating in the ocean not only needs to face time-varying ocean current speed, but also needs to consider the adverse effects brought by parameter uncertainties and unknown disturbances in actual operation. Considering the high nonlinearity of TECS, conventional linear control systems may not necessarily provide satisfactory performance. Therefore, the NCFTO takes into account the TECS parameter uncertainties and unknown disturbances in its design. This mainly involves using a designed fixed-time observer to accurately estimate a concentrated disturbance term containing TECS nonlinearities, parameter uncertainties, disturbances in real time, and offsetting the adverse effects of actual disturbances on the control system. Meanwhile, a linear controller is designed based on the linearization of TECS to ensure satisfactory performance of NCFTO under time-varying ocean current speed, thus laying a solid foundation for achieving maximum tidal current energy capture. In addition, to verify the feasibility and effectiveness of NCFTO, three simulation testing scenarios have been set up, namely time-varying ocean current speed, rotor inertia uncertainty, and unknown disturbance torque.

Multi-Channel Phase-Compensated Active Disturbance Rejection Control with an Improved Backstepping Strategy for Electro-Optical Tracking Systems

A multi-channel phase-compensated active disturbance rejection control (MPADRC) incorporating an improved backstepping strategy is proposed in this paper to handle the phase lag in the extended state observer (ESO) and the residual uncertainty in the system. Firstly, a multi-channel phase-compensated ESO (MPESO) is constructed by adding phase-advanced networks to all output channels of the ESO, which allows disturbances and system states to be compensated and feedback in a more timely manner, respectively. Then, to estimate and offset the residual uncertainty in the system, an improved backstepping control method is employed and a Lyapunov function is designed to verify the convergence of the error between the estimated and actual values of the residual uncertainty. After that, the improved backstepping control is combined with MPADRC, and comparisons with the conventional linear active disturbance rejection control (LADRC) are conducted for a range of cases. Finally, on an inertial stabilization platform in the electro-optical tracking system (ETS), simulation and experimental results verified the effectiveness of the proposed method.

Sliding‐mode variational structure study of Cuk converter based on target holographic feedback

SummaryWith the rapid advancement of new energy sources, distributed power supplies have gained widespread adoption in DC microgrid systems. The stability of the DC‐DC converter, serving as the central component for energy transfer between the distributed power supply and the DC bus, holds significant importance in ensuring the overall system performance. Due to the intricate nature of real‐world operating conditions, the DC bus voltage is frequently subject to uncertainties such as fluctuations in distributed power supplies and random variations in loads. As a consequence, the reliability of DC‐DC converters faces escalating demands, making it challenging for conventional linear controllers to ensure consistent operation of DC‐DC converters across a broad range. This study focuses on addressing this issue by investigating the Cuk converter, which serves as a representative example of a single‐input multiple‐output system. The operating characteristics and control challenges of the Cuk converter are analyzed, and a nonlinear control strategy based on target holographic feedback is proposed to enhance the system's stability. Considering the non‐minimum phase characteristics of the Cuk converter and its inability to be linearized through exact feedback, a sliding mode variable structure control approach is introduced, utilizing target holographic feedback. Through simulation and experimental analysis, the effectiveness of the model and the theoretical analysis are validated.

Linear time-varying fractional-order model predictive attitude control for satellite using two reaction wheels

Achieving precise attitude control in satellites equipped with two reaction wheels remains a significant challenge. During the last decade, model predictive control has emerged as a promising technique for satellite attitude control. However, this paper takes a step by introducing the novel concept of linear time-varying fractional-order model predictive control specifically tailored for satellites with dual reaction wheels, enabling them to achieve desired orientations more effectively. This study begins by elucidating the nonlinear dynamics and kinematic equations governing the satellite's behavior. To facilitate control design, the satellite linear time-varying model is derived by linearizing the nonlinear equations around the operating point. Leveraging this linearized representation, a linear time-varying fractional-order model predictive control method is designed, leveraging the benefits of fractional-order cost functions. Finally, the simulation results show the remarkable performance of the linear time-varying fractional-order model predictive control approach, particularly when confronted with input constraints. Notably, the proposed method outperforms the traditional linear time-varying model predictive control method by achieving an 80% improvement in tracking speed, while simultaneously reducing the applied torque by 67%. Additionally, the proposed approach decreases the mean absolute error of the satellite attitude angles by over 80% compared to the conventional linear time-varying model predictive control method. This research not only addresses the pressing challenge of attitude control in satellites with dual reaction wheels but also presents a novel and highly effective approach that surpasses existing methods in terms of performance and efficiency. As such, it holds immense potential for the field of satellite attitude control, making it an indispensable read for engineers and researchers working in the domain of aerospace engineering and control systems.

