Conventional Control Structure Research Articles

Direct Predictive Voltage Control for Grid-Connected Permanent Magnet Synchronous Generator System

In this paper, a direct predictive voltage control (DPVC) is proposed for the grid-connected permanent magnet synchronous generator (PMSG) system. In the proposed strategy, the dc-link voltage regulation and power regulation terms are merged into one cost function, thereby eliminating the conventional cascade control structure. The strategy selects the voltage vector that not only will generate a dc-link voltage closer to the setpoint at instant <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k+2$</tex-math></inline-formula> , but will generate an active power that can further reduce that voltage error for the future instant. To cope with the mismatch between the actual and nominal parameters, Kalman filter has been added to compensate for the steady-state error. Besides, to enhance the dynamic performance and to save the effort of parameter tuning, the weighting factor is further eliminated from the cost function by sorting the terms into two groups and independently evaluating each group in turn. To fully validate the effectiveness of the proposed strategy, the experimental test waveforms of the DPVC strategy with and without weighting factor have been presented and compared with that of the conventional PI-MPC strategy in various testing conditions.

Dynamic control of an energy-saving process with two extractive dividing-wall columns for separation of acetone/methanol/butanone/tert-butyl alcohol mixtures

In the chemical and petrochemical industries, an azeotropic mixture of acetone/methanol/butanone/tert-butanol needs to be separated for high-purity products. Following a previous work in which an energy-saving process composed of two extractive dividing-wall columns (EDWCs) was developed for the quaternary system, this paper focuses on the issue of dynamic control for this process. Several control strategies in combined with temperature control, temperature-difference control and composition control are established to maintain the purity of all products in the face of disturbances in feed flow and feed composition. Dynamic simulations demonstrate that a conventional temperature control structure provides very poor control while a control strategy that used three-temperature-difference control for both EDWCs is the most effective.

Design of structured [formula omitted] flight controllers: Passive fault-tolerant versus observer-based structures

This article presents the structured H∞ design and validation of two types of flight controller architectures: a passive fault-tolerant controller for the longitudinal motion and an active observer-based fault-tolerant controller for the lateral-directional motion. In the first, the controller follows the conventional Stability/Control Augmentation System (SCAS) structure, and its gains are obtained in continuous-time with the hinfstruct command by considering a set of elevator Loss-Of-Efficiency (LOE) faults. For the second, the conventional Luenberger observer-based controller structure is used, and the design aims to monitor the health of the aileron and rudder actuators in addition to provide active tolerance against LOE faults. Two different discrete-time designs are obtained for the latter, one focused on control performance optimization (using also the hinfstruct command), and the other on simultaneous control and observer performance optimization (using the systune command and under a slightly relaxed control performance constraint). For the two types of architectures, unmodeled dynamics are represented by uncertain bounded time delays modeled as pure delays or first-order Padé approximations. The resulting controllers are implemented on-board JAXA’s research airplane MuPAL-α, and not only is their practicality demonstrated but also control performance is validated via Aircraft-In-the-Loop (AIL) testing under gust-free and realistic gusty conditions. This demonstration is at a Technological Readiness Level (TRL) of 7–8, resulting in a high-level of confidence in the validity of the proposed flight control structures.

A novel “feed-backward” control structure for on-demand control of distillation column sequences

The typical conventional plantwide control structure sets the flow rate of the fresh feed entering the process. Sometimes marketing or safety requirements dictate that the flowrate of the product leaving the process must be flow controlled. This structure is called “on-demand.” Important examples of chemicals that must be supplied on an “as-needed” basis include hydrogen, oxygen, synthesis gas, toxic hydrogen cyanide and explosive nitrotoluene. Since the output flow is fixed in an on-demand control structure, the material balance loops controlling liquid levels and gas pressures must work their way back upstream through the process to eventually adjust the fresh feed streams. A novel on-demand control structure is developed in this paper that reduces peak dynamic disturbances throughout the process by immediately changing upstream flow rates in a “feed-backward” manner when the product flow rate is changed.

