Rapid Control Prototyping Research Articles

A Two-Stage Real-Time Optimized EV Battery Cooling Control Based on Hierarchical and Iterative Dynamic Programming and MPC

The battery thermal management (BTM) system plays an increasingly important role today in the safety of electric vehicles (EVs) and hybrid electric vehicles (HEVs) as the battery capacity and power ratings keep growing. The BTM system is commonly coupled with the vehicle passenger cabin HVAC system. This integrated thermal system is a major onboard energy consumer, and its complexity brings challenges to its control. With the planned-ahead speed profile and the corresponding power trajectory obtained from the connected and automated vehicle (CAV) technology, predictive control makes a desirable option for the integrated system to maintain battery safety and passenger comfort while lowering energy consumption. However, in order to achieve both high accuracy and low cost in a wide control range, a very long prediction horizon and high sampling rate are both necessary. This will overwhelm the processing capacity of the onboard electronic control unit (ECU) if using conventional predictive control. In this paper, a two-stage predictive control strategy for the BTM and HVAC coupled system is proposed to solve this problem. In stage 1, based on the integrated cooling system efficiency features, a hierarchical and iterative dynamic programming (HIDP) scheme is designed to derive the optimal battery temperature trajectory to reach the set point at the end of the horizon with a modest computation burden. In stage 2, a control-oriented model is constructed for the cooling system and a model predictive controller (MPC) is accordingly built to track the trajectory from Stage 1 while enforcing the energy saving. A high set-point-tracking performance and as high as 10.61% energy saving for the cooling system in the UDDS cycle are verified by simulation results. The real-time implementation capability of the proposed strategy is demonstrated by the vehicle emulator experiments based on hardware in the loop (HIL) and a rapid control prototyping (RCP) platform.

Adaptive droop control strategy for Flywheel Energy Storage Systems: A Power Hardware-in-the-Loop validation

Low-inertia power systems can suffer from high rates of change of frequency during imbalances between the generation and the demand. Fast-reacting storage systems such as a Flywheel Energy Storage System (FESS) can help maintain the frequency by quickly reacting to frequency disturbances, with no concern over its lifetime. While a modern high-speed FESS has a significantly higher energy density than the conventional low-speed ones, the capacity of this storage technology is still limited. Therefore, this paper proposes a new adaptive droop controller for a FESS, considering the practical advantages and also limitations of this storage technology. The proposed controller increases the contribution of the FESS for frequency support during the first instances of a disturbance, while it reduces its output when the frequency is recovering. To verify the advantages of the proposed control strategy, the controller is implemented on a real 60 kW high-speed FESS using the concept of rapid control prototyping. Next, the performance of the FESS with the new controller is tested using Power Hardware-in-the-Loop simulations in a low-voltage microgrid. The PHIL simulation results show that the proposed adaptive controller improves the performance of the FESS in terms of limiting the frequency deviations, while preserving more energy in the FESS.

Combustion rate shaping for flex-fuel applications

Compliance with future greenhouse gas (GHG) and pollutant emissions poses major challenges for the further development of advanced internal combustion engines for light and heavy-duty applications. To meet all standards, the use of synthetic fuels and/or E-Fuels is an important alternative due to their enormous potential in terms of energy density, sustainability and low pollution combustion. However, the increased fuel diversity associated with the use of these alternative fuels adds an additional layer of complexity to the powertrain development and calibration process, resulting in an increase in development time and cost. This necessitates the application of advanced model-based closed-loop control strategies to optimize the fuel- and air-path calibration to make best use of the properties of the different fuels. One potential solution to address the impact of flex-fuel variances on the combustion process is the Combustion Rate Shaping (CRS) concept presented in this paper. It can maintain a desired combustion trace irrespective of fuel variations, hardware drifts and other external factors, thus ensuring optimal combustion. The highest benefit of this control concept comes from its application directly on the engine control unit (ECU) in combination with an in-cylinder measurement. This enables the online real-time control of the combustion, regardless of which fuel is being used. In addition, this also enables optimization and adaption of the fuel- and air-path settings to the used fuel while driving the vehicle. However, so far, the high computational cost of this control concept limits its real-time capability. Therefore, the optimization of the control concept to achieve real-time capability is the focus of this paper. The optimized control strategy is implemented on a demonstrator engine test bench built using a Rapid Control Prototyping (RCP) system. The controller performance is demonstrated both under steady-state and transient operating conditions, and the potential of the concept is demonstrated in several cases such as engine temperature variations, injector drift, individual cylinder balancing, and fuel-variation.

