Dynamic Control Performance Research Articles

Reconstruction design of a turbine generator foundation

The key to the reconstruction of turbine foundation is the dynamic performance control and the anti fatigue performance and durability of the new and old concrete interface. Based on the finite element analysis method, the natural vibration analysis of the steam turbine foundation before the reconstruction is carried out, and the calculation data of the natural vibration frequency and mode are compared with the field dynamic test data to verify the rationality of the finite element calculation model. On this basis, the natural vibration analysis and the harmonic response analysis of the reconstruction scheme are carried out, and the vibration line displacement of the key points of the disturbance force of the steam turbine foundation meets the vibration displacement control standard within the frequency range of 0 ∼ 62.5Hz. The static analysis is carried out for the transformation scheme, and the prestressed reinforcement is arranged to ensure the compression of the new and old interface; the project abandoned bonded rebars with limited service life and adopted self-locking anchors with the same life as the original structure to connect old and new concrete bonding surface. The low cycle fatigue test of self-locking bolt and concrete base material is carried out. The test results show that there is no fatigue failure, which shows that the reinforcement scheme can meet the requirements of fatigue resistance and durability.

Optimization of Proportional Integral Derivative Parameters of Brushless Direct Current Motor Using Genetic Algorithm

Optimal performance of the Brushless Direct Current (BLDC) motor is to be realized using an efficient Proportional Integral Derivative (PID) controller. However, conventional tuning technique fails to perform satisfactorily under parameter variations, nonlinear conditions and time delay. Also using conventional technique to tune the parameters gain of the PID controller is a difficult task. To overcome these difficulties, modern heuristic optimization technique are required to optimally tune the Proportional, Integral, Derivative of the controller for optimal speed control of three phase BLDC motor. Thus, genetic algorithm (GA) based PID controller was used to achieve a high dynamic control performance. The Brushless DC Motor mathematical equation which describes the voltage and corresponding rotational angular speed and torque of the brushless DC motor was employed using electrical DC Machines theorem. The Genetic algorithm was further analyzed by adopting the three common performance indices i.e. Integral Time Absolute Error (ITAE), Integral Square Error (ISE) and Integral Absolute Error (IAE) in order to capture and compare the most suitable BLDC Motor speed and torque control characteristics. All simulations were done using MATLAB (R2018a). The simulation result showed that the system with GA-PID controller had the better system response when compared with the existing technique of ZN-PID controller.

Improved Indirect Model Predictive Control for Enhancing Dynamic Performance of Modular Multilevel Converter

Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic performance. However, the high number of submodules in cascaded control means that the model predictive control for the modular multilevel converter suffers from a computational burden. Several approaches focused on reducing the computational burden based on limiting the number of possible switching states (possible choices) to be evaluated at each sampling instant. The dynamic performance of the modular multilevel converter is degraded in a transient state, despite the reduced computational burden. This paper presents an improved indirect model predictive control method to reduce the computational burden and enhance the dynamic performance. The proposed approach considers the steady-state and transient state individually and applies a different range of choices for each specific case. The range of choices during the steady-state is limited in order to reduce the computational burden without deteriorating the output quality, whereas the number of choices will be increased during the transient state to guarantee dynamic performance. The results that were obtained by implementing an experiment on a laboratory setup of a single-phase modular multilevel converter are presented in order to verify the proposed approach’s effectiveness. From the experimental setup, the computational time in the proposed approach was reduced by about 75% when compared with the conventional indirect model predictive control, whereas keeping fast dynamic performance.

High-speed nonlinear model predictive control of an interleaved switching DC/DC-converter

This paper presents a high speed nonlinear model predictive control (MPC) strategy for (interleaved switching) buck-type DC/DC-converters. Compared to known MPC strategies the proposed approach allows for longer prediction horizons while keeping the calculation times in the range of a few µs. This is achieved by tailoring the MPC strategy to the efficient implementation on an FPGA, exploiting the inherent parallel computation capabilities of FPGAs. Moreover, the utilization of a numerically efficient envelope model in the MPC is an important building block to reach the desired fast calculation times. The MPC strategy systematically takes into account input and state constraints, features a high dynamic and accurate control performance, exhibits constant switching frequencies and enables an interleaved switching operation. The proposed MPC strategy is tested in detailed simulations and in hardware-in-the-loop (HIL) experiments. An accurate and fast closed-loop dynamics can be achieved, also with respect to unknown fast load variations and parameter uncertainties. It is finally shown that the proposed MPC strategy has the potential to outperform the control performance of existing state-of-the-art controllers for DC/DC-converters.