An Adaptive Backstepping Sliding-Mode Control for Improving Position Tracking of a Permanent-Magnet Synchronous Motor With a Nonlinear Disturbance Observer

To provide reliable position control for a permanent-magnet synchronous motor (PMSM) under conditions of lumped disturbances such as external load torque fluctuation and system parameter variation, an adaptive backstepping sliding-mode control (ABSMC) with a nonlinear disturbance observer (NDO) is proposed. An ABSMC is a non-cascade technique that employs a position-current single-loop control structure rather than a conventional cascade control structure for vector control of the PMSM. This method uses Lyapunov theory to design a control law to ensure the motor position reaches a desired value in a finite period of time and consequently achieves a rapid transient response. The proposed ABSMC incorporates an adaptive convergence gain to avoid a large overshoot under point-to-point position command. The NDO with a nonlinear observer gain is proposed to estimate unknown disturbances and provide feed-forward compensation for the ABSMC, improving robustness and reducing steady-state position error. The proposed methods are applied to an industrial motor drive to confirm their validity in real-world operating environments.

Optimization and model-based control of sustainable ethyl-methyl carbonate and diethyl carbonate synthesis through reactive distillation

As excellent solvents of lithum-ion electrolyte, ethyl-methyl carbonate (EMC) and diethyl carbonate (DEC) are synthesized through transesterification of dimethly carbonate (DMC) and ethanol. Process intensification, optimization and the corresponding control scheme of the synthesized process are essential when sustainability is becoming a necessity. In the present work, the intensified flowsheet for EMC and DEC production process was firstly proposed and optimized with conventional reactive distillation (RD) and reactive dividing wall column (RDWC), respectively. Compared with RD process, RDWC could achieve 25.3% and 8.2% total annualized cost reduction for EMC and DEC production process, respectively. And carbon dioxide emission could be decreased by 29.4% and 11.7% by further integrating RD and separation column into RDWC arrangement for DEC and EMC production. Then multi-loop PI control schemes were developed as benchmark and linear model predictive controller was designed to handle the persistent feed disturbance. The superiorities of model-based controllers for the strongly interactive and coupled system are demonstrated by the dynamic response comparisons in terms of settling time, overshoot and integral of squared error (ISE), especially for the controlled variables with poor control performance under conventional multi-loop PI control structure. To summarize, the comprehensive control performance index-ISE with MPC is reduced by 55.9%–99.1%, as compared to those under PI control strategy.

Positioning control of liquid crystal elastomer actuator based on double closed-loop system structure

This paper proposes a control strategy with a double closed-loop system structure to achieve the positioning control of the photo-responsive liquid crystal elastomer (LCE) actuator. This work helps developing photo-responsive soft robot applications that are totally different from conventional electro-driven ones. In the proposed strategy, the outer loop is a combination of a PID controller in parallel with a feed-forward controller, the PID controller ensures that the positioning control target can be reached, and the feed-forward controller is an inverse model of the temperature-deformation relationship of the LCE actuator developed recently, to calculate the target temperature of the LCE actuator. The inner loop is a PID controller, which ensures that the temperature of the LCE actuator converges to the target value calculated by the feed-forward controller. Parameters of the inner PID controller are tuned using a simulation-experiment combined method based on the Hammerstein–Wiener model, and parameters of the outer PID controller are tuned based on experiments. Experiments are performed to show the effectiveness of the proposed method, and comparisons are made with conventional single closed-loop control structure. Such a double closed-loop structure has faster response and higher accuracy, and it lays a basis for possible photo-responsive soft robot applications.

Data-Driven Distributed Online Learning Control for Islanded Microgrids

In this paper, a new discrete-time data-driven distributed learning control strategy for frequency/voltage regulation and active/reactive power sharing of islanded microgrids is proposed. Instead of using the static droop relationship and the conventional primary-secondary hierarchical control structure, a new control framework is adopted and a neural network is used to learn the control law. The neural network is tuned online using the operational system input/output data with no training phase. As a result, the transient performance of microgrids is improved and a remarkable plug-and-play capability is also achieved. Moreover, the stability of the closed-loop system is analyzed through the Lyapunov approach, where the interactions between different distributed energy resources are considered. The effectiveness of the proposed method is demonstrated by real-time hardware-in-the-loop experiment of a typical microgrid.

