Control Performance Research Articles

Performance Evaluation and Comparative Analyses of Tuned Inerter Damper for Stochastic Base Excited Structures Based on Hybrid H2/H∞ Optimization

Compared with tuned mass damper, tuned inerter damper (TID) has higher damping efficiency and lightweight characteristic if appropriate optimal methods are selected. Generally, [Formula: see text] or [Formula: see text] optimal methods are adopted to determine the optimal parameters of TID individually. But the vibration mitigation performance of the TID under near resonance frequency band based on [Formula: see text] optimization is less than [Formula: see text] optimization, but the peak frequency response based on [Formula: see text] optimization will be greater than [Formula: see text] optimization at the same time. Dual-characteristic-based vibration control may not be achievable based on [Formula: see text] or [Formula: see text] criteria, respectively. For this reason, hybrid [Formula: see text] optimization can be adopted. In this work, closed-form expressions are derived for the control of structural displacement responses based on hybrid [Formula: see text] optimal method. The vibration mitigation performance of the different optimized TIDs is evaluated considering the single-degree-of-freedom and multi-degrees-of-freedom systems are subjected to typical ground motions excitation. Results illustrate that because of the use of the optimal stiffness ratio of [Formula: see text] optimization and very close value of [Formula: see text] optimizations’ nominal damping ratio in [Formula: see text] optimization, [Formula: see text] optimization shows ‘dual characteristics’ in different excitation situations. Specifically, the peak response and structural fundamental frequencies’ response in displacement frequency response function using hybrid [Formula: see text] optimal methods are between [Formula: see text] and [Formula: see text] optimization, which indicates an excellent and balanced control performance combining the advantages of [Formula: see text] and [Formula: see text] optimal solutions. Hence, this hybrid method is more suitable for more complex ground motions excitation to control critical structural responses instead of single characteristic excitation. And the comprehensive vibration control in dynamic time histories analyses can be achieved by this dual characteristic-based optimal strategy. When designing the specific TID, hybrid [Formula: see text] optimization can be considered as the best choice for its compatibility and high adaptability for complex practical engineering scenarios with random and diverse excitations.

Acute Toxicity of Malathion, Permethrin, and Roundup on the Tropical Freshwater Shrimp Xiphocaris elongata (Guérin-Méneville, 1855)

Urban and agricultural runoffs can transport contaminants and pesticides into freshwater ecosystems, particularly in the developing tropics. For instance, organophosphate and pyrethroids pesticides, such as Roundup, Malathion, and Permethrin, have been found in tropical streams. The uncontrolled application of these pesticides has become a growing concern due to their adverse effects on various non-targeted organisms. Unfortunately, most studies have focused on a few selected model species, ignoring the effects on other non-target organisms, which may play an important role in tropical lotic ecosystems. In addition, the biological characteristics of aquatic crustaceans, including their morphology, physiology, and behavior, make them susceptible to toxic chemicals. For this reason, this study used the widely distributed freshwater shrimp Xiphocaris elongata as a model organism to determine the acute toxicity of Permethrin, Malathion, and Roundup. Our results show that the proportion of mortality of X. elongata in each concentration group became progressively higher as the concentration of exposure increased. We also found that the synthetic pyrethroid Permethrin was the most toxic pesticide tested, with a median lethal concentration (LC50) value for 96 h of 3.96 × 10−6 µg·L−1, followed by organophosphate Malathion (8.87 µg·L−1) and Roundup (748.92 µg·L−1). Experiments with this freshwater shrimp showed a good control performance and reproducibility for the tested pesticides. This study demonstrated that X. elongata is a suitable test organism that can be a representative bioindicator of pesticide toxicity in tropical streams.

