Mode Control Research Articles

Methodology for the Synthesis of a Multicopter Controller Acting as a Swarm Agent using the Thermal Motion Equivalent Method

The paper is dedicated to the development of a method for the synthesis of the control system of a swarm multicopter. The motion of the agents in the swarm is organised by the thermal motion equivalent method. The idea of the method is the behavioral similarity of the thermal motion of the atoms by the agents. In the practical implementation of the thermal motion equivalent method, it is important to ensure constancy of velocity and isotropy of agent dynamics. Violating these properties will cause the swarm to fail a mission, such as an area exploration, by reducing the RMS speed of the agents to zero. The proposed solution to these problems is to synthesize a modal controller for the agent-boundaries test system for the slowest control channel, thereby ensuring RMS velocity constancy of the agent. The synthesized controller is used as a filter in the fast-acting channels, the second horizontal channel and the vertical channel. In the fast-acting channels, an additional filter is proposed to bring their dynamics to the slowest channel, thereby ensuring isotropy. The inclusion of a limit on the maximum length of the equivalent field vector ensures isotropy. The synthesis was carried out using a simplified multicopter dynamics mathematical model, obtained with small UAV deviations from the vertical and without considering the Coriolis force. The methodology for the synthesis of a multicopter control system for functioning as part of a swarm is developed using the obtained results. Numerical simulation results of both a single vehicle in closed space and a swarm using a more complete nonlinear dynamic quadcopter model are presented. The proposed method has the advantage of simple synthesis using a linear model. Numerical simulation results confirm the operability of the developed methodology.

Spatiotemporal-restricted A∗ algorithm as a support for lane-free traffic at intersections with mixed flows

Improving the capacity of intersections is the key to enhancing road traffic systems. Benefiting from the application of Connected Automated Vehicles (CAVs) in the foreseeing future, it is promising to fully utilize spatiotemporal resources at intersections through cooperative and intelligent trajectory planning for CAVs. Lane-free traffic is currently a highly anticipated solution that can achieve more flexible trajectories without being limited by lane boundaries. However, it is challenging to apply efficient lane-free traffic to be compatible with the traditional intersection control mode for mixed flow composed of CAVs and Human-driving Vehicles (HVs). To address the research gap, this paper proposes a spatiotemporal-restricted A∗ algorithm to obtain efficient and flexible lane-free trajectories for CAVs. First, we restrict the feasible area of the heuristic search algorithm by considering the feasible area and orientation of vehicles to maintain the trajectory directionality of different turning behaviors. Second, we propose a spatiotemporal sparse sampling method by defining the four-dimensional spatiotemporal grid to accelerate the execution of the heuristic search algorithm. Third, we consider the motions of HVs as dynamic obstacles with rational trajectory fluctuation during the process of trajectory planning for CAVs. The proposed method can retain the advantage of efficiently exploring feasible trajectories through the hybrid A∗ algorithm, while also utilizing multiple spatiotemporal constraints to accelerate solution efficiency. The experimental results of the simulated and real scenarios with mixed flows show that the proposed model can continuously enhance traffic efficiency and fuel economy as the penetration of CAVs gradually increases.

Adaptive Virtual Impedance Control with MPC’s Cost Function for DG Inverters in a Microgrid with Mismatched Feeder Impedances for Future Energy Communities

More and more distributed generations (DGs), such as wind, PV or battery bank sources, are connected to electric systems or customer loads. However, the locations of these DGs are based on the highest energy that can be potentially harvested for electric power generation. Therefore, these locations create different line impedances based on the distance from the DGs to the loads or the point of common coupling (PCC). This paper presents an adaptive virtual impedance (AVI) in the predictive control scheme in order to ensure power sharing accuracy and voltage stability at the PCC in a microgrid network. The reference voltage from mismatched feeder impedances was modified by utilizing the suggested AVI-based predictive control for creating equal power sharing between the DGs in order to avoid overburdening any individual DG with low-rated power. The AVI strategy used droop control as the input control for generating equal power sharing, while the AVI output was used as the reference voltage for the finite control set–model predictive control (FCS-MPC) for creating a minimum voltage error deviation for the cost function (CF) for the inverter’s vector switching pattern in order to improve voltage stability at the PCC. The proposed AVI-based controller was tested using two DG inverter circuits in a decentralized control mode with different values of line impedance and rated power. The performance of the suggested controller was compared via MATLAB/Simulink with that of a controller based on static virtual impedance (SVI) in terms of efficiency of power sharing and voltage stability at the PCC. From the results, it was found that (1) the voltage transient magnitude for the AVI-based controller was reduced within less than 0.02 s, and the voltage at the PCC was maintained with about 0.9% error which is the least as compared with those for the SVI-based controller and (2) equal power sharing between the DGs increased during the change in the load demand when using the AVI-based controller as compared with using the SVI-based controller. The proposed controller was capable of giving more accurate power sharing between the DGs, as well as maintaining the voltage at the PCC, which makes it suitable for the power generation of consumer loads based on DG locations for future energy communities.

