Control Loop Design Research Articles

AI/ML-based services and applications for 6G-connected and autonomous vehicles

AI and ML emerge as pivotal in overcoming the limitations of traditional network optimization techniques and conventional control loop designs, particularly in addressing the challenges of high mobility and dynamic vehicular communications inherent in the domain of connected and autonomous vehicles (CAVs). The survey explores the contributions of novel AI/ML techniques in the field of CAVs, also in the context of innovative deployment of multilevel cloud systems and edge computing as strategic solutions to meet the requirements of high traffic density and mobility in CAV networks. These technologies are instrumental in curbing latency and alleviating network congestion by facilitating proximal computing resources to CAVs, thereby enhancing operational efficiency also when AI-based applications require computationally-heavy tasks. A significant focus of this survey is the anticipated impact of 6G technology, which promises to revolutionize the mobility industry. 6G is envisaged to foster intelligent, cooperative, and sustainable mobility environments, heralding a new era in vehicular communication and network management. This survey comprehensively reviews the latest advancements and potential applications of AI/ML for CAVs, including sensory perception enhancement, real-time traffic management, and personalized navigation.

Characteristic Analysis and Control Loop Design of Transmission Torque and Jerk for Flexible Joint Servo Systems

Characteristic Analysis and Control Loop Design of Transmission Torque and Jerk for Flexible Joint Servo Systems

Development of bipolar high-current correction magnet power supply for TPS facility

Taiwan Photon Source (TPS) is a globally renowned 3 GeV synchrotron accelerator light source. With a successful decade of operation, various subsystems have continuously improved and maintained an optimal research facility environment. Presently, there is a concerted effort towards energy conservation. This technical report focuses on the future development of the TPS-II Permanent Magnet Trim Coil Power Supply for the correction magnet, emphasizing a Bipole high-current correction magnet power source. According to the prototype specifications, the maximum output current is 20 A with an operating voltage of 48 V. This augmentation increases the amplitude of the magnetic field correction in the permanent magnet-associated Trim core, providing greater flexibility in manufacturing the permanent magnet correction coils. To design a power supply with high current and stability, the system adopts the Danisense DP50-IP-B DC Current Transducers (DCCT) as the current feedback component and Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) as power switches in a full-bridge (H-bridge) configuration. The driving frequency is set at 40 kHz. Analog modulation control circuitry and protective circuits ensure precise control loop modulation. In the power laboratory, a hardware prototype circuit was constructed, featuring a 48 V input voltage, 20 A output current, a maximum power of 960W, and a current ripple component maintained within 100 μA. This experiment validates the control loop design of the prototype, showcasing the ability to achieve rapid and stable output current performance. Using a 1 V input reference signal for small-signal testing, the bandwidth displayed a -3 dB bandwidth of 8.51 kHz. Long-term current stability is within ± 10 ppm, and interface compatibility with the existing TPS correction magnet power source interface allows direct operation within the current system.

Optimizing the series cascade control structure for nonminimum phase system regulation

AbstractThis work elucidates the control of integrating a nonminimum phase system via a series cascade scheme with fractional‐order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional‐filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error. Two illustrative problems are utilized to examine the recommended control structure's virtue.

Innovative mechanisms for designing the regional public administration system

Subject. This article discusses the issues of managing complex systems and the feedback quality. Objectives. The article aims to develop a process model for the functioning of the regional public administration system. Methods. For the study, we used a systems analysis. Results. The article presents the design of a single control loop based on the model of a goal-oriented system and the model of an automatic control system and offers complete lists of elements for projects of a regional public administration system. Conclusions. Further development and implementation of the proposed project of the regional management system can help improve the effectiveness of targeted activities.

Outer loop control design of grid-forming converters for enhanced transient stability and current limiting capability

Outer loop control design of grid-forming converters for enhanced transient stability and current limiting capability

Development of linear power operational amplifier power supply with pre-regulated voltage controller for TPS correction magnets

