Control Loop Research Articles

Multi-channel decentralized decoupling FxLMS algorithm and active vibration control experiment

When vibrations generated by marine machinery propagate through a ship’s hull into the ocean, they produce low-frequency radiated noise with distinct “acoustic fingerprint” characteristics. This noise, characterized by stable and concentrated energy, long transmission distances, and difficulty in elimination, becomes the primary target for enemy sonar detection. Active vibration isolation serves as a critical method for reducing low-frequency vibrations in ships and enhancing their acoustic stealth performance. However, control challenges persist, including multi-frequency excitation, frequency fluctuation, multi-channel coupling, and slow convergence speed. To address these issues, this paper introduced an innovative multi-channel decentralized decoupling filtered-x least mean square (DMFxLMS) algorithm. Firstly, a recursive least squares identification algorithm with a forgetting factor was proposed, taking into account the characteristics of single-input, multi-output and multi-input, and multi-output control systems, effectively enhancing the algorithm’s convergence speed and control accuracy. Secondly, based on the decentralized decoupling control concept, the multi-channel control system was simplified into parallel single-channel control loops. The control weight coefficient updates were only related to adjacent error signals, significantly reducing the algorithm’s computational complexity. Thirdly, an anti-impact link was designed to improve the algorithm’s robustness, considering the interference caused by other mechanical equipment during the control process. The influence of abnormal error signals in the control weight coefficient correction term was suppressed, and a percentage function was introduced to limit the output signal. Finally, the feasibility and effectiveness of the DMFxLMS algorithm were verified through simulations and experiments. The results demonstrated that the DMFxLMS algorithm achieved significant control effects for both constant frequency line spectrum excitation and frequency fluctuating line spectrum excitation, fulfilling the objective of reducing base vibration. The DMFxLMS algorithm exhibited fast convergence and excellent robustness, making it suitable for practical engineering applications.

Thermal defocus-free Hartmann Wavefront Sensors for monitoring aberrations in Advanced Virgo

Earth-based gravitational waves interferometric detectors are shot-noise limited in the high-frequency region of their sensitivity band. While enhancing the laser input power is the natural solution to improve on the shot noise limit, higher power also increases the optical aberration budget due to the laser absorption in the highly reflective coatings of mirrors, resulting in a drop of the sensitivity of the detector. Advanced Virgo exploits Hartmann Wavefront Sensors (HWSs) to locally measure the absorption-induced optical aberrations by monitoring the optical path length change in the core optics. Despite the very high sensitivity of Hartmann sensors, temperature fluctuations can cause a spurious curvature term to appear in the reconstructed wavefront due to the thermal expansion of the Hartmann plate, that could affect the accuracy of the aberration monitoring. We present the implementation and validation of a control loop to stabilize the Advanced Virgo HWS temperature at the order of ΔT⩽0.01 K, keeping the spurious curvature within the detector’s requirements on wavefront sensing accuracy.

A Hybrid Semi-Automated Workflow for Systematic and Literature Review Processes with Large Language Model Analysis

Systematic reviews (SRs) are a rigorous method for synthesizing empirical evidence to answer specific research questions. However, they are labor-intensive because of their collaborative nature, strict protocols, and typically large number of documents. Large language models (LLMs) and their applications such as gpt-4/ChatGPT have the potential to reduce the human workload of the SR process while maintaining accuracy. We propose a new hybrid methodology that combines the strengths of LLMs and humans using the ability of LLMs to summarize large bodies of text autonomously and extract key information. This is then used by a researcher to make inclusion/exclusion decisions quickly. This process replaces the typical manually performed title/abstract screening, full-text screening, and data extraction steps in an SR while keeping a human in the loop for quality control. We developed a semi-automated LLM-assisted (Gemini-Pro) workflow with a novel innovative prompt development strategy. This involves extracting three categories of information including identifier, verifier, and data field (IVD) from the formatted documents. We present a case study where our hybrid approach reduced errors compared with a human-only SR. The hybrid workflow improved the accuracy of the case study by identifying 6/390 (1.53%) articles that were misclassified by the human-only process. It also matched the human-only decisions completely regarding the rest of the 384 articles. Given the rapid advances in LLM technology, these results will undoubtedly improve over time.