Mitigation of severe false data injection attacks (FDIAs) in marine current turbine (MCT) type 4 synchronous generator renewable energy using promoted backstepping method

False data injection attack (FDIA) is kind of the most important and prevalent cyber attacks, influencing in power systems and renewable energy resources in microgrids (MGs). The destructive effects caused by FDIAs in the voltage components of synchronous generator with full converter in AC microgrid (ACMG) renewable energy production would seriously damage the DC link voltage, network frequency and also, the active power. The extracted voltage components in the d and q axes to control the grid side converter (GSC) as the main control section, are the important signals for power control process of the synchronous generator with wind or marine current turbine (MCT). In this regards and due to the nonlinear behavior caused by cyber attacks in the generator control process, the robust performance of modified nonlinear backstepping method would be an appropriate alternative, instead of the conventional linear control including PI controllers. Thus, a remedial action against various FDIAs caused in the voltage control commands of the GSC is proposed. Moreover, promotion of the backstepping control by combining with the switching terms, adopted from the higher order super twisting sliding mode control (HOSTSMC), the performance of the proposed method would be precisely robust. To verify the proposed method, severe FDIAs by injecting various constant values, periodic and also, noisy signals are our case studies which are simulated via MATLAB software in the weak grid connect and standalone operation modes.

Sliding Mode Control for Hybrid Mass Dampers: Experimental analysis on robustness

This manuscript presents an experimental investigation into the effectiveness of Sliding Mode Control (SMC) for vibration mitigation of a structure equipped with a Hybrid Mass Damper (HMD), as compared to conventional linear controllers. The experimental setup involves a cantilever beam exhibiting a first bending mode at 21Hz, subjected to strong parametric uncertainties and external excitation through a shaker. Additionally, an inertial actuator with internal resonance at 21Hz is utilized to apply passive and active control to the vibrating beam. The SMC approach is compared to three more common HMD control methods: α−controller, LQG, and passivity-based control. To highlight the robustness and performance advantages of SMC, the nominal system undergoes significant mass and inertia modifications, not accounted for during the tuning of the observer and the controllers. The performances of the various controllers are then compared on four scenarios: two nominal identified systems and two configurations with uncertain parameters. Experimental results underscore the superior capabilities of SMC in mitigating structural vibrations, showcasing not only enhanced stability but also superior performance when confronted with substantial parametric uncertainties, outperforming traditional linear control methods.

Predictive direct control strategy of unified power quality conditioner based on power angle control

The unified power quality conditioner (UPQC), based on power angle control (PAC), addresses the power distribution issue and enhances equipment utilization between two active power filters (APF) of UPQC by employing conventional linear control algorithms that have complex control structures and exhibit challenges in adjusting controller parameters and control delays. This study proposes a UPQC predictive direct control strategy based on power angle control (PDCS-PAC). We combine the direct control strategy with the finite control set model predictive control (FCS-MPC) to establish the UPQC finite set model predictive direct control system model in the dq coordinate system. This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. Finally, we construct a simulation platform and a laboratory prototype to validate the feasibility and efficacy of the proposed control strategy.

Experimental evaluation of the backstepping‐based input resistance controller in step‐up DC–DC converter for maximum power point tracking of the thermoelectric generators