Model-Free Parallel Predictive Torque Control Based on Ultra-Local Model of Permanent Magnet Synchronous Machine

The finite control set model predictive torque control (FCS-MPTC) selects the optimal voltage vector (VV) by the composite cost function composed of torque and flux error, which makes it have a faster dynamic response than conventional control methods. However, the prediction state error caused by machine parameter mismatch and the difficulty in setting the weight factor in the composite cost function seriously restrict the popularization and application of FCS-MPTC. In this paper, a model-free parallel predictive torque control (MF-PPTC) based on an ultra-local (UL) model is proposed to solve above problems. The UL model replaces the machine mathematical model without any machine parameters and only uses the input and output of the system, which greatly improves the robustness of the control system. The nonlinear extended state observer proposed for the unknown part of the system has fast convergence and improves the dynamic performance of the system. In addition, the conventional parallel predictive control structure is optimized to reduce the dynamic adjustment process during the selection of optimal voltage vector. Simulation and experimental comparison between the conventional PPTC and the proposed MF-PPTC verified the superiority of the proposed method.

A minimal architecture neuro adaptive predictive control scheme for power system stabilizer

The ever-increasing size and complexity of the present-day power systems puts a higher demand on the power system stabilizer for low-frequency oscillation damping. Alternate design methods of the conventional power system stabilizer or control structures to replace it, proposed over many decades, have not been widely adopted for practical use due to the impediments like non-linear and complex structure, and lack of fast adjustments. This paper proposes an improved neuro-adaptive control scheme, based on online system identification and simultaneous control, to replace conventional power system stabilizer. A simple, linear neural identifier, with a few adjustable connection weights, is used which ensures minimal computational burden and fast learning capability. The parameters of the controller, designed using optimal control with one-sample-ahead output prediction, are related to the identifier parameters. An adaptive learning rate, derived using Lyapunov stability theorems, guarantees stability of convergence of the learning algorithm as well as an optimal speed of convergence. Improved oscillation-damping performance over a wide range of operating conditions, in comparison with a well-designed conventional power system stabilizer and some other alternative controllers reported in literature, has been validated through simulation studies carried out on two different power systems. It is demonstrated that a simple linear neural identifier, which approximates a local linear model of a system, by adjustment of its parameters online, is faithfully able to track the varying dynamics of the system. Hence, it is not always appropriate to use complex structures and non-linear activation functions in neural network-based adaptive control applications which may pose difficulties in the implementation of these controllers. Also, the proposed control scheme is model-free, easier to implement and needs local measurements only.

Modeling and Adaptive Control Law Design for a Bi-Tiltrotor Unmanned Aerial Vehicle

This paper presents modeling and control law design for a bi-tiltrotor unmanned aerial vehicle for autonomous payload delivery. An ultralight bi-tiltrotor aerial vehicle was developed for a payload delivery contest using only two motors attached to a carbon fiber tube with an additional cube basket to carry the payload. To achieve desirable three-dimensional (3D) trajectory tracking performance with unknown payload, an adaptive control system has been developed, which consists of two components: (1) a baseline control law, including a lateral speed controller, forward speed controller, yaw angle controller, and altitude controller; and (2) an adaptive augmentation to all these four channels to compensate for modeling uncertainties and disturbances caused by the payload, which has large influence on system dynamics due to the light weight of the vehicle. A mathematical model of the vehicle has been built using the Newton-Euler method and simplified based on reasonable assumptions to facilitate control design. The baseline control law employs conventional proportional-derivative control structure. Subsequently, L1 adaptive control theory is adopted in the adaptive augmentation design. Simulation examples verify the efficacy of the proposed adaptive control solution.

Transfer Learning in Wastewater Treatment Plant Control Design: From Conventional to Long Short-Term Memory-Based Controllers.

In the last decade, industrial environments have been experiencing a change in their control processes. It is more frequent that control strategies adopt Artificial Neural Networks (ANNs) to support control operations, or even as the main control structure. Thus, control structures can be directly obtained from input and output measurements without requiring a huge knowledge of the processes under control. However, ANNs have to be designed, implemented, and trained, which can become complex and time-demanding processes. This can be alleviated by means of Transfer Learning (TL) methodologies, where the knowledge obtained from a unique ANN is transferred to the remaining nets reducing the ANN design time. From the control viewpoint, the first ANN can be easily obtained and then transferred to the remaining control loops. In this manuscript, the application of TL methodologies to design and implement the control loops of a Wastewater Treatment Plant (WWTP) is analysed. Results show that the adoption of this TL-based methodology allows the development of new control loops without requiring a huge knowledge of the processes under control. Besides, a wide improvement in terms of the control performance with respect to conventional control structures is also obtained. For instance, results have shown that less oscillations in the tracking of desired set-points are produced by achieving improvements in the Integrated Absolute Error and Integrated Square Error which go from 40.17% to 94.29% and from 34.27% to 99.71%, respectively.