Contactless control of suspended loads for offshore installations: Proof of concept using magnetic interaction

Current offshore wind turbine installation and positioning methods require mechanical equipment attached on the lifted components and human intervention. The present paper studies the development of a contactless motion compensation technique by investigating a magnetically controlled pendulum. The technique involves the interaction of a magnetic pendulum with an electromagnetic actuator. Two control modes are considered: the imposition of a desired motion to the mass and the motion attenuation of a prescribed pivot excitation. The numerical model is validated and calibrated against experiments and demonstrates excellent predictive capabilities. The control exerted is effective for a broad range of excitation frequencies and amplitudes. Important parameters associated with the performance of the technique such as the separation distance of the magnets and the saturation of the controller are identified. The controllability regions for effective control depending on the characteristics of the excitation are derived. The force amplitude of the contactless actuator is comparable to currently-used active tugger line control systems, but with the additional advantage of both attractive and repulsive forces. The findings of this paper illuminate the path for the further development of a non-contact control technique which has the potential to increase the efficiency of offshore wind installations.

Analysis of the filling patterns and reservoir development models of the Ordovician paleokarst reservoirs in the tahe oilfield

The characteristics of Ordovician paleokarst reservoirs in the Tahe Oilfield are complex. Many prediction studies on the distribution of karst fractures and caves have been carried out, but the filling types and distribution characteristics of caves have been less studied and are thus less understood. First, the development characteristics of the early paleohydrological landforms in the early Hercynian are considered, the paleokarst landforms are restored, the characteristics of the paleohydrological network are clarified, and the lateral distribution of the surface and groundwater systems is illustrated. Additionally, based on a qualitative analysis of core thin section photographs, conventional logging curves, full-bore formation microresistivity scanning, imaging, logging and other characteristics, the existing filling types are divided into four classes: vertical flow filling, river transport filling, cave collapse and hydrothermal transformation. Moreover, reservoir facies division standards for the different filling types are established. Different filling types are constrained in the context of paleogeomorphology and paleohydrology to further study the filling effects and the corresponding controlling factors. As research progresses, five common joint control modes are proposed: joint control of sinkholes and underground rivers, joint control of ancient landforms and underground rivers, joint control of multilayer caves and ancient landforms, control due to collapse and fracture, and joint control of early collapse and late hydrothermal transformation. Based on the model, the relevant mechanisms and the concentrated areas of development are analyzed in depth. The distribution map of the plane filling type is obtained by combining the development model with the identification of the filling type. The relationships between oil and gas production and the reservoir filling degree and between oil and gas migration channels are analyzed by the classification and statistics of different filling types laterally, and the relationships between oil and gas production and the reservoir filling degree and between oil and gas migration channels are analyzed. Hydrothermal action has the strongest ability to transform reservoirs, mainly due to hydrothermal dissolution and fault zones transporting oil and gas; the yield of caves filled with sinkholes is relatively low, which is related to the good reservoir space retained by oil and gas filling and the migration channels provided by fault zones. The yield of the underground river filling type is lower than that of the water-falling cave filling type, mainly because the underground river filling type is located in the karst slope and lower part of the basin. The water energy in the karst slope is relatively strong, and the interior of the cave is filled with medium-fine sandstone. In the lower part of the karst zone, the water energy becomes weak; both of these conditions lead to further filling of the cave reservoir space and a lack of migration channels. The collapse filling type has the strongest impact on the reservoir because this discussion is mainly about late collapse, which causes the cave to collapse, and the internal filling is severe; even if a fault zone acts as a migration channel, oil and gas production is relatively low.

An efficient power control strategy for active mitigation of blade in‐plane fatigue loading in PMSG‐based wind turbines

AbstractThis paper assesses the dynamic performance of permanent magnet synchronous generator‐based wind turbine (WT) regarding the blade in‐plane fatigue loads once the WT is controlled in power control mode. Blade in‐plane oscillations, associated with the poorly blade in‐plane modes, can be excited by turbulent winds or grid disturbances that may lead to damage of the blades and reduce the drive‐train reliability. To overcome this drawback, at first, a model with three degrees of freedom is extracted for the drive‐train system, and then, an active mitigation approach is proposed to mitigate the blade in‐plane oscillations. The proposed method can effectively suppress the blade in‐plane vibrations by adding a supplementary term into the power control loop that is proportional to the speed difference between the blade and generator. The speed difference between the blade and generator is obtained by estimation of the blade‐hub and hub‐generator shaft torsional torques. Next, the performance of the proposed active mitigation approach is examined by the modal and frequency response analyses and time‐domain simulations. Finally, it is shown that the proposed approach has superior performance over the conventional approaches based on the simplified drive‐train model and crossing the measured generator speed through a band‐pass filter.