The Taiwan Photon Source (TPS) is a renowned 3 GeV synchrotron accelerator light source. Over the past decade of successful operation, it has demonstrated outstanding performance, notably in average beam trip downtime, meeting international standards. A continuous regimen of scheduled equipment upgrades has been maintained across all subsystems to ensure ongoing improvement and the preservation of an optimal research facility environment. The central focus of this study revolves around the design and realization of a TPS correction magnet power supply employing Linear Power Operational Amplifiers (LPOA) in conjunction with a pre-regulated voltage controller. The power source predominantly features APEX Corporation's PA05 LPOA, characterized by bipolar output, high internal power dissipation, and wide bandwidth. Additionally, a DC Current Transducer (DCCT) was employed as the current feedback element, integrated with the pre-regulator voltage controller to form a closed-loop current modulation circuit, providing the variable voltage required by the LPOA. Through these measures, we have successfully developed an LPOA power supply unit equipped with a pre-regulated voltage controller for TPS correction magnets. The prototype device boasts a maximum output current of ±10 A, operating at 24 V. Validation through control loop design has led to rapid and stable output current performance. The output current ripple is maintained within 100 μA, with a rise time of 75 μs during step response. During frequency response testing utilizing a 0.1 V disturbance signal, the gain margin resides within -3 dB at an 11.2 kHz bandwidth and the phase margin within -45∘ at a 5.1 kHz range. Long-term output current stability is sustained within ten ppm. Finally, a hardware prototype circuit has been constructed in the power supply laboratory, featuring a ±24 V input voltage and ±10 A output current, achieving a maximum rated power of 240 W.

Droop-Based DC Microgrids Analysis and Control Design Using a Weighted Dynamic Aggregation Modeling Approach

In this paper, Weighted Dynamic Aggregation (WD agg) approach is used for modeling, analyzing and control loop design of islanded DC microgrids. The proposed approach models <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><inline-formula><tex-math notation="LaTeX">$ \textbf {n}$</tex-math></inline-formula></i> DC-DC converters and their controllers with a single equivalent converter and an equivalent control system, which without sacrificing the accuracy, reduces the complexity of such large-scale system studies. It is shown that the model equivalent converter and control system parameters can be determined by the weighted average of the corresponding parameters of the large-scale system. The weight of each converter is quantified based on the contribution of that converter in the overall dynamic behavior of the large-scale system. WD agg model can accurately predict the transient response and can be employed in power planning, stability and sensitivity analyses with high accuracy. It is also shown that the proposed model can be used in designing the controller parameters of the large-scale system to ensure desirable system performance. The accuracy and applications of the proposed WD agg model are evaluated through time-domain simulations, and experiments of an islanded microgrid consisting of three paralleled converters with different control parameters connected to a Constant Power Load (CPL) emulating a challenging system stability case.

Neural Network-Based Hybrid Three-Dimensional Position Control for a Flapping Wing Aerial Vehicle.

This article presents a novel neural network-based hybrid mode-switching control strategy, which successfully stabilizes the flapping wing aerial vehicle (FWAV) to the desired 3-D position. First, a novel description for the dynamics, resolved in the proposed vertical frame, is proposed to facilitate further position loop controller design. Then, a radial base function neural network (RBFNN)-based adaptive control strategy is proposed, which employs a switching strategy to keep the system away from dangerous flight conditions and achieve efficient flight. The learning process of the neural network pauses, resumes, or alternates its update strategy when switching between different modes. Moreover, saturation functions and barrier Lyapunov functions (BLFs) are introduced to constrain the lateral velocity within proper ranges. The closed-loop system is theoretically guaranteed to be semiglobally uniformly ultimately bounded with arbitrarily small bound, based on Lyapunov techniques and hybrid system analysis. Finally, experimental results demonstrate the excellent reliability and efficiency of the proposed controller. Compared to existing works, the innovations are the put forward of the vertical frame and the cooperative switching learning and control strategies.

Data-driven discovery of sparse dynamical model of cardiovascular system for model predictive control

Cardiovascular diseases remain the leading cause of death globally. In recent years, vagal nerve stimulation (VNS) has shown promising results in the treatment of a number of cardiovascular diseases. In this approach, mild electrical pulses are sent to the brain via the vagus nerve. This open-loop neurostimulation, however, leads to various side effects due to physiological and inter-patient variability and therefore a closed-loop delivery strategy of electrical pulses that accounts for this variability is desired. In this context, we envision data-driven sparse dynamical model parameterized by patient-specific data as appropriate for use in closed loop controller design. In this work, we build a dynamical model for mean arterial pressure and heart rate using the method sparse identification of nonlinear dynamics (SINDy). As a proxy for real datasets or measurements from a patient, we simulate a mechanistic model from the literature and then discover a data-driven model for predicting mean arterial pressure and heart rate in response to neural stimulus. This discovered model is then used to design a controller to be implemented in closed-loop via model predictive control. We observe that this data-driven model is interpretable, consistent with experiments, provides insights on the sensitivity of different stimulation locations and simplifies the formulation of the optimal control problem. Noting the set-point tracking performance of this closed-loop model-based controller that uses this discovered model, we conclude that the model is adequate in capturing the dynamics of a highly nonlinear cardiovascular system for the purpose of optimal predictive controller design.