Temperature Fluctuation Attenuation of Circulating Cooling Water Using Dynamic Thermal Filtering

The Demand for circulating cooling water (CCW) with high temperature stability and a quick response to temperature control is essential for precision engineering, so a dynamic thermal filtering method is proposed in this paper. Some CCW is bypassed, blocked, and used as a thermal capacity medium, and the temperature fluctuation of CCW is significantly reduced by heat exchanging with the medium. The temperature of the medium dynamically follows the set value of the CCW temperature by real time updating, and so realizes a quick CCW temperature control response. The attenuation ratio of temperature fluctuation was derived, theoretically validating the effectiveness of the method. The experimental results indicate that a CCW temperature fluctuation attenuation ratio of tens of dB (−3.47 dB, −6.91 dB, −10.97 dB and −15.28 dB corresponding to temperature fluctuation frequencies of 0.01 Hz, 0.025 Hz, 0.053 Hz and 0.105 Hz, respectively) is achieved by the proposed method. The updating time of thermal capacity medium is 82 s, which means that the temperature fluctuation attenuation remains functionally valid when the set value of CCW changes. The proposed method is low cost in operation and provides an effective approach to satisfy the challenging demand for CCW with high stability and a good dynamic temperature control performance.

Signal flow graph model and control of dual input boost converter with voltage multiplier cell

The dual input boost converter (DIBC) with dual boost and integrated voltage multiplier cell (VMC) operating in continuous conduction mode (CCM) at duty cycles larger than 0.5 is a necessity to deliver a high voltage gain for energy systems possessing two independent renewable energy resources (RES). However, the modelling of this higher order converter is challenging due to the overlapping switching signals, multi-stage operation and the parasitic elements. Thus this paper aims to develop the small-signal transfer function model by applying the signal flow graph (SFG) approach. In addition, to handle the output voltage regulation of this converter with unknown load values this paper presents the design of adaptive current-mode (ACM) control using an adaptive law to estimate the uncertain load resistance in terms of load conductance to compute the reference inductor currents. Two independent input inductor reference currents are considered to ensure the decoupling among the interacting loops. The dynamic performance of the ACM controller to handle unknown load and an improved version of a traditional control, the feedforward plus feedback controller for known values of load resistance are designed and assessed. A 200W converter model is built, and the controls are implemented using FPGA.

A Scheme to Improve Power Factor and Dynamic Response Performance for CRM/DCM Buck–Buck/Boost PFC Converter

Buck-buck/Boost power factor correction (PFC) converter is a great choice to compensate the inherent dead zones in the input current of buck PFC converter. However, whether the converter operates with traditional constant on-time control in critical conduction mode (CRM) or with conventional constant duty-cycle control in discontinuous conduction mode (DCM), the power factor (PF) is low, especially at low input voltage. Therefore, fixed on-time ratio control (FOTRC) and fixed duty-cycle ratio control (FDCRC) are proposed for CRM/DCM buck-buck/boost PFC converter to achieve high PF, respectively. Both control methods maximize PF over wide input voltage range by adjusting on-time or duty-cycle of buck/boost mode and buck mode. Compared with the traditional controls, the proposed control methods also have advantage of increasing efficiency. Furthermore, for improving dynamic response performance, smooth and rapid dynamic response control (SRDRC) is put forward, which can reduce the regulation time and output voltage overshoot/undershoot when the load or input voltage changes abruptly. In addition, the implementation circuits combining FOTRC/FDCRC and SRDRC are designed. Two prototypes have been built and tested in the lab to demonstrate the validity of the theoretical analysis.