Control of the azeotropic distillation process for separation of acetonitrile and water with and without heat integration

A novel acetonitrile/water azeotropic distillation scheme shows obvious economic advantages. It is of great significance to study the dynamic controllability of this process. In this work, the dynamic control structures of the non heat-integration and full heat-integration azeotropic distillation are studied. The control ability of the proposed control structures is tested by adding flow disturbance and composition disturbance. For the non heat-integration scheme, the conventional PID control structure and composition controller is used to achieve effective control when a disturbance occurs. For the full heat-integration scheme, the temperature difference control scheme and the composition controller are used to handle disturbances. This control structure reduces the stabilization time and makes the purity of the product return to the set value. The effect of different makeup flow on the purity of acetonitrile under different disturbances is discussed. Moreover, two control strategies are synthetically analyzed and compared by calculating integral of squared error. Considering economy and controllability, it is concluded that control strategy of heat-integrated azeotropic distillation has more advantages. This study has certain guiding value for the research of chemical dynamic control.

Robust current control scheme for single‐phase PWM rectifiers based on improved μ ‐synthesis in electric locomotive

The parameter perturbation of grid-side equivalent inductance is a significant feature of the uncertainty in the single-phase pulse-width modulation rectifiers system for the electric locomotive. This characteristic tends to reduce the robustness of the rectifier system. This study handles these problems in the framework of the structured singular value, which helps to reduce the influence of model parameter perturbation, caused by measurement error and operation condition change, on the robustness. However, the conventional μ-synthesis robust controls only reflect tracking and anti-disturbance performance by weighting functions and ignoring the dynamic response performance. Herein, a direct current control (DCC) scheme based on improved μ-synthesis is proposed. A desired closed-loop transfer function is introduced to the conventional μ-synthesis control structure to ameliorate the performance of the dynamic response. Furthermore, considering the external disturbances on the system control output, a suitable weighting function is used to restrict the external disturbance. The input–output relationship of the generalised open-loop plant can thus be constructed accordingly. The proposed control scheme is compared with the widely applied proportional–integral-based DCC scheme and the conventional μ-synthesis DCC scheme. Hardware-in-the-loop experiment results show promising dynamic performance as well as stronger robustness against parameter perturbation and external disturbances.

Optimised damping control of islanded DC power systems using state feedback

The voltage oscillation of islanded DC-power systems is probably caused by negative impedance, produced by the converter from conventional power control structure. In this study, the small disturbance linearised state equation of a DC-power grid with constant power load is derived to estimate the damping characteristics of DC voltage. To enhance the transient voltage stability, a novel DC-voltage damping control method is proposed, where both DC voltage and DC current are used as state-feedback variables. Furthermore, two state-feedback control loops are designed to regulate the duty cycle of buck–boost converter added to the energy-storage device. Using the root-locus method, the principle of system pole placement is further discussed to determine the optimal control parameters in the proposed feedback loops, so that the damping characteristics of power system can be optimised. Finally, experimental tests are conducted on a hardware-in-the-loop platform of a typical islanded DC-power system to validate the new control structure. The results demonstrate that the DC-voltage oscillation can be reduced rapidly, which greatly improves the transient stability of DC-power system.

Unified Disturbance-Estimation-Based Control and Equivalence With IMC and PID: Case Study on a DC–DC Boost Converter

In the context of disturbance-estimation (DE)-based control, it is reported that including desired dynamics into the nominal model yields a simple and compact control law that is easier to implement. The resulting control structure unifies the nominal feedback controller and feed-forward disturbance compensator to formulate an overall feed-forward disturbance compensation problem. Based on this, two popular DE-based techniques, namely active disturbance rejection control (ADRC) and uncertainty and disturbance estimator (UDE)-based control, are restructured into a unified form. By reformulating the controllers in the frequency domain, it is shown that the two structures are equivalent provided the UDE filter is selected based on the observer designed for ADRC. For an easier understanding of practitioners who are familiar with the conventional control structures, the designed controllers are reinterpreted in the framework of two-degree-of-freedom (2DoF) internal model control and 2DoF proportional-integral-derivative (PID) controller to show the equivalence among them. Tuning rules for PID controllers in terms of unified ADRC parameters are also presented to aid practical implementation in industry. Performance of the unified control scheme is evaluated on a non-minimum phase dc-dc boost converter that is operating under line and load disturbances using simulation and experimental study.