Sliding-Mode Control Algorithm for DFIG Synchronization to Unbalanced and Harmonically Distorted Grids

In order to smoothly connect to permanently disturbed grids, DFIG-based wind turbines must precisely synchronize the voltage induced at their open stator with that of the grid. Hence, aiming at addressing the still unpublished task of synchronizing DFIGs to simultaneously unbalanced and harmonically distorted grids, a phase-locked loop (PLL)-less and naturally chatter-free sliding-mode control (SMC) algorithm is proposed. The strategies developed so far were formulated considering synchronous reference frames. However, by designing a stationary reference frame-based solution, decomposition into positive- and negative-sequences and harmonic components is avoided. As a result, a relatively straightforward control structure with strong potential for industrialization is obtained, consisting of a single voltage loop per component with just one parameter to be tuned. The stability and robustness resulting from its application are analytically studied under both uncertainties and disturbances. Additionally, a simple method for rotor positioning, independent of grid disturbances, is provided. Simulation over a 2-MW DFIG model and rapid control prototyping (RCP) over a 7-kW DFIG experimental rig are carried out. In this way, the performance and robustness of the suggested control scheme are validated under both unbalanced and harmonically distorted grid voltage, substantial parameter deviations, and varying wind speed and grid frequency profiles.

Real-time Implementation of a Single Phase Asynchronous Motor Drive, Feeding within an Open Energy Source

A modified nanogrid (MnG) is a very small scalable grid with a low power single-input multi-output (SIMO) inverter. This inverter simultaneously produces both AC and DC currents, such as the switched boost inverter (SBI) and the z-source inverter. These inverters are suitable for low-power loads such as home appliances that use fractional horse-power motors as single-phase asynchronous drives. Thus, this article proposes a single-phase induction motor powered from a modified nanogrid that involves multiple types of inverters such as a SBI and a ZS inverter. The modified nanogrid is mainly dependent on photovoltaic (PV) as a renewable resource. Thus, this manuscript involves a full design for this proposed grid with its maximum power point tracking (MPPT) and the mathematical models for motor drive with both a SBI and a ZSI. Time-varying speed trajectories are proposed to test the robustness of the proposed drives relative to the fluctuation of PV-parameters like its irradiance. Test results are obtained using the Matlab/ Simulink software package and a comparison with the traditional sinusoidal pulse width modulation (SPWM) inverter as a single-input single-output inverter (SISOI). The results indicate that the proposed single-input multi-output inverters are suitable for driving these motors through start-up and operation, although the DC-link voltage is minimized. Furthermore, the proposed system is experimentally implemented with OPAL RT-4510v real-time hardware in the loop (HIL), rapid control prototyping, and OP-8660 HIL controller and data acquisition platform.

Rapid Control Prototyping of Five-Level MMC based Induction Motor Drive with different Switching Frequencies

In this paper, Rapid Control Prototyping (RCP) of five-level Modular Multilevel Converter (MMC) based Induction Motor (IM) drive performance is observed with different switching frequencies. The Semikron based MMC Stacks with two half-bridge each are tested with the switching logic generated by phase and level shifted based Sinusoidal Pulse Width Modulation (SPWM) technique. The switching logic is generated by the Typhoon Hardware in Loop (HIL) 402. The disadvantages of Multilevel Converter like not so good output quality, less modularity, not scalable and high voltage and current rating demand for the power semiconductor switches can be overcome by using MMC. In this work, the IM drive is fed by MMC and the experimentally the performance is observed. The performance of the Induction Motor in terms of speed is observed with different switching frequencies of 2.5kHz, 5kHz, 7.5kHz, 10kHz, 12.5kHz and the results are tabulated in terms of Total Harmonic Distortion (THD) of input voltage and current to the Induction Motor Drive. The complete model is developed using Typhoon HIL 2021.2 Version Real-Time Simulation Software.

Efficient adaptive controllers and recursive filters for centralized control scheme of islanded microgrid with linear and non-linear loads

This paper presents a new combination of adaptive controllers and recursive filters for the operation of the microgrid with different balanced, unbalanced, and nonlinear loads. The suggested control scheme has the cascaded structure of voltage and current loops for positive- and negative-sequence control. The suggested adaptive controllers are the single-perceptron-based PI controller (the 1st adaptive controller) and the least mean fourth-based PI controller (the 2nd adaptive controller). The 1st adaptive controller is employed with the voltage control loop, while the 2nd adaptive controller is integrated with the current control loop. The Gauss-Newton algorithm is newly formulated to recursively estimate the voltage fundamental/harmonics at the load side. The suggested adaptive controllers are compared with other controllers for the same microgrid operation. The practical implementation of the suggested control scheme along with its adaptive controllers and recursive filters is validated using the dSPACE-SCALEXIO platform using rapid control prototyping.