Reinforcement learning control of multi-spectral LED systems for rendering optimal lighting performance in indoor environment

Light-emitting diodes (LEDs) have superseded traditional light sources due to their superior qualities. However, achieving desired spectral distribution in indoor environment still remains a challenge, particularly for optimizing multiple lighting parameters, which are nonlinear functions of the light spectra, including correlated color temperature (CCT), color rendering index (CRI) and circadian action factor (CAF). Existing studies have been mainly devoted to seeking optimal solutions, by means of various optimization methods, e.g. genetic algorithms. However, these methods can only result in fixed recipes to achieve pre-assigned reference parameters, and cannot meet the need of dynamic varying lighting environment. Therefore, this paper proposes a novel framework for optimal spectrum design and control in multichannel LED lighting systems. It surpasses traditional methods by employing reinforcement learning (RL) to generate an entire optimal spectral power distribution (SPD) model, comprehensively considering CCT, CRI, CAF, and other relevant parameters. This framework integrates the RL-based optimal SPD generator with a corresponding real-time controller, bridging the gap between simulations and real-world applications. The effectiveness of this new framework has been verified by an experimental prototype, showcasing both the optimal SPD and the achieved control performance. This work paves the way for high-quality, user-centric lighting with dynamic CCT and spectral control, and enables the creation of lighting environments that optimize human well-being, productivity, and overall experience.

Acute Toxicity of Malathion, Permethrin, and Roundup on the Tropical Freshwater Shrimp Xiphocaris elongata (Guérin-Méneville, 1855)

Urban and agricultural runoffs can transport contaminants and pesticides into freshwater ecosystems, particularly in the developing tropics. For instance, organophosphate and pyrethroids pesticides, such as Roundup, Malathion, and Permethrin, have been found in tropical streams. The uncontrolled application of these pesticides has become a growing concern due to their adverse effects on various non-targeted organisms. Unfortunately, most studies have focused on a few selected model species, ignoring the effects on other non-target organisms, which may play an important role in tropical lotic ecosystems. In addition, the biological characteristics of aquatic crustaceans, including their morphology, physiology, and behavior, make them susceptible to toxic chemicals. For this reason, this study used the widely distributed freshwater shrimp Xiphocaris elongata as a model organism to determine the acute toxicity of Permethrin, Malathion, and Roundup. Our results show that the proportion of mortality of X. elongata in each concentration group became progressively higher as the concentration of exposure increased. We also found that the synthetic pyrethroid Permethrin was the most toxic pesticide tested, with a median lethal concentration (LC50) value for 96 h of 3.96 × 10−6 µg·L−1, followed by organophosphate Malathion (8.87 µg·L−1) and Roundup (748.92 µg·L−1). Experiments with this freshwater shrimp showed a good control performance and reproducibility for the tested pesticides. This study demonstrated that X. elongata is a suitable test organism that can be a representative bioindicator of pesticide toxicity in tropical streams.

A robust and optimal voltage control strategy for low-voltage grids utilizing group coordination of photovoltaic and energy storage systems via consensus algorithm

This study presents a novel voltage control strategy for low voltage (LV) distribution grids, addressing the lack of coordination between photovoltaic (PV) reactive control and energy storage system (ESS) active control. The proposed strategy concentrates on group coordination of PV and ESS to improve LV grid performance. Initially, it suggests employing PV reactive power for voltage regulation before utilizing ESS active power, relying on the voltage cost sensitivity factor (VCSF) of different regulating devices, to reach efficient PV resource utilization. Devices are categorized by their VCSF, prioritizing groups with larger VCSF for voltage regulation, enhancing overall coordination. In the PV reactive voltage regulation stage, the reactive power utilization rate is the consensus variable, while in the ESS active control stage, the change in state of charge (SOC) is the consensus variable, collectively working towards desired voltage regulation and SOC change. Coordinated control is utilized to converge key node voltages to set values and obtain effective LV grid voltage regulation. An IEEE 14-node LV grid simulation incorporating PV and ESS validates the proposed strategy, demonstrating its effectiveness and correctness in improving voltage control performance. The strategy achieves 70.56% of the capacity and 81.45% of the setup cost compared to similar research, with associated costs limited to 15.80% and 35.0% of accumulated costs.

Enhanced Fuzzy-Based Super-Twisting Sliding-Mode Control System for the Cessna Citation X Lateral Motion

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC.

Identification and Compensation Method of Unbalanced Error in Driving Chain for Rate-Integrating Hemispherical Resonator Gyro.