Control of a Supercapacitor-Battery-PV Based Stand-Alone DC-Microgrid

A non-linear control structure for a Photovoltaic (PV), battery and supercapacitor based stand-alone DC-microgrid is presented in this paper. Most of the conventional PI-based linear control structures reported in the literature have been designed around a single operating point and also supercapacitor voltage has not been regulated. Though supercapacitor voltage is regulated in some of the works, a dedicated controller has been used which increases controller count and makes designing/tuning of controllers together for desired system performance complicated. However, due to self-discharge or frequent discharge during operation, supercapacitor voltage can reach the lowest value which affects controller performance and even makes the system unstable. So, a robust non-linear controller: Interconnection Damping Assessment-Passivity Based Controller (IDA-PBC) is implemented as an outer loop controller to regulate DC-link and supercapacitor voltages. Also, a Finite Control Set-Model Predictive Control (FCS-MPC) which is intuitive in nature is implemented as inner current controllers. The proposed control structure is digital-friendly and can address the limitations of linear PI-control structure such as (i) Controller conflicts in designing the multiple controllers, (ii) Small region of stability (iii) Supercapacitor voltage regulation. Finally, the proposed control structure is verified through simulation and experimental results.

Impact of converter control strategy on low- and high-frequency resonance interactions in power-electronic dominated systems

The transient stability of power-electronic dominated systems such as wind farms and photo-voltaic power plants depends on the control settings of the involved converters, the grid resonances and the system’s operating conditions. This paper focuses on investigating the impact of converter control algorithms on possible interactions that could endanger the overall stability of these kinds of systems. Mainly, two control approaches namely the conventional cascaded control structure, consisting of an inner current-control loop and various outer-loop controls, and the immediate voltage control structure which generates the converter voltage directly from the power and voltage controllers without necessarily including a current-control loop, are compared. The latter control structure falls in the class of grid-forming control strategies and the impact of different variants of this control structure will also be investigated. For this purpose, the ac-side input admittance of a grid-connected converter is derived for the two approaches and passivity-based frequency-domain stability analysis is used to assess their impact on system stability. Finally, the analytical findings are verified through time-domain simulations and recommendations to increase system stability are given accordingly.

A hybrid control approach for the cracking outlet temperature system of ethylene cracking furnace

The main objective of this paper is to show the design and application on the cracking outlet temperature (COT) system using a hybrid control approach including non-minimal state-space model predictive control with an adjustable factor (AFNMSSMPC) and humanoid intelligent multimodality control (HIMMC) in two 100 k tone/year SC-1 ethylene cracking furnaces. Compared with the conventional control structure, the advanced control structure is designed based on the existing control problem. The advanced controller is developed at the platform of APC-ISYS software made by Zhejiang Supcon Company and implemented in an industrial upper computer which sets over and is connected with a CS3000 distributed control system (DCS) through OPCServer. In order to reduce the fluctuation of the COT, AFNMSSMPC is chosen as feedback controller, which guarantees system robustness together with tracking ability, and meanwhile HIMMC is as feed-forward controller based on the change in chamber temperature (measured disturbance), which can eliminate the effect on cracking outlet temperature (COT) in advance. The application results on COT of two ethylene cracking furnaces labeled M and N furnaces in practice using AFNMSSMPC-HIMMC compared to the traditional proportional–integral–differential (PID) control are presented. The standard deviation of COT reduces by 54.03% and 60.87% for M and N furnaces, respectively. The results show that the designed COT system has the capability of good tracking and strong disturbance rejection.

Flexible Control Structure for Enhancement of Scalability in DC Microgrids

In this article, a new control structure is proposed to improve the scalability of dc microgrids. Because conventional control structures require implementation of higher control level, subsystems that do not include them cannot be added in a microgrid. However, there are many subsystems in the field that do not support higher control level, which hinders microgrid scalability. For such subsystems to perform these functions, their local controller should be modified, which requires a lot of time and economic effort. In this article, by adding a new controller that performs higher control level without changing the local controller of subsystems, a structure to expand the scalability of a dc microgrid is proposed. The proposed flexible control structure consists of a local controller of subsystems, a flexible controller that performs higher control level, and microgrid central controller. A new communication network is required between local controller and flexible controller. However, due to a communication delay, the overall system stability is reduced. Therefore, problems related to the additional communication network were analyzed and a compensator was designed to overcome these issues. Through the flexible control structure, a subsystem that does not support higher control level can be added to dc microgrid.