Closed-loop Control Strategy Research Articles

Low order speed harmonic suppression in FOC-PMSM based on the closed-loop transfer mechanism of injected voltage

In the field oriented control (FOC) permanent magnet synchronous motor (PMSM) servo system, torque ripple impairs motor performance. Harmonic injection methods can suppress torque ripple by injecting additional voltage harmonic to offset the existing speed harmonic. However, since FOC is a closed-loop motion control strategy, the transfer path from injected voltage harmonic to speed harmonic is affected by FOC, especially in very low frequency. Due to the influence of FOC on the transfer function, the relation between the injected voltage harmonic and speed harmonic varies with operating conditions and motor control parameters. It causes the existing harmonic injection methods ineffective to suppress low order speed harmonics. To solve the problem, in this paper, the closed-loop transfer mechanism of injected voltage harmonics is analyzed and the closed-loop transfer function is derived. Based on the derived closed-loop transfer function, a low order speed harmonic suppression method is proposed. With the derived transfer function, the proposed method can adapt to the variations of the relation between low order injected voltage harmonic and speed harmonic under different operation conditions. Finally, the accuracy of the derived closed-loop transfer function and the effectiveness of the proposed low order speed harmonic suppression method are evaluated by experiment.

Design of a 20 kWth gasification reactor for harnessing energy from rice husks

Biomass energy is vital in the quest for sustainable and renewable energy sources. Despite the extended development of gasification, equipment malfunctions persist when using biomass that does not meet the expected technical specifications, requiring reactor designs based on fuel properties. Considering the limited information focused on the design of fixed-bed gasifiers for low-density biomass, this study presents the sizing of a gasification equipment to generate 20 kWth whilst taking rice husks as fuel into account. The main reactor dimensions were computed based on experimental tests performed in a low-complexity laboratory-scale gasification facility. This resulted in a throatless reactor with a diameter of 304.8 mm and 1-m length. Since the flame position using a closed-loop control strategy has not been reported for this type of reactor, a novel control methodology based on the signals of three thermocouples and a shaking system is proposed and demonstrated using modelling. This study aimed to develop widespread biomass gasification that derives environmental benefits.

Modeling and controlling a rotary piezo actuator

In this study, a novel piezo rotary stick–slip actuator was designed and investigated. This approach employs two piezo actuators to deform a flexible mechanism in order to generate a variable stick-and-slip force that drives the rotor. The compliant mechanism is composed of the bridge amplifiers and lever mechanism. They are arranged in sequence to amplify the piezo actuator's displacement. Hence, the operating range of the actuator, which includes rotation speed and resolution, can be increased. To optimize the fundamental dimensions of the actuator, the method of finite elements was investigated. The mechanical structure is detailed, the operating principle is elucidated, and a dynamic model is developed. From experimental data, the dynamic model of the structure is identified. The actuator achieves an angular displacement resolution of 0.028 degree at an applied voltage of 45 V and an operating frequency range up to 140 Hz, allowing it to be employed in applications requiring high precision positioning. Besides, the closed-loop control scheme is proposed to control the actuator in both directions. The simulation and experimental results have demonstrated that the position of the stick–slip actuator can be effectively controlled through this proposed controller. This is expected to increase the potential application of the stick–slip actuator in industrial practice.

Modeling the coupled aero-hydro-servo-dynamic response of 15 MW floating wind turbines with wind tunnel hardware in the loop

Accurate modeling and design tools are required to lower the cost of floating wind and enable the rapid growth that is expected in the next years. This paper presents a hardware-in-the-loop (HIL) wind tunnel experiment, showing it is a valuable tool to investigate the coupled response of two 15 MW floating wind turbines. In the HIL experiment, the wind turbine is emulated with a physical scale model, that is a 1:100 version of the IEA 15 MW, with reference closed-loop control functionalities. Rotor aerodynamic loads are continuously measured and fed back to a numerical simulation of the floater response. The output of the simulation are platform motions that are recreated in the wind tunnel with a robot. The two floating wind turbines are tested with various wind, waves, and turbine control conditions. It is shown the turbine scaled model matches with good accuracy the response of the IEA 15 MW, thanks to the aerodynamic re-design of blades and the adopted closed-loop control strategy. The HIL control system reproduces the coupling between turbine and platform with very small errors. In operational conditions, aerodynamic damping of platform motion is sensitive to wind speed when the turbine is controlled in closed loop, and it is shown that this is due to the coupling between platform pitch and rotor. The amount of aerodynamic damping just below the rated wind speed is found to be more uncertain than in other wind conditions.