Development of DSP-based TPS fully digital correction magnet power supply

The Taiwan Photon Source (TPS) is a third-generation 3 GeV synchrotron accelerator light source. After successfully operating for ten years since its first light in 2013, various subsystems are undergoing updates. In the context of magnet power supply upgrades, the trend toward digitization and high-precision modulation control is driving advancements worldwide. This study focuses on developing a fully digital correction magnet power supply (FDCMPS) based on a digital signal processor (DSP). The prototype utilizes a low-power, floating-point DSP with multiple communication functionalities as the core control unit. The output current is converted into digital values using current sensors and high-precision analog-to-digital converters. Discrete PI compensator algorithms are implemented within the DSP to generate pulse-width modulation (PWM) waveforms, driving a full-bridge (H-bridge) converter configuration with metal-oxide-semiconductor field-effect transistors (MOSFET). This forms a complete, fully digital closed-loop current control system. A virtual control interface is designed to operate the FDCMPS state. The control loop design of the prototype has been validated and demonstrates stable output bipolar current performance. When tested with a 0.1 V input reference signal, the prototype achieves a -3 dB bandwidth of 2.03 kHz. Finally, a hardware prototype circuit was constructed in the power supply laboratory, with an input voltage of 48 V, an output current of 10 A, and a maximum power of 400 W. Overall, the developed fully digital correction magnet power supply prototype showcases stable and high-performance output bipolar current performance. The system achieves total harmonic distortion of output current ripple within 0.3 mA peak to peak and long-term stability within ± 15 ppm. The successful implementation of the prototype establishes a solid foundation for advancing magnet power supply technology at the TPS.

Small Signal Stability of Phase Locked Loop Based Current-Controlled Inverter in 100% Inverter-Based System

Present-day inverter control mainly employs phase locked loop (PLL) based current-controlled strategies. With growing penetration of inverter-based resources in power systems, stability issues associated with inverter control have been reported in weak grid scenarios. A natural and fundamental question to answer is whether this instability is inherent to PLL based current-controlled strategies or it can be resolved with proper frequency and voltage control loop design. This paper addresses this question by analyzing the small signal stability of the current-controlled inverter in island and weak grid operation scenarios. Torque analysis, which is well known for synchronous machine stability analysis, is adapted to uncover the stability enhancement effect of properly designed and parameterized outer-loop controls. Different types of loads are considered and investigated in the study. Electromagnetic transient (EMT) simulations are conducted on a test network to validate the analytical results. The results from this study indicate that with appropriate outer-loop voltage and frequency control design, the PLL based current-controlled inverter can be small signal stable with high inverter penetration, even in a 100% inverter-based system.

Design and implementation of a temperature-compensated corrector magnet power supply for the Taiwan Photon Source

The Taiwan Photon Source (TPS) is a widely recognised 3 GeV synchrotron light source. It has demonstrated exceptional performance in average beam downtime and meeting international standards over its successful ten-year operation. Regular equipment updates are conducted for all subsystems to ensure continuous improvement and maintain an optimal research facility environment. This study focuses on designing and implementing a temperature-compensated corrector magnet power supply for the TPS. The power supply incorporates a high-bandwidth, compact, cost-effective, bipolar, and highly precise shunt resistor as the current feedback component. A temperature control copper box and temperature compensation circuit are employed to improve the thermal equilibrium time of the output current. A laboratory-developed TPS-corrected magnet power supply with temperature compensation control has been successfully developed through these measures. The prototype exhibits a maximum output current of 10 A and operates at a voltage of 40 V. Metal-oxide-semiconductor field-effect transistors (MOSFETs) are utilised as the power switch in a full-bridge (H-bridge) configuration with a driving frequency of 40 kHz. The output current ripple is effectively maintained at 100 μA for a 10 A output, and the stabilisation time is achieved within 5 minutes. The control loop design of the prototype has been verified to achieve fast and stable output current performance. The completed prototype demonstrated a -3 dB bandwidth of 2.57 kHz when tested with an input reference signal of 0.1 V. Finally, a hardware prototype circuit was constructed in the power supply laboratory, featuring an input voltage of 48 V, an output current of 10 A, and a maximum power capacity of 400 W.