A Library of Second-Order Models for Synchronous Machines

This article presents a library of second-order models for synchronous machines that can be utilized in power system dynamic performance analysis and control design. The models have a similar structure to that of the so-called classical model in that they consist of two dynamic states, the power angle and the angular speed. However, unlike the classical model, they find applications beyond first swing stability analysis, i.e., they can be utilized for multi-swing transient stability analysis. The models are developed through a systematic reduction of a nineteenth-order model using singular perturbation techniques. They are validated by comparing their response with that of the high-order model from which they were derived, as well as that of other synchronous machine models existing in the literature, such as the so-called two-axis model and the so-called one-axis model.

Development and application of multi servo motor system of environmental monitoring equipment based on DSP control

This paper provides a solution of synchronous control of 10-way Panasonic A6 servo motor using DSP chip (TMS320F28379D), which can obtain good dynamic performance and motion position control accuracy. The system uses PID control algorithm to realize intelligent control of position and speed of ten servo motors, and uses database to record the dynamic data of speed, time, distance and power of each servo motor. It can be used in the driving device of environmental monitoring equipment.

IMPROVEMENT IN SPEED PERFORMANCE OF AN INDUCTION MOTOR WITH SLIDING MODE CONTROLLER AND ANN FOR DTC

To further improve the dynamic speed control performance of an induction motor (IM) using a controller based on sliding mode control (SMC) strategy, the switching table for direct torque control (DTC) is realized using a feed forward artificial neural network (ANN). The proposed feed-forward ANN consists of three layers: input, hidden and output layer. The input layer consists of three neurons (sector of flux vector, electromagnetic torque error and stator flux error), the hidden layer consists of a number of neurons that can be determined by experiment to obtain good results. The output layer consists of three neurons (three signals of the converter Sa, Sb and Sc). Simulation results under MATLAB environment are presented and compared with classical DTC using an Integral-proportional (IP) controller to verify the proposed approach.

Event-triggered receding horizon control via actor-critic design

In this paper, we propose a novel event-triggered near-optimal control for nonlinear continuous-time systems. The receding horizon principle is utilized to improve the system robustness and obtain better dynamic control performance. In the proposed structure, we first decompose the infinite horizon optimal control into a series of finite horizon optimal problems. Then a learning strategy is adopted, in which an actor network is employed to approximate the cost function and an critic network is used to learn the optimal control law in each finite horizon. Furthermore, in order to reduce the computational cost and transmission cost, an event-triggered strategy is applied. We design an adaptive trigger condition, so that the signal transmissions and controller updates are conducted in an aperiodic way. Detailed stability analysis shows that the nonlinear system with the developed event-triggered optimal control policy is asymptotically stable. Simulation results on a single-link robot arm with different noise types have demonstrated the effectiveness of the proposed method.

Circulating Harmonic Currents Suppression of Level-Increased NLM Based Modular Multilevel Converter With Deadbeat Control

This article first analyzes the effect of the level-increased nearest level modulation (NLM) to the circulating current of the modular multilevel converter (MMC). The total inserted submodule (SM) number in one phase-leg of the MMC is variable using the level-increased NLM, which can significantly increase the peak-to-peak value of the circulating harmonic currents. Then, a circulating harmonic currents suppression method is proposed by applying deadbeat control for the MMC with level-increased NLM. Compared with the existing direct circulating current control approaches for the MMC, the proposed method presents specific extension and adjustment principle of the total inserted SM number. Therefore, the proposed method can improve the dynamic control performance and handle large circulating harmonic currents at steady state. And it can well coordinate the modulation and circulating harmonic currents suppression stages to avoid disturbing the ac-side output voltage while regulating the circulating current. The effectiveness of the proposed method is evaluated by a single-phase industrial-level simulated MMC system and a laboratory experimental platform.