Speed Estimation Strategy for Closed-Loop Control of PMSM Based on PSO Optimized KF Series Algorithms

In this paper, solving the problem of the noise covariance matrix parameters tuning of the extended Kalman filter (EKF) and unscented Kalman filter algorithms (UKF) is difficult. A speed estimation strategy for a permanent magnet synchronous motor (PMSM) based on particle swarm optimization (PSO) optimized Kalman filter (KF) series algorithms is proposed. By using MATLAB/Simulink, in this paper, 20 effective simulation experiments on the noise covariance matrix parameter optimization process are conducted to obtain the optimal covariance matrix parameters of the extended Kalman filter and unscented Kalman filter. Moreover, EKF, PSO-EKF, UKF, and PSO-UKF are also compared to verify the effectiveness of the particle swarm optimization algorithm in optimizing the systems using the extended Kalman filter and unscented Kalman filter. For the error of speed estimation, taking 4000 rpm as a reference, the system using PSO-EKF has improved by 2.125% compared to that using EKF, and the system applying PSO-UKF has improved by 0.55% compared to the system applying UKF. For the error of electrical angle estimation, taking the system errors of original algorithms as references, the system adopting PSO-EKF has decreased by 60% compared to that adopting EKF, and the system using PSO-UKF has decreased by 47% compared to the system using UKF.

Active band gap control of magnetorheological meta-plate using frequency feedback control law

An innovative special class of magnetorheological metamaterial is proposed to achieve a tunable band gap using a new frequency feedback control law. By using the frequency feedback control law, the active band gap can intelligently track the external excitation frequency. The active control function of the band gap is realized using an intelligent local resonator embedded in the plate. Such a local resonator consists of a mass and a magnetorheological elastomer (MRE) driven by an external magnetic field. The local resonator and metamaterial plate are modeled analytically, and an analytical expression is derived to predict the band gap region. The effect of the external magnetic field on vibration attenuations is analyzed by the Galerkin method. Subsequently, a closed-loop frequency feedback control strategy is used to actively adjust the band gap according to the excitation frequency. Based on this frequency feedback control strategy, the effective band gap range of the metamaterial plate can be largely widened. The effect of damping of the MRE on broadband vibration reduction is also investigated, and the results show that the damping of the MRE plays an important role in the control of the band gap of the magnetorheological metamaterial.

Maximum Convergence Rate Control of a Switched Electrical Network with Symmetries

The purpose of the present research endeavor is to propose a novel control strategy for a DC-DC electrical converter realized as a switched circuit. The present endeavor is based on an early work by Leonard and Krishnaprasad where a prototypical DC-DC converter was modeled as a state space dynamical system and controlled by an open-loop strategy based on Lie group theory. In this work, we shall rather introduce a closed-loop control strategy based on maximum convergence rate, study some features of the novel method, and illustrate its behavior by numerical simulations. A numerical comparison of the two methods complements the paper. The numerical comparison shows how the proposed feedback control method outperforms the static one in terms of convergence rate and resiliency against parameters mismatch.

A deep reinforcement learning-based power control scheme for the 5G wireless systems

In the fifth generation (5G) wireless system, a closed-loop power control (CLPC) scheme based on deep Q learning network (DQN) is introduced to intelligently adjust the transmit power of the base station (BS), which can improve the user equipment (UE) received signal to interference plus noise ratio (SINR) to a target threshold range. However, the selected power control (PC) action in DQN is not accurately matched the fluctuations of the wireless environment. Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network (DNN). As a result, the Q-value of the sub-optimal PC action exceed the optimal one. To solve this problem, we propose the improved DQN scheme. In the proposed scheme, we add an additional DNN to the conventional DQN, and set a shorter training interval to speed up the training of the DNN in order to fully train it. Finally, the proposed scheme can ensure that the Q value of the optimal action remains maximum. After multiple episodes of training, the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment. As a result, the UE received SINR can achieve the target threshold range faster and keep more stable. The simulation results prove that the proposed scheme outperforms the conventional schemes.

Distributed Dual Closed-Loop Model Predictive Formation Control for Collision-Free Multi-AUV System Subject to Compound Disturbances

This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme.

Design and Analysis of XY Large Travel Micro Stage Based on Secondary Symmetric Lever Amplification.