AbstractIn this paper, a novel non‐linear model‐based approach is presented for maximum power point (MPP) tracking of thermoelectric generators (TEGs) using the backstepping controller. Considering the output voltage range of the thermoelectric devices, a step‐up DC–DC converter is employed as an interface between the load and input power source. According to the maximum power transfer theorem, if the equivalent input resistance of the converter (Rin) is equal to the internal resistance of the input source (RTEG), the TEG operation at the MPP will be achieved. Hence, defining the RTEG as a reference value and Rin as a feedback variable for a closed‐loop controller, the backstepping non‐linear controller is developed for input resistance control of the boost DC–DC converter. Owing to the non‐linear nature of the error variable in the input resistance control of the converters, conventional linear controllers cannot guarantee the system's closed‐loop stability within an extensive operational range. However, despite changes in generator's open‐circuit voltage (VOC) and RTEG, the designed closed‐loop controller can successfully stabilize the thermoelectric converter in different operational conditions. Considering the Lyapunov theorem and the Barbalat lemma, the asymptotic stability of the backstepping controller is proved. During the steady‐state operation, the actual values of the VOC and RTEG are updated periodically by the measurement of the converter input voltage/current values. To verify the functionality of the designed control method, PC‐based simulations are carried out in MATLAB/Simulink software. Moreover, by using TMS320F28335 digital signal processor from Texas Instruments and a simple thermoelectric simulator, the experimental response of the proposed controller is evaluated in dynamic and steady‐state conditions. The developed closed‐loop system can track the MPP of a TEG with zero steady‐state error, regardless of uncertain parameter variations.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor (PMSM) speed control systems with conventional linear active disturbance rejection control (CLADRC) strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances. In order to address these issues, this paper proposes an improved two-degree-of-freedom LADRC (TDOF-LADRC) strategy, which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning. PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately. Moreover, to evaluate the control performance of the TDOF-LADRC strategy, its stability is proven, and the influence of each controller parameter on the system control performance is analyzed. Based on it, a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances. Finally, experiments are performed on a 750 W PMSM experimental platform, and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

DESIGN OF A VARIABLE GAIN NONLINEAR FUZZY CONTROLLER AND PERFORMANCE ENHANCEMENT DUE TO GAIN VARIATION

In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

Decentralized proportional-integral controller based on dynamic decoupling technique using Beckhoff TwinCAT-3.1

An improved technique for the design of decentralized dynamic decoupled proportional-integral (PI) controllers to control many variables of column flotation was developed and implemented in this paper. This work was motivated by challenges when working with multiple inputs and multiple outputs (MIMO) systems that are not controllable by conventional linear feedback controllers. Conventional feedback control design consists of various drawbacks when it comes to complex industrial processes. The introduction of decentralization, decoupling, and many advanced controls design methods overcomes these drawbacks. Hence, the design and implementation of control systems that mitigate stability for MIMO systems are important. The developed closed-loop model of the flotation process is implemented in a real-time platform using TwinCAT 3.1 automation software and CX5020 Beckhoff programmable logic controllers (PLC) through the model transformation technique. The reasons for using the CX5020 as an implementation environment were motivated by the reliability, and is built according to new industry standards, allowing transformation, which makes it more advantageous to be used more than any other PLCs. This is done to validate the effectiveness of the recommended technique and prove its usability for any multivariable system. Comparable numerical results are presented, and they imply that industrial usage of this method is highly recommended.

LQR controller design for stabilization of non-linear DIP system based on ABC algorithm

Inverted pendulum systems, such as double or single, rotational or translational inverted pendulums are non-linear and unstable, which have been the most dominant approaches for control systems. The double inverted pendulum is one kind of a non-linear, unstable system, multivariable, and strong coupling with a wide range of control methods. To model these types of systems, many techniques have been proposed so that motivating researchers to come up with new innovative solutions. The Linear Quadratic Regulator (LQR) controller has been a common controller used in this field. Meanwhile, the Artificial Bee Colony (ABC) technique has become an alternative solution for employing Bee Swarm Intelligence algorithms. The research solutions of the artificial bee colony algorithm in the literature can be beneficial, however, the utilization of discovered sources of food is ineffective. Thus, in this paper, we aim to provide a double inverted pendulum system for stabilization by selecting linear quadratic regulator parameters using a bio-inspired optimization methodology of artificial bee colony and weight matrices Q and R. The results show that when the artificial bee colony algorithm is applied to a linear quadratic regulator controller, it gains the capacity to autonomously tune itself in an online process. To further demonstrate the efficiency and viability of the suggested methodology, simulations have been performed and compared to conventional linear quadratic regulator controllers. The obtained results demonstrate that employing artificial intelligence (AI) together with the proposed controller outperforms the conventional linear quadratic regulator controllers by more than 50 % in transient response and improved time response and stability performance