Review on Close Loop Control of Novel Transformer Less Inverter Topology for Single Phase Grid Converter

The continuous urge for improvement in our standard of living has increased the consumption of electrical energy by leaps and bounds. This hike in energy consumption, draining of fossil fuels and degrading global environment has led to invention of green power generation systems. Thus, the global demand for renewable resources has led to flourishing of photovoltaic (PV) market. The enabling technology in the PV systems is the inverter, which could be either: 1) with transformer isolated or 2) without transformer non-isolated (transformer-less inverter). Recently, single phase transformerless voltage source inverters (VSI) have been extensively used for distributed photovoltaic grid tied systems. The objective of this paper is to review a few notable topologies and propose a new topology for transformer-less photovoltaic inverter. The analysis and design of the proposed topology is verified by simulating it on PSIM. Furthermore, the simulation results are validated by testing a proof-of-concept laboratory hardware prototype rated at 250 W. Keywords— Photovoltaic (PV) systems, transformer-less, single phase inverter

A Novel Second Harmonic Voltage Suppression Control for PSFB Converter in Dual-Stage Single-Phase Rectifier

The inherent second harmonic power pulse in single-phase grid-connected rectifiers leads to a noticeable output voltage ripple and thus results in the degradation of the system. A novel second harmonic suppression control is introduced in this paper to address this issue. The key point of the proposed control lies in the real-time prediction of the phase-shifted full-bridge (PSFB) converter’s desired duty cycle through accurate PSFB converter modeling. By accurately predicting the ideal duty cycle, the proposed control facilitates a significant enhancement in the control loop’s gain specifically at the second harmonic frequency, thereby improving the overall system performance. To validate the theoretical analysis, a series of simulations and experiments were conducted. The results demonstrate the effectiveness of the proposed second harmonic suppression control in mitigating second harmonic output voltage ripple.

Discrete-Time Adaptive Control for Three-Phase PWM Rectifier

This paper proposes a dual-loop discrete-time adaptive control (DDAC) method for three-phase PWM rectifiers, which considers inductance-parameter-mismatched and DC load disturbances. A discrete-time model of the three-phase PWM rectifier is established using the forward Euler discretization method, and a dual-loop discrete-time feedback linearization control (DDFLC) is given. Based on the DDFLC, the DDAC is designed. Firstly, an adaptive inductance disturbance observer (AIDO) based on the gradient descent method is proposed in the current control loop. The AIDO is used to estimate lump disturbances caused by mismatched inductance parameters and then compensate for these disturbances in the current controller, ensuring its strong robustness to inductance parameters. Secondly, a load parameter adaptive law (LPAL) based on the discrete-time Lyapunov theory is proposed for the voltage control loop. The LPAL estimates the DC load parameter in real time and subsequently adjusts it in the voltage controller, achieving DC load adaptability. Finally, simulation and experimental results show that the DDAC exhibits better steady and dynamic performances, less current harmonic content than the DDFLC and the dual-loop discrete-time PI control (DDPIC), and a stronger robustness to inductance parameters and DC load disturbances.

Rectification and converter control of the FPSLGs for energy storage applications

AbstractThis article presents two power converters with controllers attached to the Free‐Piston Stirling Linear Generator (FPSLG) and energy storage system (ESS). The rectifier uses hysteresis‐SVPWM current regulation and CB‐SPWM, while the buck‐boost converter utilizes the dual‐loop PI control method. The storage battery receives energy from a linear‐generator with a rectifier and converter. The FPSE and linear motors in the FPSLG convert thermal to electrical energy. A two‐level electrical energy conversion technique using a three‐phase AC signal to DC and DC‐DC converter has been devised to reduce output electrical energy oscillation as well as stabilize the generating system's DC power. Initially, the FPSE's nonlinear model and the three‐phase permanent magnet linear‐motor's linear mathematical model were created and followed by the ESS and control mechanism simulation. The simulation shows that the ESS system and control approach can give stable power to the storage battery using linear‐generator power. The PR controller replaces the PI controller in the position loop to improve frequency and displacement tracing. The control system design was simulated in MATLAB and the topology's feasibility and correctness were confirmed. Comparative analysis shows that, rectifier uses the H‐SVPWM's unity power factor of AC and stability controllability of the DC‐side voltage is better than the CB‐SPWM approach.