This study presents a newly developed piezoelectric drive mechanism for the purpose of designing, analyzing, and testing a micro-positioning platform driven by piezoelectric actuators. The platform incorporates a piezoelectric ceramic actuator and a flexible hinge drive and features a symmetrical two-stage lever (STSL) amplification mechanism and a parallelogram output structure. The implementation of this design has led to notable enhancements in the dynamic properties of the platform, thereby eliminating the undesired parasitic displacement of the mechanism. An analytical model describing the fully elastic deformation of the platform is established, which is further verified by finite element simulation. Finally, the static and dynamic performances of the platform are comprehensively evaluated through experiments. A closed-loop control strategy is adopted to eliminate the nonlinear hysteresis phenomenon of the piezoceramic actuator (PEA). The experimental results show that the piezoelectric micro-actuator platform has a motion range of 97.84 μm × 98.03 μm; the output coupling displacement error is less than 1%; the resolutions of the two axes are 8.1 nm and 8 nm, respectively; and the x-axis and y-axis trajectory tracking errors are both 0.6%. The piezoelectric micromotion platform has good dynamic properties, precision, and stability. The design has a wide application potential in the field of micro-positioning.

Inductive sensing of magnetic microrobots under actuation by rotating magnetic fields.

The engineering space for magnetically manipulated biomedical microrobots is rapidly expanding. This includes synthetic, bioinspired, and biohybrid designs, some of which may eventually assume clinical roles aiding drug delivery or performing other therapeutic functions. Actuating these microrobots with rotating magnetic fields (RMFs) and the magnetic torques they exert offers the advantages of efficient mechanical energy transfer and scalable instrumentation. Nevertheless, closed-loop control still requires a complementary noninvasive imaging modality to reveal position and trajectory, such as ultrasound or X-rays, increasing complexity and posing a barrier to use. Here, we investigate the possibility of combining actuation and sensing via inductive detection of model microrobots under field magnitudes ranging from 100 s of microtesla to 10 s of millitesla rotating at 1 to 100 Hz. A prototype apparatus accomplishes this using adjustment mechanisms for both phase and amplitude to finely balance sense and compensation coils, suppressing the background signal of the driving RMF by 90 dB. Rather than relying on frequency decomposition to analyze signals, we show that, for rotational actuation, phase decomposition is more appropriate. We demonstrate inductive detection of a micromagnet placed in two distinct viscous environments using RMFs with fixed and time-varying frequencies. Finally, we show how magnetostatic selection fields can spatially isolate inductive signals from a micromagnet actuated by an RMF, with the resolution set by the relative magnitude of the selection field and the RMF. The concepts developed here lay a foundation for future closed-loop control schemes for magnetic microrobots based on simultaneous inductive sensing and actuation.

Dual-Loop Control of Cable-Driven Snake-like Robots

Snake-like robots, which have high degrees of freedom and flexibility, can effectively perform an obstacle avoidance motion in a narrow and unstructured space to complete assignments efficiently. However, accurate closed-loop control is difficult to achieve. On the one hand, this is because adding too many sensors to the robot will significantly increase its mass, size, and cost. On the other hand, the more complex structure of the hyper-redundant robot also challenges the more elaborate closed-loop control strategy. For these reasons, a cable-driven snake-like robot, which is compact and low cost, with force transducers and angle sensors, is designed in this article. The simpler and more direct kinematic model is studied, which applies to a widely used kinematics algorithm. Based on the kinematic model, the inverse dynamics are resolved. Finally, this article analyzes the sources of the motion errors and achieves dual-loop control through force-feedback and pose-feedback. The experiment results show that the robot’s structure and dual-loop control strategy function with high accuracy and reliability, meeting the requirements of engineering applications and high-precision control.

Three-Level Isolated Direct AC–AC Converter and its Closed-Loop Control Strategy

The isolated direct AC-AC converter has the advantages of high power density and long life time, however, suffering from the high cost and relatively low efficiency. In this paper, a three-level isolated direct resonant AC-AC converter is proposed, thus the voltage stress of power switches reduce to half of the input voltage amplitude and as a result, the voltage rating of the power switches is reduced. A hybrid modulation strategy for the proposed converter is proposed to realize the AC-AC conversion and reduce the switching power loss. Furthermore, in order to obtain a good control of the output voltage based on the proposed converter, the closed-loop control strategy of the output voltage combining a linear controller with the repetitive controller is proposed and the detailed parameters design rule is discussed. The proposed control strategy not only realizes the sinusoidal output voltage waveforms and good dynamic performance, but also effectively eliminates the effect of input voltage harmonics. The corresponding proposed topology, modulation and closed-loop control strategy are all verified by the detailed experimental results.