Robust constraint-following control for permanent magnet linear motor with optimal design: A fuzzy approach

In this paper, robust constraint-following control (RCFC) with the optimal design is developed to handle the trajectory tracking control issues for permanent magnet linear motor (PMLM), which control performance is deteriorated mainly by friction, ripple force, and external disturbance. Specifically, a fuzzy description for the main nonlinearity of the PMLM system and its fuzzy dynamic model is formulated. Then, the tracking specification is modeled as a performance constraint, the RCFC algorithm following the Udwadia-Kalaba theory is designed to comply with this constraint, and possess strong robustness to uncertainties simultaneously. The resulting controller is demonstrated to be uniform bounded and uniform ultimate bounded with Lyapunov analysis. Furthermore, the optimal design issue via a fuzzy approach is investigated to achieve the optimal tradeoff between control effort and system performance. Finally, the rapid control prototype platform CSPACE is employed to implement the real-time control while avoiding time-consuming repetitive programming and debugging. Simulation and experimental results illustrate the actual effectiveness of the proposed algorithm.

Rapid DNA origami nanostructure detection and classification using the YOLOv5 deep convolutional neural network

The intra-image identification of DNA structures is essential to rapid prototyping and quality control of self-assembled DNA origami scaffold systems. We postulate that the YOLO modern object detection platform commonly used for facial recognition can be applied to rapidly scour atomic force microscope (AFM) images for identifying correctly formed DNA nanostructures with high fidelity. To make this approach widely available, we use open-source software and provide a straightforward procedure for designing a tailored, intelligent identification platform which can easily be repurposed to fit arbitrary structural geometries beyond AFM images of DNA structures. Here, we describe methods to acquire and generate the necessary components to create this robust system. Beginning with DNA structure design, we detail AFM imaging, data point annotation, data augmentation, model training, and inference. To demonstrate the adaptability of this system, we assembled two distinct DNA origami architectures (triangles and breadboards) for detection in raw AFM images. Using the images acquired of each structure, we trained two separate single class object identification models unique to each architecture. By applying these models in sequence, we correctly identified 3470 structures from a total population of 3617 using images that sometimes included a third DNA origami structure as well as other impurities. Analysis was completed in under 20 s with results yielding an F1 score of 0.96 using our approach.

Robust control technique in power converter with linear induction motor

Induction motors are widely used in industrial applications as actuators, thanks to their simplicity of construction, which is subsequently reflected in low-cost maintenance. This paper shows the behavior of a three-phase power converter with a linear induction motor (LIM) as load, using a quasi-sliding control technique for output voltage regulation and a new control technique to control chaos. Digital pulse width modulation (DPWM) techniques are widely used to control electronic power converters. The controller proposed in this paper was designed using zero average dynamic (ZAD) and fixed point inducting control (FPIC) techniques. The ZAD-FPIC control strategy was designed and applied to a three-phase converter with linear induction motor load. Since it is not possible to measure the secondary currents, a secondary current observer was included in the system. Finally, bifurcation diagrams are shown as a technique for tuning controller parameters in ZAD-FPIC controllers. For the illustration of numerical results a simulation of the linear induction motor drive controlled was made by MATLAB/Simulink. The designs were tested in a rapid control prototyping (RCP) system based on digital signal processing (DSP) for dSPACE platform, using the 1103 controller card and control desk interface.

An Observer-Based Harmonic Extraction Method with Front SOGI

With the further development of harmonic pollution in the power system, scientists have carried out research on harmonics. Among them, harmonic detection is the first step in harmonic research. In this paper, a harmonic detection method based on an observer is proposed. This method first uses the cascaded Second-Order Generalized Integration (SOGI) algorithm, which can filter the Direct Current (DC) component of the input signal to extract the fundamental frequency, and then uses a time-varying observer to extract the harmonics. This can be used to extract harmonics from a distorted online grid signal. The effectiveness of the proposed method was evaluated on the Speedgoat Rapid Control Prototype (RCP) platform. The results show that it can complete the convergence within 0.05 s, and the standard deviation after stability will not exceed 1%.