Guest Editorial Special Issue on Integrated Control and Modulation for Electric Drives

Green energies and electric mobility are considered exciting solutions to help reduce the emissions of greenhouse gases into the atmosphere. This scenario has significantly promoted the use of electric drives; consequently, higher technical requirements are assumed as mandatory. Focusing on the required high-performance electric drives, the direct control of power converters and the use of integrated modulators, namely, control techniques that avoid the pulse-width modulation stage, can be an attractive alternative to conventional linear controllers. For example, Model Predictive Control (MPC) presents inherent flexibility in defining control objectives, while Direct Torque Control (DTC) provides a fast dynamic response. Unfortunately, unacceptable harmonic distortion can appear in the system if single control action is applied per control cycle. This scenario promotes a higher current ripple in three-phase electric drives when a control scheme using a standard integrated modulator is implemented. The situation is even worse when multiphase drives are used since several orthogonal subspaces need to be regulated with a single control action. In addition, the characteristic low value of the equivalent impedance of the secondary subspaces may lead to enormous harmonic currents. Considering the previous scenario, although the dynamic response is very fast in direct controllers (control scheme based on integrated modulators), these control strategies could be discarded due to their high harmonic distortion. Fortunately, the disadvantages of direct control strategies can be mitigated by using enhanced integrated modulators, such as multi-vector solutions as control actions. On the other hand, as these control techniques’ performance is founded on the nature of the available voltage vectors, the use of some specific electric drives, such as symmetrical six-phase machines, can allow taking advantage of their desirable skills.

The ping-pang variable amplitude limiter used in the coordinated controller of a hybrid reactive power compensation system

The hybrid reactive power compensation system, which connects different reactive power compensation devices to the same bus, will be essential equipment for future power systems. In a power grid with a high proportion of photovoltaic, wind turbines, and power electronic devices, it is significant to design a coordinated control strategy for the hybrid reactive power compensation system. In this paper, a kind of ping-pang variable amplitude limiter is used in the linear optimal controller. The ping-pang variable amplitude limiter can improve the transient stability of a hybrid reactive power compensation system. The effects of the coordinated controller are verified in simulation. Compared with the conventional linear optimal controller, the coordinated controller with the ping-pang variable amplitude limiter has a better optimization effect in large disturbance conditions.

Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter

Model predictive control (MPC) is an efficient and growing approach to power converter control. This paper proposes an improved and simplified model predictive current control (MPCC) technique for a four-level nested neutral point clamped (4L-NNPC) converter. Conventional MPCC exhibits better performances as compared to the conventional linear control system such as fast dynamic response, consideration of the system constraints, and nonlinearities. However, the application of the conventional model predictive current control (MPCC) approach on complex systems provokes a significant number of calculations, which is the main hurdle to its practical implementation. To fix this flaw, this paper proposes an effective algorithm to shorten the execution time of the conventional MPCC. In this proposed technique, 216 current predictions of the conventional MPCC are skipped and converted into one required voltage vector (RVV) prediction. With this equivalent reference voltage transformation, the calculation burden of MPCC is significantly reduced, while the output performance is not influenced. The results of the simplified MPCC for the 4L-NNPC converter are analyzed and compared with the conventional MPCC. The computational time is reduced by 19.56% using the simplified MPCC, while keeping an approximately similar error of output currents. The switching frequency and total harmonic distortion (THD) of the proposed method are reduced by 8.16% and 0.07%, respectively, as compared to the conventional technique. These results demonstrate the fact that that the performance of a conventional MPCC is enhanced with the proposed MPCC. The proposed algorithm can be applied to several inverter topologies.

Sliding Mode Control Based on High Gain Observer for Electro-Hydraulic Servo System

The electro-hydraulic servo system is widely used in industrial automation fields for its merits of the high force to weight ratio, compact size, and fast response. However, the parameter uncertainties and external disturbances of the electro-hydraulic servo system significantly deteriorate the control performance of conventional linear controller in practice. To deal with this problem, sliding mode controller (SMC) that incorporates high gain observer (HGO) is proposed in this paper. HGO is used to obtain the accurate time derivative of position signal for sliding mode controller design. The stability of the control system is guaranteed by Lyapunov stability theory. Comparation simulation is conducted to validate the effectiveness of the presented control scheme.