High-Performance Wireless Charging System Using Interleaved Buck Converter and Integrated Solenoid Magnetic Coupler

This paper proposes a wireless charging system (WCS) with the secondary-side interleaved Buck converter (SIBC) and multi-coil integrated solenoid magnetic coupler (ISMC). Then the constant current/constant voltage (CC/CV) charging based on SIBC duty cycle regulation is realized with high misalignment tolerance. First, the working principle and parameter design of the WCS is analyzed. Second, the ISMC structure is optimized, then the coupling condition comparison proves the high anti-misalignment capability. Besides, both the LCC inductor and SIBC filter inductors are integrated into the ISMC without affecting the power transfer. Third, the small-signal model of SIBC is set up, combined with the simulation results, the closed-loop control scheme for CC/CV charging is confirmed. Finally, the experimental results validate the feasibility of the proposed WCS with high performance.

Layer-to-layer closed-loop feedback control application for inter-layer temperature stabilization in laser powder bed fusion

In laser powder bed fusion (LPBF), part quality and process conditions are highly dependent on the interlayer temperature (ILT) of the exposure surface of printed parts. State-of-the-art closed-loop control applications do not stabilize ILT, which has a decisive influence on the resulting part properties. This paper presents a closed-loop control strategy for LPBF that stabilizes the ILT. The thermal balance is defined with respect to exposure area change in overhanging parts and a control strategy is proposed to maintain the thermal balance by actuating energy input. The proposed control strategy uses an off-axis thermal camera for interlayer temperature acquisition to update the laser power layer to layer. An online optimization-based controller that leverages the repetitive nature of the LPBF process is implemented for the task. The developed controller is validated by experiments with different overhanging geometries. Successful ILT stabilization for various overhanging angles shows the robustness of the controller for an extended number of layers. However, modulation of laser power alone is shown to be insufficient to maintain the ILT within the stable processing window due to excessive heat accumulation in the long term. Nevertheless, the results of this study demonstrate the feasibility of ILT stabilization via of closed-loop control in LPBF and the potential for significant improvements in stabilizing the properties of the printed parts.

Lithium Titanate battery-based frequency modulation control strategy for doubly fed induction generator

This paper proposes a Lithium Titanate battery-based primary frequency regulation strategy for doubly fed induction generators to solve the problems of a decrease in power generation efficiency and an increase in turbine losses under a traditional over-speed load shedding control strategy. A stator voltage orientation-based dual closed-loop control strategy for the vector control system is designed for the PWM rotor converter. A grid voltage-oriented vector control is adopted for the grid converter to maintain the stability of DC bus voltage. To enable a single doubly fed induction generator to have primary frequency regulation capability, a dual Lithium Titanate energy storage device is installed on the DC bus to improve the power generation efficiency of the unit. Modeling and analysis on Matlab/Simulink to verify that the proposed control strategy not only ensures the economic benefits of the generator’s electricity but also enables the generator to have good frequency regulation capability.

A Novel Control Scheme for Induction Generator Based Stand-alone Micro Hydro Power Plants

A system comprising of a hydraulic turbine (HT) driven induction generator with excitation capacitor (IGEC) has been proposed for providing electricity to the residents living in remote areas and steep terrains, wherein the grid connection is unviable. The available water resource in such locations is effectively utilized and the load on the generator terminals is set, based on the requirement of the consumer demand. A method has been formulated for the estimation of excitation capacitor and rotor speed for ensuring nominal voltage and frequency at the generator terminals, regardless of variation in the consumer load. This design procedure is based on the analysis of IGEC employing the binary search algorithm (BSA). The logical way of arriving at the range of per unit (pu) speed to start the BSA has also been illustrated. A closed-loop control scheme has also been formulated, by taking generator voltage as the feedback variable and comparing the voltage set limits Vmin and Vmax. Accordingly, a controller action is initiated to add or disconnect the flexible loads. An available mathematical modeling of HT has been modified suitably and by using this model, the functioning of the proposed system with respect to the HT characteristics and generated frequency of IGEC has also been investigated. Using a MATLAB/Simulink software, the successful functioning of the proposed system has been demonstrated with typical operating conditions. The predetermined values and simulated observations are amply supported with the laboratory results conducted on a 3-phase, 3.7 kW IGEC.