Simulation and rapid control prototyping of DC powered universal motors speed control: Towards an efficient operation in future DC homes

Universal motors are widely used in household appliances. When traditionally powered by AC, current harmonics are created which cause overheating of the windings and electromagnetic compatibility problems affecting the lifespan of the motor. Considering the remarkable comeback of DC power and its prospects in the electrification of homes, this paper proposes a control strategy for universal motors powered by DC using the rapid control prototyping feature offered by the dSPACE MicroAutoBox. A PI controller is designed using dominant-pole compensation method. The control strategy is simulated in Matlab/Simulink, then implemented in the MicroAutoBox via the Real-Time Interface. The simulation results are compared with those acquired by implementation through a laboratory test bench built around the MicroAutoBox and a dual full-bridge driver. The experimental results show that the designed PI controller managed to eliminate the static error and increased significantly the system dynamic performance by 26.5% in simulation and by 23.5% in practice. The robustness of the proposed control strategy against randomized load disturbances is proved by experimental tests. Furthermore, a significant improvement in power quality is reported.

Model-based robust control design and experimental validation of SCARA robot system with uncertainty

In this paper, we design a novel robust control method to reduce the trajectory tracking errors of the SCARA robot with uncertainties including parameters such as uncertainty of the mechanical system and external disturbance, which are time-varying and nonlinear. Then, we propose a deterministic form of the model-based robust control algorithm to deal with the uncertainties. The proposed control algorithm is composed of two parts according to the assumed upper limit of the system uncertainties: one is the traditional proportional-derivative control, and the other is the robust control based on the Lyapunov method, which has the characteristics of model-based and error-based. The stability of the proposed control algorithm is proved by the Lyapunov method theoretically, which shows the system can maintain uniformly bounded and uniformly ultimately bounded. The experimental platform includes the rapid controller prototyping cSPACE, which is designed to reduce programming time and to improve the efficiency of the practical operation. Moreover, we adopt different friction models to investigate the effect of friction on robot performance in robot joints. Finally, numerical simulation and experimental results indicate that the control algorithm proposed in this paper has desired control performance on the SCARA robot.

Rapid Control Prototyping by MBD for a Haptic Control Law of SBW

Rapid Control Prototyping by MBD for a Haptic Control Law of SBW

Model‐Based Design, HIL Testing, and Rapid Control Prototyping of a Low‐Cost POC Quadcopter with Stability Analysis and Control

Unmanned aerial vehicles (UAVs), particularly quadcopters, have several medical, agriculture, surveillance, and security applications. However, the use of this innovative technology for civilian applications is still very limited in low‐income countries due to the high cost, whereas low‐cost controllers available in the market are often tuned using the hit and trial approach and are limited for specific applications. This paper addresses this issue and presents a novel proof of concept (POC) low‐cost quadcopter UAV design approach using a systematic Model‐Based Design (MBD) method for mathematical modeling, simulation, real‐time testing, and prototyping. The quadcopter dynamic model is developed, and controllers are designed using Proportional Integral, and Derivative (PID), Pole Placement, and Linear Quadratic Regulator (LQR) control strategies. The stability of the controllers is also checked using Lyapunov stability analysis. For verification and validation (V&V) of the design, Software‐in‐the‐Loop, Processor‐in‐the‐Loop, Hardware‐in‐the‐loop testing, and Rapid Control Prototyping have been performed. The V&V methods of the MBD approach showed practically valid results with a stable flight of the quadcopter prototype. The proposed low‐cost POC quadcopter design approach can be easily modified to have enhanced features, and quadcopters with different design parameters can be assembled using this approach for a diverse range of applications.

Improved Synergetic Current Control for Grid-connected Microgrids and Distributed Generation Systems

This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system (DGS). This paper introduces new formulas of the macro-variable functions for integral synergetic control (SC) and integral fast terminal SC, which both have an integral term to guarantee zero steady-state error. The proposed integral SC and integral fast terminal SC achieve a seamless performance such as the fast convergence, minimal overshoot, zero steady-state error, and chattering-free operation. To demonstrate the meritorious performance of the proposed scheme for injected current control, it is compared with the performance of a proportional-integral (PI) controller and advanced exponential sliding mode control (SMC). Finally, the practicality of the proposed scheme is justified by experimental results obtained through rapid control prototyping (RCP) using the dSPACE-SCALEXIO platform.

A Unified Active Damping for Grid and Converter Current Feedback in Active Front End Converters

The Active Front End (AFE) is interconnected to the grid with an LCL filter to reduce the switching harmonics. Possible resonances induced by the LCL filter can be damped using Active Damping (AD). In AFE applications, the current sensor can be placed on either the grid-side or the converter-side, resulting in different frequency responses. This paper presents a novel active damping approach that is universally applicable to all active front end converters regardless of whether the current sensor is placed on the grid side or the converter side. At the heart of the proposed approach is a practically implementable fourth-order filter that dampens the resonance whilst being capable of mitigating the challenges associated with both grid current feedback and converter current feedback. These include amplifications associated with derivatives in active damping term with grid current feedback and high susceptibility to instability with converter current feedback due to digital delay. The proposed active damping is thoroughly investigated in terms of practical implementation issues such as different LCL filter parameters, different sampling methods, grid impedance, and digital delay. The approach is experimentally validated on motor drives consisting of 2 two-level three-phase converters interfaced with a dSPACE rapid control prototyping system across a wide range of resonant frequencies and PWM sampling methods. Stability analysis is performed on both current control methods to validate that active damping assures stable operation for a wide range of resonant frequencies and grid impedance.