Analysis, Simulation, and Experiments of Dynamics and Control of a Hydrostatic Wind Turbine Under Partial Load

Abstract Kω2 control, also called torque control, is a popular method for maximizing wind turbine power. For hydrostatic wind turbines, torque control becomes pressure control with pc=K'ω2 because pressure is proportional to torque. Inverse Kω2 control is an alternative approach using rotor speed control with pc=(p/K')1/2. This work analyzes the dynamics of hydrostatic wind turbines using forward and inverse Kω2 control with P-, PD-, PI-, and PID-control for feedback. Dimensionless, linearized models are used. Analysis shows that the mechanical rotor dynamics are much slower than the hydrostatic transmission dynamics and that frictional and leakage losses are negligible. Linear perturbation of the nonlinear model reveals that the closed-loop control is not in Evan's form, so that closed-loop poles and zeros both vary with the loop gain. Pole and zero root locus analysis shows how systems responses change with controller gains. Both control approaches require derivative controller action to sufficiently dampen their responses; both are also fundamentally limited in speed of response by a slow stable pole regardless of controller loop gains. Nonlinear system simulation shows that both control approaches track the maximum power point with nearly identical transient behavior and have nearly identical power losses when using suboptimal values of the control law gain, K. Pressure control has a gain margin of infinity and a phase margin of 99.3 degrees, while speed control has a gain margin of 22.4 dB and a phase margin of 73.8 degrees showing that pressure control is more robust than speed control. Experiments using the power regenerative hydrostatic test stand at the University of Minnesota show that the control approaches have different transient responses but capture comparable power under steady and turbulent conditions.

Guiding Lunar Landers: Harnessing Neural Networks for Dynamic Flight Control with Adaptive Inertia and Mass Characteristics

The autonomous control of landing procedures can provide the efficiency and precision that are vital for the successful, safe completion of space operations missions. Controlling a lander with this precision is challenging because the propellants, which will be expended during the operations, represent a significant fraction of the lander’s mass. The mass variation of each tank profoundly influences the inertia and mass characteristics as thrust is generated and complicates the precise control of the lander state. This factor is a crucial consideration in our research and methodology. The dynamics model for our lander was developed where the mass, inertia, and center of mass (COM) vary with time. A feed-forward neural network (NN) is incorporated into the dynamics to capture the time-varying inertia tensor and COM. Moreover, the propellant takes time to travel through the feed lines from the storage tanks to the engine; also, the solenoid valves require time to open and close. Therefore, there are time delays between the actuator and the engine response. To take into account these sources of variations, a combined time delay is also included in the control loop to evaluate the effect of delays by fluid and mechanisms on the performance of the controller. The time delay is estimated numerically by a Computational Fluid Dynamics (CFD) model. As part of the lander’s control mechanism, a thrust vector control (TVC) with two rotational gimbals and a reaction control system (RCS) are incorporated into the dynamics. Simple proportional, integral, and derivative (PID) controllers are designed to control the thrust, the gimbal angles of the TVC, and the torque required by the RCS to manipulate the lander’s rotation and altitude. A complex mission with several numerical examples is presented to verify the hover and rotational motion control.

Enhancing Industrial Process Control: Integrating Intelligent Digital Twin Technology with Proportional-Integral-Derivative Regulators

This paper explores the integration of intelligent digital twin technology with PID regulators in industrial process control utilizing smart meter data. It presents a novel approach involving the creation of mathematical models to simulate real-time system behavior, thereby enhancing the PID control loop. The focus is on the development of specialized IT infrastructure to support this integration, which includes data acquisition, processing, and control optimization. This integration aims to not only improve control system efficiency but also introduce a robust predictive maintenance framework, offering significant benefits across a wide range of industrial applications.