The accuracy of the signal within a driving chain for the rate-integrating hemispherical resonator gyro (RI-HRG) plays a crucial role in the overall performance of the gyro. In this paper, a notable and effective method is proposed to realize the identification and compensation of the unbalanced error in the driving chain for the RI-HRG that improved the performance of the multi-loop control applied in the RI-HRG. Firstly, the assembly inclination and eccentricity error of the hemispherical resonator, the inconsistent metal conductive film layer resistance error of the resonator, the coupling error of the driving chain, and the parameter inconsistency error of the circuit components were considered, and the impact of these errors on the multi-loop control applied in the RI-HRG were analyzed. On this basis, the impact was further summarized as the unbalanced error in the driving chain, which included the unbalanced gain error, equivalent misalignment angle, and unbalanced equivalent misalignment angle error. Then, a model between the unbalanced error in the driving chain and a non-ideal precession angular rate was established, which was applicable to both single channel asynchronous control and dual channel synchronous control of the RI-HRG. Further, an unbalanced error identification and compensation method is proposed by utilizing the RI-HRG output with the virtual precession control. Finally, the effectiveness of the proposed method was verified through simulation and experiments in kind. After error compensation, the zero-bias instability of the RI-HRG was improved from 3.0950°/h to 0.0511°/h. The results of experiments in kind demonstrated that the proposed method can effectively suppress the non-ideal angular rate output caused by the unbalanced error in the driving chain for the RI-HRG, thereby further improving the overall performance of the RI-HRG.

A Reconfigurable Single-/Dual-Bandstop Filter with Controllable Equal-Ripple Performance

Bandstop filters (BSFs) have many applications in suppressing interference signals and shielding specific bands. Among them, reconfigurable BSFs that cover more frequency bands by switching modes have great research value. In this paper, a novel synthesis approach for compact reconfigurable BSFs with controllable equal-ripple performance is proposed. By switching the ON/OFF state of the positive intrinsic negative (PIN) diode, the proposed reconfigurable BSF can be switched between single-BSF (S-BSF) and dual-BSF (D-BSF). Based on the synthesis approach, the equal-ripple levels of stopband and passband for S-BSF and D-BSF can be independently controlled. To verify, the equal-ripple levels of stopband and passband for S-BSF state and D-BSF state are independently controlled in four groups of examples. Finally, a reconfigurable BSF with a miniaturized size is designed and fabricated. The fabricated reconfigurable BSF behaves with 15 dB and 10 dB return loss (RL) in two different passbands of the D-BSF state, and 25 dB bandpass RL and controllable stopband rejection (SR) for the S-BSF state. The measured results are in good agreement with the electromagnetic (EM) simulation results.

Cooperative voltage control in distribution networks considering multiple uncertainties in communication

Delays, jitter, and packet loss in communication networks can impact the performance of cooperative voltage control systems in distribution networks. In distribution systems with a high penetration of renewable energy sources that do not respond promptly, these issues can even lead to system destabilization when voltage surges occur. Considering the interdependence of delay, jitter, and packet loss, the current direct approach of accumulating information entropy may result in the deterioration of dynamic control performance. Based on Copula entropy theory, a new multivariate communication uncertainty metric model is proposed. Using the multivariate Epanechnikov kernel function model, a method has been developed to estimate the multivariate non-independent uncertainty of a communication system. Accurate state estimation is integrated into event-triggered sliding mode control (ETSMC) of the distribution network to facilitate coordinated voltage control and enhance resilience against communication uncertainty. Design criteria for the controller and observer parameters are provided based on Lyapunov stability theory. Simulation results confirm that the proposed ETSMC offers significant improvements in control performance and system resilience to external power disturbances and multivariate communication uncertainty events.