Comparative Stability Analysis of Synchronous Reference Frame Current Controllers Operated at High Fundamental Frequency

Synchronous reference frame (SRF) proportional-integral (PI) current controller (CC) is the most well-established solution for current regulation in AC machine drives and grid-connected voltage source converters. The design of high dynamic performance current control loop has several challenges in high-speed and high-power applications due to the effects of controller gain’s selection, non-linearities, parameters variations, disturbances, digital implementation, and time delays. These become more significant due to high operating frequencies, which severely degrade dynamics and stability of the current control system. Various structures of SRF PI CCs have been reported in the literature. However, the aforementioned effects on the dynamics at high frequency operation have not been thoroughly addressed. Therefore, a comparative analysis of different SRF PI CCs’ structures is proposed in this paper, which addresses the design principles and gains’ selection while also taking into account the heavy computational burden and PWM delays. Additionally, the paper thoroughly analyzes and evaluates the dynamics and stability of the system operating at high fundamental frequencies. The advantages and limitations of each SRF PI CC scheme are studied and reported. The performance of the SRF PI CCs is comprehensively tested to demonstrate the analytical outcome of this study.

A novel step-up/step-down DC-DC converter based on flyback and SEPIC topologies with improved voltage gain

A novel step-up/step-down DC-DC converter with improved voltage gain characteristics is suggested in this paper. The proposed converter combines flyback and single-ended primary inductance converter (SEPIC) converters. The voltage control loop design is simplified due to the use of only a single controlled switch. It has been discussed how switch duty cycle affects voltage gain. This relationship demonstrates that the proposed converter voltage gain is improved compared with flyback and SEPIC converters. However, compared to flyback and SEPIC converters, it has a higher voltage gain at any given duty cycle. The proposed converter operation is thoroughly discussed, the associated equations are derived, and its parameters are expertly designed. Moreover, it is designed to supply a DC load of 2.5 kW, 500 V, and 5 A. The proposed converter efficiency exceeds 84% under rated load conditions. Additionally, it is also presented as an adapter for electric vehicles. The waveforms associated with the simulation of the converter across the universal line voltage of 110-260 Vrms are shown. At both line voltages, the total harmonics distortions (THDs) of the line current are 17.12% and 27.26%, respectively. MATLAB/Simulink is utilized for validation in order to validate the topology for different applications.

Automated control loop selection via multistage optimal control formulation and nonlinear programming

In this work, a novel approach based on the multistage optimal control formulation of the control loop selection problem is introduced. Currently, state-of-the-art approaches for controller loop design have been focused on data that yield only the pairings between input-output variables, and are not able to incorporate path and end-point constraints. Thus, they only produce the optimal loops for control purposes, without the simultaneous consideration of their optimal tuning. This formulation overcomes these drawbacks by producing an automated integrated solution for the task of control loop design, which also obviates the need for any form of combinatorial optimisastion to be used. To illustrate the procedure, as well as the advantages of the proposed scheme, different practical case studies are discussed and the results compared with those obtained with standard controller loop selection methods and their tuning. The results of the proposed approach show improved performance over previous methodologies found in the literature. Furthermore, the framework is extended to the selection of the control loops that must obey path and end-point constraints imposed by the underlying dynamical process. This task is usually difficult for classical methods, which violate them or exhibit underdamped response in some cases.

DO-Based Adaptive Consensus Control for Multiple MUAVs With Dynamic Constraints

This article investigates the adaptive consensus control problem for a group of multirotor unmanned aerial vehicles (MUAVs) subject to dynamic state constraints and unmatched external disturbances. An adaptive inner–outer loop controller is devised based on the backstepping method, where the issue of “explosion of complexity” is solved via a first-order sliding-mode differentiator. By introducing a barrier function-based state transformation technique into the outer loop controller design, the dynamic constraints covering different types of time-varying state constraints can be addressed without reconfiguring the controller structure. Meanwhile, a neural-network-based disturbance observer is constructed to estimate the external disturbances. Consequently, the applicability and robustness of controller are improved, such that the position tracking control can be implemented in severe environments. Moreover, the inner loop controller is established by virtue of a distributed sliding-mode estimator so as the consensus control for attitude systems of multiple MUAVs can be realized rapidly. Finally, a simulation example is presented to demonstrate the validity and superiority of the proposed control strategy.