Sliding Mode Input Current Control of the Synchronous DC-DC Buck Converter for Electro-Mechanical Actuator Emulation in More Electric Aircrafts

The main challenges of the input current control in synchronous DC-DC buck converters are the nonlinear model of the system, changes of the operating point in a wide range, and the need to use an input LC filter for current smoothing, which may result in the instability of the closed-loop system. In this paper, a step-by-step approach is developed for the design and improvement of a PI-feedforward closed-loop controller. It is shown that a linear PI controller cannot stabilize the closed-loop system properly during wide changes in model parameters, e.g., an equivalent series resistance of the input filter. To cope with the stability issues, a fixed-frequency sliding mode controller (SMC) has been developed in this paper for the implementation of an electro-mechanical actuator (EMA) emulator. Moreover, a systematic approach is proposed for controller tuning and the selection of the SMC’s gains. To achieve high power efficiency, high-frequency GaN switches are used for the practical implementation of the DC-DC converter. Despite large changes in the load current, the designed nonlinear controller can track the input current reference satisfactorily. Steady-state and dynamic responses of the proposed SMC are compared with conventional linear controllers. Considering the Lyapunov stability theorem, it is proved that the designed SMC can stabilize the closed-loop system in the entire utilizable domain. The proposed nonlinear SMC controller enjoys a very simple control law. Hence, despite having very high switching and sampling frequencies, it can be easily implemented. The experimental response of the designed synchronous DC-DC buck converter is evaluated experimentally by implementing the control strategy in a TMS320F28335PGFA DSP from Texas Instrument. Moreover, the comprehensive comparison of the proposed SMC controller and a PI-feedforward controller proved the superior performance of the developed closed-loop system, in terms of the transient time response, robustness, and stability of the EMA emulator.

Machine learning for flow-informed aerodynamic control in turbulent wind conditions

Control of aerodynamic forces in gusty, turbulent conditions is critical for the safety and performance of technologies such as unmanned aerial vehicles and wind turbines. The presence and severity of extreme flow conditions are difficult to predict, and explicit modeling of fluid dynamics for control is not feasible in real time. Model-free reinforcement learning methods present an end-to-end control solution for nonlinear systems as they require no prior knowledge, can easily integrate different types of measurements, and can adapt to varying conditions through interaction. Here, we show that reinforcement learning methods can achieve effective aerodynamic control in a highly turbulent environment. Algorithms are trained with different neural network structures, and we find that reinforcement learning agents with recurrent neural networks can effectively learn the nonlinear dynamics involved in turbulent flows and strongly outperform conventional linear control techniques. We also find that augmenting state observations with measurements from a set of bioinspired flow sensors can improve learning stability and control performance in aerodynamic systems. These results can serve to inform future gust mitigation systems for unmanned aerial vehicles and wind turbines, enabling operation in previously prohibitively dangerous conditions.

A Revisit to Model-Free Control

Starting from Fliess's model-free control (MFC) technique developed 15 years ago, this article aims to provide a systematic framework for characterizing, benchmarking, and generalizing this emerging control technique, with a particular focus on power electronics (PE). It examines the performance of MFC in terms of dynamic response, stability, and robustness, using the classical control theory as a basic tool. A theoretical comparison is conducted with the conventional linear control techniques on dynamic response and performance robustness. A generalized MFC theory and means to enhance its robustness performance are also highlighted. This article suggests that MFC, in contrast to the conventional understanding based on model-independent error dynamics, is practically a model-based control technique. Such model dependence characteristics under MFC become more severe for PE systems. However, following a new design principle, MFC is found possible to possess extraordinarily robust performance against model variations as compared to most existing model-based control methods. On top of that, stability margin is found to be the key bottleneck hindering the performance robustness of the existing MFC techniques. A new MFC with greater stability margin and performance robustness is proposed in this article. Comprehensive Pareto fronts analysis, simulations, and experiments are conducted on a buck converter system to verify the new understandings and conclusions drawn from the framework. With the new design principle and the new MFC, the system is able to demonstrate an almost constant dynamic response despi <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">te</b> 25-fold circuit parameter ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R, C</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ) variations and 1.85-fold input voltage variations.