Virtual synchronous generator control with parameters optimization based on new WaOA algorithm for grid-feeding inverters

The widespread integration of renewable energy sources (RESs) within traditional power systems causes a considerable impact, such as a decrease in total inertia, damping properties, and large frequency deviation. To tackle this issue, numerous research have been proposed to introduce the virtual synchronous generator (VSG) control strategy as an effective solution applied to power electronics inverters operating in grid-forming or grid-feeding control modes. However, the proper tunning of the inertia and damping parameters is considered as a significant challenge to ensure the system stability and reliability. In this paper, an efficient meta-heuristic Walrus Optimization Algorithm (WaOA) -based VSG control intended for grid-feeding inverters within a weak grid is proposed. The objective of this work is to offer a proper tuning of the VSG parameters, thereby improving the dynamic characteristics of the microgrid (MG) and guaranteeing a stable operation. In addition, it highlights the adopted optimization technique which is introduced on VSG control while ensuring minimum objective function value. Through offline simulations in MATLAB/Simulink, the superiority of the suggested WaOA method is first confirmed, in which it offers the lowest Integral Square Error (ISE) fitness function value of 0.026, compared to the Mountain Gazelle Optimizer (MGO) and Tunicate Swarm Algorithm (TSA) with 0.027 9 and 0.0281, respectively. Second, the performance of the WaOA-based VSG control is compared to the ones based on MGO and TSA techniques under active and reactive power variations. The obtained results demonstrate that the proposed VSG control ensures a better transient performance, especially in terms of under and overshoots.

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as “Porpoising”. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems

In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward control, which requires the announcement of the meal by the patient with type 1 diabetes (DM1) to achieve the desired glycemic control performance. The calculation of insulin bolus in the HAID system is based on the amount of carbohydrates (CHO) in the meal and patient-specific parameters, i.e. carbohydrate-to-insulin ratio (CR) and insulin sensitivity-related correction factor (CF). The estimation of CHO in a meal is prone to errors and is burdensome for patients. This study proposes a fully automatic insulin delivery (FAID) system that eliminates patient intervention by compensating for unannounced meals. This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO content. The DRL bolus calculator is integrated with a closed-loop controller and a meal detector (both previously developed by our group) to implement the FAID system. An adult cohort of 68 virtual patients based on the modified UVa/Padova simulator was used for in-silico trials. The percentage of the overall duration spent in the target range of 70–180 mg/dL was 71.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$71.2\\%$$\\end{document} and 76.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$76.2\\%$$\\end{document}, <70\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$<70$$\\end{document} mg/dL was 0.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.9\\%$$\\end{document} and 0.1%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.1\\%$$\\end{document}, and >180\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>180$$\\end{document} mg/dL was 26.7%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$26.7\\%$$\\end{document} and 21.1%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$21.1\\%$$\\end{document}, respectively, for the FAID system and HAID system utilizing a standard bolus calculator (SBC) including CHO misestimation. The proposed algorithm can be exploited to realize FAID systems in the future.

Wind and Wave-Induced Vibration Reduction Control for Floating Offshore Wind Turbine Using Delayed Signals

Active vibration control is a critical issue of the wind turbine in the field of marine energy. First, based on a three-degree-of-freedom wind turbine, a state space model subject to wind and wave loads is obtained. Then, a delayed state feedback control scheme is illustrated to reduce the vibration of platform pitch angle and tower top foreaft displacement, where the control channel includes time-delay state signals. The designed controller’s existence conditions are investigated. The simulation results show that the delayed feedback H∞ controller can significantly suppress wind- and wave-induced vibration of the wind turbine. Furthermore, it presents potential advantages over the delay-free feedback H∞ controller and the classic linear quadratic regulator in two aspects: vibration control performance and control cost.

Experimental Investigation of the Performance of a Novel Ejector–Diffuser System with Different Supersonic Nozzle Arrays

The supersonic–supersonic ejector–diffuser system is employed to suck supersonic low-pressure and low-temperature flow into a high-pressure environment. A new design of a supersonic–supersonic ejector–diffuser was introduced to verify pressure control performance under different operating conditions and vacuum background pressure. A 1D analysis was used to predict the geometrical structure of an ejector–diffuser with a rectangular section based on the given operating conditions. Different numbers and types of nozzle plates were designed and installed on the ejector to study the realizability of avoiding or postponing the aerodynamic choking phenomenon in the mixing section. The effects of different geometrical parameters on the operating performance of the ejector–diffuser system were discussed in detail. Experimental investigation of the effects of different types of nozzle plates and the back pressures on the pressure control performance of the designed ejector–diffuser system were performed in a straight-flow wind tunnel. The results showed that the position, type and number of the nozzle plates have a significant impact on the beginning of the formation of aerodynamic choking. The geometry of the ejector and the operating conditions, especially the backpressure and inlet pressure of the ejecting stream, determined the entrainment ratio of the two supersonic streams. The experimental results showed that long nozzle-plate had a better performance in terms of maintaining pressure stability in the test section, while short a nozzle-plate had a better pressure matching performance and could maintain a higher entrainment ratio under high backpressure conditions.