Smart Home Powered by Solar: IoT-based SEPIC Converter Control

Background: In this article, an IOT solution for managing and controlling a PV system with applications for the home is presented. A DC-DC SEPIC converter, a bidirectional converter, a PWM generator, and a single-phase voltage source inverter with active clamping are used for power conditioning. An output voltage control loop is implemented, and real-time online communication with an internet server is accomplished using the PIC microcontroller. Methods: The ESP8266MOD WIFI IOT module works with the Blynk mobile app. Experimental findings showing the proper operation of IOT features demonstrate the effectiveness of voltage regulation. In this article, frequency is taken into consideration as solar power is integrated with the grid. A user may easily control the DC-DC converter, load batteries, and monitor battery voltage through our userfriendly GUI interface. Results: In this paper, an IOT (Internet of Things) application was used to control and track the output of a modest PV power plant. The study shows the efficiency of the digitally controlled system developed to regulate the output voltage of the SEPIC DC-DC converter. Practical Significance: They further argue that the ESP8266 and microcontroller's versatility make them an appropriate instrument for remote and real-time monitoring and control of the proposed model from around the world. The energy that is produced by the sun is added to the grid so that it may be put to effective use and contribute to satisfying the rising demand for energy. Solar energy is the input that SEPIC uses to charge the batteries and for all of its other processes. In the event that solar photovoltaic (PV) panels are not available, the SEPIC DC-DC converter will derive its energy from AC power. Conclusion: In this article, an IOT (Internet of Things) application was used to control and track the output of a modest PV power plant. The research demonstrates the effectiveness of the digitally controlled system created to manage the output voltage of the SEPIC DC-DC converter. They further argue that the ESP8266 and microcontroller's versatility make them an appropriate instrument for allowing remote and real-time monitoring and control of the proposed model from any part of the world. The energy that is produced by the sun is added to the grid so that it may be put to effective use and contribute to satisfying the rising demand for energy. Solar energy is the input that SEPIC uses to charge the batteries and for all of its other processes. In the event that solar photovoltaic (PV) panels are not available, the SEPIC DC-DC converter will derive its energy from AC power.

Improved extended empirical wavelet transform for accurate multivariate oscillation detection and characterisation in plant-wide industrial control loops

The conventional extended empirical wavelet transform (EEWT) proposed recently is intended to decompose multivariate signals with clear peaks in power spectra without considering the cases where the signals contain high noise levels. Even when dealing with signals with distinct peaks, the EEWT method can still encounter challenges in properly decomposing the signals. However, plant-wide data from industrial control loops, including controllers’ outputs, process variables, and manipulated variables, are commonly corrupted by high levels of noise, which can be introduced at various stages of data acquisition, transmission, and processing within the control system. To address these limitations and ensure the applicability of the EEWT to real-world industrial data with diverse and challenging characteristics, this paper presents an improved version called the improved extended empirical wavelet transform (IEEWT). The IEEWT incorporates noise-reduced power spectra and detrended fluctuation analysis techniques to enhance the decomposition. The proposed method demonstrates accurate multivariate data decomposition for both simulated and real data sets, surpassing the limitations associated with the conventional EEWT.

Learning and Balancing Unknown Loads in Large-Scale Systems

Consider a system of identical server pools where tasks with exponentially distributed service times arrive as a time-inhomogeneous Poisson process. An admission threshold is used in an inner control loop to assign incoming tasks to server pools, while in an outer control loop, a learning scheme adjusts this threshold over time to keep it aligned with the unknown offered load of the system. In a many-server regime, we prove that the learning scheme reaches an equilibrium along intervals of time when the normalized offered load per server pool is suitably bounded and that this results in a balanced distribution of the load. Furthermore, we establish a similar result when tasks with Coxian distributed service times arrive at a constant rate and the threshold is adjusted using only the total number of tasks in the system. The novel proof technique developed in this paper, which differs from a traditional fluid limit analysis, allows us to handle rapid variations of the first learning scheme, triggered by excursions of the occupancy process that have vanishing size. Moreover, our approach allows us to characterize the asymptotic behavior of the system with Coxian distributed service times without relying on a fluid limit of a detailed state descriptor. Funding: The work in this paper was supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Gravitation Grant NETWORKS-024.002.003 and Vici Grant 202.068].

Autonomic end-to-end quality-of-service assurance over QKD-secured optical networks

Quantum key distribution (QKD) provides future-proof security for data communications over optical networks. Currently, sophisticated QKD systems are developed and the scale of QKD-secured optical networks (QKD-ONs) becomes larger. Given the complex network conditions and dynamic end-to-end security services in QKD-ONs, autonomic management and control becomes a promising paradigm to support end-to-end quality-of-service (QoS) assurance in an efficient and stable way without requiring human intervention. Hence, to enable and utilize the autonomic functionalities over QKD-ONs for realizing the end-to-end QoS assurance becomes a challenge. This work enhances the software defined networking (SDN) technique to tackle this challenge because SDN can add programmability and flexibility for QKD-ON’s management and control. A new architecture of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance is designed, where a knowledge engine with autonomic control loops is developed in the SDN controller. We present the autonomic end-to-end QoS assurance procedure, and the cross-layer collaborative QoS assurance (CLC-QA) strategy for implementing the autonomic functionalities in the network level over QKD-ONs. We also establish an experimental testbed of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance, and perform the numerical simulation to verify our proposed approaches. Experimental results demonstrate that our presented approaches can achieve the millisecond-level overall latency of 337 ms and 618 ms, during the first and second autonomic adjustment without human intervention in case of the autonomic QoS protection. Moreover, the CLC-QA strategy is evaluated under different traffic loads by being compared with the baseline strategy without cross-layer collaboration. It can improve 22.5% protection success ratio and save 5.7% average key consumption.