Sliding-Mode Disturbance Observer-Based Control for Fractional-Order System with Unknown Disturbances

This paper concentrates on the disturbances estimation and attenuation problem of a general class of the fractional-order systems. For this purpose, this paper proposes a fractional sliding-mode disturbance observer (FSMDO)-based control scheme, which is capable of mitigating the unknown disturbances asymptotically. Meanwhile, by incorporating a novel fractional sliding-mode controller into the proposed control scheme, the asymptotical convergence of trajectory tracking errors is guaranteed. The developed control scheme owns three attractive highlights: (1) it is suitable for the general fractional-order systems, including nonlinear systems and incommensurate systems; (2) the proposed FSMDO can estimate the unknown exogenous disturbances and system uncertainties timely and precisely; (3) nominal performance can be retained by compensating the observed disturbances in a feedforward manner, and thus, the robustness of the system can be strengthened. Illustrative examples are provided to show the availability and superiority of the presented FSMDO control method in terms of robust control. As compared with the conventional methods, the dynamic control performance of the closed-loop system can be improved.

Model Predictive Direct Duty-Cycle Control for PMSM Drive Systems With Variable Control Set

Finite control set model predictive control has received extensive attention because of its excellent dynamic performance; however, it still needs to be studied in terms of torque ripples reduction and parameter robustness. To reduce the steady-state torque ripples and maintain the appropriate antiparameter perturbation ability, in this article, we propose a model predictive direct duty-cycle control (MPD2C) strategy based on “variable control set (VCS).” In the proposed strategy, the direct mapping relations between the electromagnetic torque, flux, and three-phase duty cycles have been established by exploring the dual relationship of vector synthesis and duty cycles. On this basis, the novel predictive model and VCS that uses the three-phase duty cycles as the key variable are constructed. Finally, the proposed strategy determines the three-phase duty cycles from VCS by employing a two-stage optimization mechanism, which means the proposed strategy can generate virtual vectors with multiple insulated gate bipolar transistor (IGBT) switching patterns. Then, the high-precision torque and flux adjustment would be achieved. The experimental results show that VCS-MPD2C has excellent static and dynamic control performance, acceptable execution efficiency, and relatively good parameter robustness.

Error-Driven Nonlinear Feedback Design for Fuzzy Adaptive Dynamic Surface Control of Nonlinear Systems With Prescribed Tracking Performance

This paper addresses an error-driven nonlinear feedback design technique to improve the dynamic performance of fuzzy adaptive dynamic surface control (DSC) for a class of uncertain multiple-input-multiple-output nonlinear systems with prescribed tracking performance. The highlight of the error-driven nonlinear feedback technique is that the feedback gain self-regulates versus different levels of output and virtual tracking errors, this reflects the classical control design criterions commendably: relatively high feedback gains can be implemented to guarantee disturbances and uncertainties attenuation and so on to improve the control performance when small tracking errors are measured, and relatively small feedback gains can be implemented to circumvent the problems of actuator and states saturations when large tracking errors are measured. The complexity problem of the traditional backstepping design is circumvented owe to the peculiarity of DSC method. Caused by the compound error functions of nonlinear feedback dynamics, a nonquadratic Lyapunov function is used to deduce the conditions of closed-loop stability. Fuzzy logic systems and error transformation-based method are used in the online learning of completely unknown dynamics and the prescribed performance tracking, respectively. Comparative results are presented to demonstrate the effectiveness and preponderance of the proposed control scheme with comparison to existing ones.

Modified STATCOM control strategy for fault ride-through capability enhancement of grid-connected PV/wind hybrid power system during voltage sag