Model-based on-board post-injection control development for marine diesel engine

Abstract The increasing demands for reducing fuel consumption and emissions in contemporary technology solutions lead to the use of more sensors, actuators, and control applications. With this increasing engine complexity, the feedback design is complex due to the coupling between inputs and combustion parameters. To be able to design the controller systematically, model predictive control (MPC) comes to the scope because of its advantages in the design of multi-input multi-output (MIMO) systems, especially with its constraints handling ability and performance in simultaneously optimizing the engine fuel efficiency and emission reduction. Multi-injection is one of the promising techniques for achieving better engine performance. In this work, post-injection control is implemented utilizing MPC MIMO strategy with the target of exploring the possibility of reducing emissions and improving engine efficiency by controlling post-injection duration and injection timing. The workflow of the MPC controller design from control-oriented model (COM) establishing to MPC problem formation and solution methodology is discussed in this work. Moreover, one contribution from this work is the different implementation angle when compared with the state-of-the-art approaches, where the MPC controller is implemented purely by Matlab Simulink to enable the rapid control prototyping design. The simulation result demonstrated the ability of the controller’s tracking performance and showed a preliminary step towards the nonlinear combustion model-based multi-injection MPC design. The systematic model-based controller framework developed in this work can be applied to other control applications and enables a fast path from design to test.

제어시스템 강좌의 온라인 수업 효율향상을 위한 교육환경 개발

In recent years, lectures on control systems have focused on hands-on experience using actual control equipment than before. However, the online education triggered compulsorily by the Covid-19 pandemic poses has restricted the construction of an education environment for hands-on experience. In this study, we proposed an economical and compact experimental environment for control education that enables hands-on experience even through online education. To this end, we utilized a light weight rapid control prototyping (LW-RCP), which is a lab-built RCP environment, and the environment was constructed using 3D printing. In the proposed environment, LW-RCP enabled students to focus on the learning and application of related control concepts, without the inconvenience of manual C-coding and the possibility of debugging errors. In addition, the proposed control equipment, which was manufactured using 3D printing, is an inexpensive equipment with a sufficiently small size that can be placed on a desk. Owing to the low cost and small size of the proposed environment, each student can have his/her own experimental equipment, which will enable a hands-on experience even through online education. Online education is expected to expand more and more in the future as it exhibits various advantages and potentials from traditional face-to-face classes. The proposed educational environment is expected to play a meaningful role in satisfying the demands of hands-on experience for control-related lectures.

Research on real-time control strategy of multi-power flow of dual-mode power-split hybrid electric vehicle

With the continuous development of hybrid vehicle control technology, great progress has been made in the research of multi-power flow collaborative control. Due to the internal delay link of each power component, the role of energy storage element, and the limitation of electric power in the whole system, the inevitable delay characteristic of state transfer is caused. Therefore, the speed of multi-power flow control torque coordinated response of hybrid vehicles needs to be improved. The dual-mode power-split hybrid electric vehicle (DMPS-HEV) overall structure and working modes are analyzed, by adopting the combination of theory and experiment method. In order to solve the problem that the power components of dual-mode power-split hybrid electric vehicle cannot follow the optimal control command of the upper energy management strategy quickly due to the engine response delay, thus affecting the control effect of the upper energy management strategy. The research on torque coordination control strategy is carried out, the reference model of electromechanical composite drive is established, and the model reference adaptive coordination control strategy based on Lyapunov stability theory is proposed. The results show that the proposed model reference adaptive torque coordinated control strategy significantly improves the effect of engine response delay on the optimization effect of energy management strategy, and can achieve the control effect of the optimal control strategy of 93.58%. The test platform of the dual-mode power-split hybrid electric vehicle was built. The control system was built based on the rapid control prototype, and the data acquisition system was built based on the NI data acquisition module. The coordinated control strategy of the dual-mode power-split hybrid electric vehicle power system proposed in this paper was verified through the bench test to significantly improve the vehicle fuel economy and the real-time performance of the control strategy, which has a good practical value