Soft Monolithic Shielded Sensors to Measure Shear and Normal Forces for Local Slip Detection

AbstractSoft force sensors enable closed loop control or autonomous operation of compliant robot systems. A stretchable force sensing surface containing an array of independent sensor units is reported. This design allows for the measurement of local shear and normal forces at multiple locations, independently, providing real‐time, multi‐axis force information at each unit. The sensor array is based on capacitive strain sensing, using liquid metal electrodes and air microchannel for high sensitivity. Electromechanical interference between adjacent sensor units is addressed and eliminated through design optimization and the use of compliant electrical shield layers. A 1D sensor array is applied to gripping tasks, where the independent sensor readings enable detecting local and partial slipping. This study illustrates how the device can be used to explore the dynamics of local forces during the stages of pick up, slip, and release.

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Purpose To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems. Design/methodology/approach The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs. Findings In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis. Research limitations/implications Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task. Practical implications The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots. Social implications The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent. Originality/value A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

Cascade control algorithm for slip rate in a brake-by-wire system based on direct drive valve

To achieve a rapid response and precise control of braking hydraulic pressure, a brake-by-wire electro-hydraulic braking system based on a direct drive valve was designed. This system employs an electromagnetic linear actuator to drive the valve core directly, achieving swift adjustment of brake wheel cylinder hydraulic pressure. Given the strong coupling and non-linearity of the electromagnetic linear actuator, solely using a single-loop controller to control the slip rate can easily lead to weakened system performance. Hence, we proposed a cascade control algorithm for the brake-by-wire system, with an outer loop for slip rate control and an inner loop for direct drive valve position. The outer loop adopted a fuzzy PID control, while the inner loop adopted a model-free adaptive sliding mode control. By combining model-free adaptive control with a novel discrete exponential approach, we addressed the system’s non-linearity and unknown disturbances. A braking system test platform was constructed to verify the superior hydraulic tracking performance of this brake-by-wire system and to perform slip rate control performance analysis under different road conditions. Results demonstrated that compared to the fuzzy PID-MFAC algorithm, the proposed fuzzy PID-MFASMC control enhanced car slip rate control precision, and reduced both braking time and distance.

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.

Performance evaluation of multi-stage manufacturing systems operating under feedback and feedforward quality control loops

In manufacturing, the essential product characteristics are often created through multiple stages. Coupling product data obtained through inspection and controllers based on decision models with prediction capabilities enables quality control loops, enhancing both feedback and feedforward mechanisms. This paper proposes a methodology to merge the formulation of feedback and feedforward quality control loops into a performance evaluation model for multi-stage manufacturing systems. This approach evaluates quality control loop impacts system-wide, aiding in configuring and reconfiguring quality gates. A case study illustrates how allocating inspection technologies and efficient decision models improves overall system performance through effective feedback and feedforward control loops.

Low/Middle-Frequency Positive External- Damping Design Under Self-Stability Constraint for Inner Control Loop of Grid-Forming Converters

The inner voltage control loop and inductor current active damping loop of grid-forming (GFM) converters perform the output voltage control and filter resonance damping, and their stability design has been widely developed in the literature. However, the equivalent external-damping characteristics have not been fully explored. In this paper, the analysis shows that inappropriate design focusing only on self-stability would lead to negative external-damping in a wide low/middle-frequency band when LC resonant frequency is greater than one-sixth sampling frequency and less than one-third sampling frequency, which may cause system instability when interacting with loads or grids. Therefore, a low/middle-frequency positive external-damping design method under self-stability constraint is proposed for inner control loop of GFM converters. Detailed design process is presented with simple implementation. The key feature is the use of negative proportional gain of voltage controller. Through the proposed design method, the GFM converters can improve system damping capability, which is beneficial to promoting large-scale integration of distributed generation systems based on power electronics. Simulation and experimental results are finally provided to verify the feasibility and effectiveness of the design method.