Effect of prediction uncertainties on the performance of a white-box model predictive controller for district heating networks

The performance of a model predictive controller (MPC) depends on the accuracy of the controller model and predictions of system disturbances. This paper studies the effect of prediction uncertainties and/or an imperfect state observer on the performance of a white-box MPC applied to a small-scale district heating network by performing a co-simulation with a detailed emulator model. This effect is studied for both a non-linear program (NLP)-based MPC and a mixed-integer NLP (MINLP)-based MPC. The results show a limited impact of prediction uncertainties when using a perfect state observer, with electricity use and thermal discomfort changing by only ▪ to ▪ and ▪/day/building to 0.56 ▪/day/building. An MPC with perfect predictions and a simple state observer only impacts the MPC's trade-off between electricity use and thermal discomfort: the former increases by 2–▪ but the latter decreases by 0.01–▪/day/building. The combined effect of both simplifications has a significant impact with an increase in electricity use and thermal discomfort of 2–▪ and 0.35–▪/day/building, but MPC still outperforms a conventional rule-based controller. The MINLP-based MPC better predicts the actual system behaviour, but its performance is similar compared to the NLP-based MPC in terms of electrical energy use and thermal comfort.

Balance Control Deficits are Associated with Diminished Ankle Force Sense, Not Position Sense, in Athletes with Chronic Ankle Instability

ObjectivesTo compare balance control and ankle proprioception between athletes with and without chronic ankle instability (CAI). A further objective was to explore the relationship between balance control performance and ankle proprioception in athletes with CAI. DesignCross-sectional study. SettingsSports Rehabilitation Laboratory. ParticipantsEighty-eight recreational athletes (47 CAI and 41 healthy control) were recruited. InterventionsNo applicable. Main outcome measuresBalance control performance was assessed using the sway velocity of the centre of the pressure during the one-leg standing tasks. Ankle proprioception, including joint position sense and force sense, were tested using absolute error (AE) associated with joint position reproduction and force reproduction tasks in four directions, i.e., plantarflexion, dorsiflexion, inversion, and eversion. ResultsAthletes with CAI performed significantly worse than those without CAI in balance control tasks. In addition, CAI athletes showed significantly worse joint position sense and force sense in all three movement directions tested (plantarflexion, inversion, and eversion). Correlation analysis showed that the AE of the plantarflexion force sense was significantly moderately correlated with medial-lateral sway velocity in the one-leg standing with eyes open and closed conditions (r = 0.372–0.403, p = 0.006–0.012), and the AE of inversion force sense was significantly moderately correlated with medial-lateral sway velocity in the one-leg standing with eyes open (r = 0.345, p = 0.018) in athletes with CAI, but the joint position sense measures were not (all p > 0.05). ConclusionsAthletes with CAI showed significantly impaired balance control performance and diminished ankle proprioception. Deficit in force sense was deemed as a moderate predictor of one-leg standing balance control deficits in athletes with dominant-side injury CAI, while ankle position sense may be a small predictor.