This paper proposes the employment of Static Synchronous Compensator (STATCOM) in reactive power compensation to enhance the Fault Ride-Through (FRT) capability and improve the dynamic performance of a grid-connected PV/wind hybrid power system during the transient grid disturbances. The hybrid power system consisting of 9 MW Doubly Fed Induction Generator (DFIG)-based wind farm and 1 MW PV station is integrated with 100 MVAR STATCOM at the Point of Common Coupling (PCC) bus. The dynamic performance of the PV/wind hybrid power system with the proposed STATCOM controller is analyzed and compared with another FRT control strategy during a grid voltage sag. The FRT control strategy is based on the injection of reactive power from the hybrid system to enhance the FRT capability during the grid faults, and also activation of the outer crowbar protection system to protect the DFIG. On the other hand, the proposed STATCOM controller adjusts the PCC bus voltage during the grid disturbances by dynamically controlling the amount of reactive power injected to or absorbed from the electrical grid. Modeling and simulation of the proposed hybrid power system have been implemented using MATLAB/SIMULINK software. The effectiveness of both the proposed STATCOM controller and the FRT control strategy is evaluated during a 50% grid voltage sag. The simulation results illustrate that the STATCOM controller decreases significantly the level of voltage drop during the voltage sag, maintains the injected active power from the PV station at its rated value, and protects effectively the PV DC-link voltage from overvoltage. Moreover, when the STATCOM controller is employed, the injected active power from the wind farm is improved considerably and the oscillations of the DFIG rotor speed are reduced efficiently during the fault. Furthermore, the comparison confirms the superior dynamic performance of the STATCOM controller in enhancement the FRT capability as compared with the FRT control strategy.

A Lyapunov-Based Model Predictive Control Design With Reduced Sensors for a PUC7 Rectifier

This article proposes a Lyapunov-based model predictive control (MPC) design for a dual output multilevel rectifier. The investigated topology, a seven-level packed U-cell (PUC7) converter, is selected based on its high reliability, compactness, and low cost. The proposed controller has the following advantages over the conventional MPC controllers: First, no gain tuning is required; second, easy implementation; and third, reduced number of sensors (the load currents are estimated using the mathematical model of the PUC7 rectifier). Simulation and experimental results are provided to show the high dynamic performance and effectiveness of the Lyapunov-based MPC controller in tracking the output voltage references under grid change and parameters mismatch conditions.

Sliding Mode Control Based on Inversion Design and Bounded Input Constraint for Path Tracking of Mobile Robot

In order to solve the problem of path tracking of mobile robot, a sliding mode control strategy is proposed. Firstly, a sliding mode controller based on the inversion algorithm is designed, and the low-pass filter is used to reduce the interference in the control process. On this basis, for solving the problem that the dynamic performance of the previous controller is not ideal, the bounded input constraint is used to improve the control law. The simulation results show that the improved controller not only has good tracking effect and fast dynamic response, but also ensures the global asymptotically stability.

Adaptive levitation control for characteristic model of low speed maglev vehicle

Due to the strong coupling and large disturbance between multiple electromagnetic coils, the previous dynamic model of low-speed maglev train cannot accurately model the complex system when it is levitated. Therefore, based on the general linear transfer function, the concept of feature modeling is introduced to describe the dynamic characteristics, environmental characteristics and control performance requirements of the system by defining feature variables. On the premise of satisfying a certain sampling frequency, the original dynamic model is approximately linearized, which is equivalent to a second-order difference equation, i.e. a system with slow time-varying parameters. On this basis, the design and implementation of the controller of the magnetic levitation system are discussed. First, by studying the application of PID controller in suspension system, the difficulty of parameter debugging of PID controller and the insufficiency of restraining coupling interference are pointed out. The generalized predictive control (GPC) is proposed and improved to improve the robustness and anti-jamming of the system. Finally, a large number of simulations and experiments show that the controller can effectively suppress the coupling interference. Compared with single-point levitation controller, it has higher application value in engineering practice.

Energy-shaping-based nonlinear controller design for rotary cranes with double-pendulum effect considering actuator saturation

Dynamic performance analysis and controller design become more difficult when the load sway in rotary cranes exhibits double-pendulum characteristics. Furthermore, uncertain parameters and external disturbances in the crane system make it difficult for traditional methods to obtain satisfactory control performance. In addition, in an actual crane system, because of physical constraints, the output torque of the motors cannot be infinite. Therefore, the motor torque calculated by existing methods may exceed the maximum value, and actuator saturation will occur, which will affect the control performance. For this purpose, an energy-shaping-based nonlinear controller is presented after simplifying the original crane model. Stability analysis is carried out using the Lyapunov technique and LaSalle's invariance theorem. Numerical simulations validate that the proposed method can provide a robust control performance superior to that of traditional controllers.