An active damping control strategy with improved transient performance for high‐frequency AC power distribution in intelligent vehicles

SummaryHigh‐frequency AC (HFAC) LCLC resonant inverter has recently received more and more attention in power distribution system (PDS) of intelligent vehicles. However, LCLC resonance complicates the design of a current control loop and can even threaten the stability and transient performance of PDS. Active damping (AD) strategies based on the feedback of a single filter voltage or current have been shown to be effective and cost‐efficient method for attenuating resonant spikes. In this paper, a notch filter‐based AD (NFAD) control strategy is proposed to improve the stability and transient performance of PDS for intelligent vehicles. By sensing and feeding back the output resonance current of LCLC resonant inverter, the NFAD control strategy is then formulated to emulate a virtual impedance in order to improve the system phase margin and crossover frequency. Hence, the proposed control strategy can not only suppress the LCLC double resonance peaks but also effectively improve the transient performance of resonant inverter while guaranteeing the stability of the system. Finally, an experimental prototype was established and tested to verify the effectiveness of the proposed control strategy with a rated output power of 130 W, an operation frequency of 25 kHz, and a sinusoidal output voltage of 28 V (rms).

Artificial intelligence support for 5G/6G-enabled Internet of Vehicles networks: An overview

Improving transportation efficiency and on-road safety using Intelligent Transportation Systems (ITSs) has become crucial as road congestion and vehicle complexity increase coupled with ongoing rapid development and deployment of electric vehicles across the globe. Recent advances in computer systems and wireless communications have ushered in more possibilities for smart solutions to road traffic safety, congestion reduction, convenience, and overall efficiency. The evolution and deployment of 5G have opened up new technologies and features that can provide the much needed high-mobility wireless networks for the emerging Internet of Vehicles (IoV). The application of AI consisting of Deep Learning (DL), Machine Learning (ML) and Swarm Intelligence (SI) techniques have emerged in both conventional and vehicular wireless networks with strong promises towards enhancing traditional data-centric methods. Particularly, in the application domains of IoV, big data is frequently generated from various sources within the vehicular communication environment. The collected big data is usually processed and used for both safety and infotainment services including routing, broadening drivers' awareness, traffic mobility prediction for hazardous situation avoidance to improve overall safety and passenger comfort, and general quality of road experience. Applying data-driven methods enables AI to address high mobility and dynamic vehicular communications and network issues facing traditional solutions and approaches like network optimization techniques and conventional control loop design. This study provides a concise review of DL, ML and SI techniques and applications that are currently being explored by different research efforts within the application area of vehicular networks. The paper further discusses the strengths and weaknesses of the proposed AI-based solutions for the IoV networks.

Optimal design and control loop selection for a STATCOM wide-area damping controller considering communication time delays

Wide-area damping controllers (WADC) have been shown to be effective in damping interarea oscillation modes. The varying nature of power system operating point requires the design of an adaptive WADC. Majority of the existing control design techniques rely on empirical approaches at one or more of their design stages, which makes it difficult to implement in adaptive control techniques. Therefore, the purpose of this study is to provide a systematic procedure based entirely on numerical approaches for designing a STATCOM-based WADC. The proposed procedure involving control loop selection, control design and adaptive time delay compensation, can then be implemented in adaptive WADC schemes. Geometric analysis has been used to choose the STATCOM location. Then, a novel optimization-based signal selection methodology is proposed. The proposed methodology employs a combination of multiple input signals to optimally generate a signal with the required modal objectives like enhancing observability and reducing interaction between different control loops. After that, another optimization problem is formulated to tune the controller parameters using integral of time multiplied by absolute error (ITAE) as the optimization objective. Both optimization problems have been evaluated using two optimization techniques: Particle swarm optimization (PSO) and self-adaptive multi-population elitist Jaya algorithm (SAMPE-JAYA). Finally, an adaptive delay compensator is designed to mitigate the effects of communication time delays. The proposed control strategy is applied on the IEEE 68-bus system and the controller performance is evaluated by modal analysis and multiple time-domain simulation scenarios.