A Simplified Model Predictive Current Control Strategy for Six-phase H-bridge Inverters

Background: The double-end H-bridge inverters can realize independent control of the stator voltage in each phase and have flexible advantages of modulation and fault tolerance; thus, they are more suitable for multi-phase fault-tolerant motor drives. However, due to the increase of voltage vectors and the coupling between the electromagnetic and non-electromagnetic quantities, the normal control strategies for traditional three-phase motor drives do not work anymore. Objective: This paper aimed to propose a simplified model predictive current control strategy based on the vector space decomposition (VSD) and the vectors’ gradual simplification for the three-level six-phase H-bridge inverters. Methods: Firstly, the 729 physical variables were decomposed and mapped onto the fundamental αβ subspace, harmonic xy subspace, and the zero-sequence o1o2 subspace based on the VSD. Then, to eliminate the influence of the harmonic and zero-sequence components on the control performance and make an easy digital implementation, vectors’ simplification has been proposed based on the in-depth analysis of the relationship between the voltage vectors mapped onto different subspaces and vectors’ stratification. With the simplification method, the number of voltage vectors was simplified from 729 to 12, and then the selected voltage vectors were used in the rolling optimization of the model predictive current control (MPCC) to choose the optimal one. Finally, sufficient experiments were carried out including static and dynamic conditions, different modulation index and power factor, etc., to verify the feasibility of the proposed strategy. Results: The simulation and experimental results show that with the simplified MPCC strategy, both the static and dynamic performances are relatively good, and the THDs of the phase current under different modulations and power factors are relatively low. Conclusion: The proposed MPCC algorithm for the three-level six-phase H-bridge inverters has shown obvious improvement in solving the control problems of multi-vectors and complex redundancy issues.

Comparison of different control methods on the thermally activated building system (TABS) with large energy flexibility

Thermally Activated Building Systems (TABS) has great energy flexibility potential for the effective demand response, but the inherent large thermal inertia creates challenges for the control. Model Predictive Control (MPC) can improve the control efficiency while achieving certain objectives. However, the modeling mechanism of the TABS thermal behavior can lead to the difference in the controller performances. In this study, the white-box model, grey-box model, and black-box model based MPCs (referred to as W-MPC, G-MPC, and B-MPC) are developed and analyzed in depth for a case TABS with high heat flexibility potential. The performances of MPC strategies are investigated together with the baseline Rule Based Control (RBC) strategy under normal conditions as well as a variety of uncertainty events. In general, MPC strategies show better performance compared to the RBC. The prediction-based control can effectively maintain the indoor temperature within the constraints considering the uncertain disturbances and the gradual outdoor climate change. Moreover, MPC strategies help to increase the cost savings due to the effective load shifting by 30%-50%, and enhance the flexible energy utilization by 14%-29%. In terms of the comparison among the different MPC strategies, W-MPC shows better performance in the room temperature control, which reduces the violation of the indoor temperature constraint by 30% and 15% compared to G-MPC and B-MPC, respectively. G-MPC shows slight superiority concerning the economy and flexible energy usage. The normalized cost saving of G-MPC is approximately 3% and 8% lower compared to the W-MPC and B-MPC, respectively, while the utilization efficiencies of the flexible energy are approximately 6% and 12% higher.

Research on the design and control of an anthropomorphic waist structure for life support robots

AbstractIn the humanoid robots, waist mechanism is an important structure to realize the whole body coordinated movement. This paper proposes a series–parallel mechanism of waist structure, and its kinematics and dynamics characteristics are studied. Based on the dynamic model, a backstepping sliding mode controller is designed to simulate control performance. Under the continuous disturbance force, the stability and accuracy of the mechanism are verified. Compared with the experiment, the results prove that the waist mechanism has the biomimetic spine movements and desired control performance, which can be applied to life support robots in the future.

Quantized control for interconnected PDE systems via mobile measurement and control strategies

This paper deals with the Rϵ-stabilization for interconnected partial differential equation systems (IPDESs) by mobile measurement and control strategies. First, compared to the static measurement and control strategies, the mobile ones are employed to improve the dynamic response of the closed-loop system, while reducing the number of sensors and actuators effectively. Moreover, considering the constrained transmission channel bandwidth, the hysteresis quantizer with an adjustable parameter is introduced to save the communication resources in the network, while can balance the quantization effect and the control performance by adjusting the parameter. Further, the output quantization controller is designed to ensure that the closed-loop system is Rϵ-stable, which converges to a given interval in finite time. Finally, a simulation example of chemical non-isothermal tubular reactors is provided to illustrate the validity of the presented design method.