Model-based closed-loop control strategies for flex-fuel capability

Meeting future limits for greenhouse gas (GHG) and pollutant emissions represents major challenges for the further development of internal combustion engines for light and heavy-duty applications. To comply with increasingly higher standards, the use of renewable fuels is an important option due to their great potential in terms of energy density, sustainability and low-pollution combustion. However, the increased fuel diversity associated with their use increases the complexity of the powertrain development and calibration process, resulting in an increase in development time and cost. To address these challenges, advanced model-based closed-loop control strategies are applied to optimize the fuel- and air-path settings and make best use of the properties of the different fuels. One such approach is Combustion Rate Shaping (CRS). This ensures a closed-loop control of combustion parameters such as the indicated mean effective pressure, the center of heat release, and the combustion noise excitation. In addition, a model-based closed-loop NOx control could simplify the control on the air-path side. Such a closed-loop approach can further be combined with an onboard fuel detection algorithm and learning functionalities that eventually allow switching to optimal setpoints based on the fuel properties. This publication presents an evaluation of CRS as control concept with flex-fuel operation. The control strategy is implemented on a demonstrator vehicle built up with a Rapid Control Prototyping (RCP) system. The results of emission test cycles with conventional diesel fuel and later with a blend with 1- Octanol, OME3–5 and a paraffinic renewable diesel fuel are presented to illustrate the potential of the novel control concept. The developed CRS concept shows a reduced combustion parameters and emissions dispersion. In particular, the results with OME3–5 blend shows up to 40% reduction in NOx emissions and up to 1 dB(A) lower average combustion noise in comparison to conventional open-loop control. Moreover, an onboard fuel detection and an adaptive control functionality are proposed and experimental validations are carried out to demonstrate the potential to optimize engine emissions.

A Linear-Parameter-Varying Formulation for Model Predictive Perimeter Control in Multi-Region MFD Urban Networks

An alternative approach for real-time network-wide traffic control in cities that has recently gained attention is perimeter flow control. Many studies have shown that this method is more efficient than state-of-the-art adaptive signal control strategies for heterogeneously congested urban networks. The basic concept of such an approach is to partition heterogeneous cities into a small number of homogeneous regions (zones) and apply perimeter control to the interregional flows along the boundaries between regions. The transferring flows are controlled at the traffic intersections located at the borders between regions so as to distribute the congestion in an optimal way and minimize the total delay of the system. The focus of current work is the mathematical formulation of the original nonlinear problem in a linear parameter-varying (LPV) form so that optimal control can be applied in a (rolling horizon) model predictive concept. This work presents the mathematical analysis of the optimal control problem as well as the approximations and simplifications that are assumed in order to derive the formulation of a linear optimization problem. Numerical simulation results for the case of a macroscopic environment (plant) are presented in order to demonstrate the efficiency of the proposed approach. Results for the closed-loop model predictive control scheme are presented for the nonlinear case, which is used as “benchmark,” as well as the linear case. Furthermore, the developed scheme is applied to a large-scale microsimulation of a European city with more than 500 signalized intersections in order to better investigate its applicability to real-life conditions. The simulation experiments demonstrate the effectiveness of the scheme compared with fixed-time control because all of the performance indicators are significantly improved. Funding: This work was supported by Dit4Tram “Distributed Intelligence & Technology for Traffic & Mobility Management” project from the European Union’s Horizon 2020 research and innovation programme under [Grant agreement 953783].

Passive machine vision-based defect classification in tungsten inert gas welding on SS304 using AI-based gradient descent algorithm

In modern digitization, safety industries demand flaw-free and high-integrity welds, due to part localization on high uncertainty makes automation a challenging task. Integrating robotic welding with high-value manufacturing sector makes volume rise through pre-programmed repetitive performance on desired welding space. Further, the establishment of fully automated robotic-based welding operations with different configurations on controlled localization is the least available due to unviable cost. Hence, the proposed work concentrates on internet of things (IoT)-driven robotic tungsten inert gas (TIG) welding on stainless steel (SS) 304 by incorporating online programming (OP) with visual control schemes to classify the nature of weld quality using an artificial neural network. Continuous sensory-guided techniques with IoT high-level operator interface affords automated welding planning by using feature matching strategies. Area scan-based complementary metal oxide semiconductor (CMOS) cameras have been used to capture passive vision real-time images of the weld species for defect classification. In real-time, discrete reference workpiece and image feature extraction processes seem to be complicated in an unstructured welding environment. Hence, the present idea will enhance the efficiency of high product variance, but the accuracy of the automation relies on the weld image database. The proposed method (a) adaptively regulates its welding parameter variation on the welding trajectory path, (b) adapts and produces precise good weld workpieces with a 92% production rate with flaw-free welds and (c) initiates the automatic tuning of robot kinematics through IoT closed-loop online external control strategy. The proposed research experimental results confirm that fully automated IoT-driven robotic TIG welding affords good welding with an 88% improved quality rate through online passive vision-based image feature analysis.