Design and Analysis of a Three-Phase Interleaved DC-DC Boost Converter with an Energy Storage System for a PV System

This paper describes a groundbreaking design of a three-phase interleaved boost converter for PV systems, leveraging parallel-connected conventional boost converters to reduce input current and output voltage ripple while improving the dynamic performance. A distinctive feature of this study is the direct connection of a Li-Ion battery to the DC link, which eliminates the need for an additional charging circuit, which is a departure from conventional approaches. Furthermore, the combination of an MPPT controller and a closed-loop fuzzy controller with a current control mode ensures accurate switching signal generation for all three phases. The meticulously tuned system exhibits a remarkably low ripple content in the output voltage, surpassing calculated values, and demonstrates a superior dynamic performance. The investigation extends to a comprehensive analysis of losses, encompassing inductor copper loss and semiconductor conduction loss. In all scenarios, the converter exhibits an efficiency exceeding 93%, highlighting its robust performance as an effective solution for PV systems.

Security region of inverter-interfaced power systems: Existence, expansion, and application

Since the increasing integration of inverter-based resources leads to a transition to inverter-interfaced power systems, the additional physical limits of inverters raise concerns for secure operation, which needs to be not only ensured but also enhanced. This study, therefore, investigates how to geometrically ensure and enlarge the security region of single-inverter-interfaced power systems, followed by establishing the inverter-security-constrained optimal power flow for multi-inverter-interfaced power systems. Therein, the inverter over-current and over-modulation/over-voltage limits are visualized by projecting cones into circles, ellipses, and a quadratic curve in different control variable spaces. First, for single-inverter-interfaced power systems, this study proposes a closed-form sufficient condition that guarantees the security region existence under different control modes. Then, this study quantifies and enlarges the security region size by leveraging the counter-intuitive complementary impacts of inverter parameters and the opposite impacts of system parameters. As an extension, an inverter-security-constrained optimal power flow using second-order cone programming relaxation is formulated for multi-inverter-interfaced power systems, in which this study proposes a closed-form sufficient condition to ensure a non-empty and non-decreasing security region. Numerical results of a single-inverter-interfaced power system and a modified IEEE 14 bus multi-inverter-interfaced power system verify the proposed security region properties.

ОПТИМАЛЬНЫЕ РЕЖИМЫ ИМПУЛЬСНОГО УПРАВЛЕНИЯ ПРИВОДОМ ЭЛЕКТРИФИЦИРОВАННОЙ ПЛАТФОРМЫ

In autonomous drives of highly maneuverable vehicles with adaptive control systems, DC motors have become the most widespread. To control them, pulse width modulation is used, in which the simplicity of the algorithm is combined with high-frequency current fluctuations in the motor windings. When optimizing these modes, it is necessary to choose both the control mode and its parameters correctly, taking into account the specifics of the power source, for example, a battery with limited capacity. (Research Purpose) The research purpose is analyzing the optimal parameters for stream and batch modes of pulse-width control of DC motors from rechargeable batteries. (Materials and methods) For the analysis of control modes, generally accepted dependencies describing the relationship of controlled parameters in transient processes, as well as methods for solving differential equations, are used. A general approximate solution of the equation relating current and voltage is obtained, and its approximation for the flow control mode is determined. (Results and discussion) The obtained solution is studied for the practical feasibility of the stream mode. The corresponding analytical condition is derived, in case of violation of which it is necessary to apply the batch control mode. (Conclusions) The optimal parameters of pulse width modulation are analyzed when controlling drives with DC motors from autonomous power sources. Based on the general solution obtained, the application area of the streaming control mode and the optimal values of the corresponding parameters, as well as the application area of the batch control mode and its optimal parameters are highlighted. The use of the proposed equations makes it possible to improve the quality of drive control, to increase its accuracy, to reduce peak loads and unproductive power losses when driving autonomous vehicles.

Controllability of Functional and Structural Brain Networks

Normal and aberrant cognitive functions are the result of the dynamic interplay between large‐scale neural circuits. Describing the nature of these interactions has been a challenging task yet important for neurodegenerative disease evolution. Fusing modern dynamic graph network theory techniques and control theory applied on complex brain networks creates a new framework for neurodegenerative disease research by determining disease evolution at the subject level, facilitating a predictive treatment response and revealing key mechanisms responsible for disease alterations. It has been shown that two types of controllability—the average and the modal controllability—are relevant for the mechanistic explanation of how the brain navigates between cognitive states. The average controllability favors highly connected areas which move the brain to easily reachable states, while the modal controllability favors weakly connected areas representative for difficult‐to‐reach states. We propose two different techniques to achieve these two types of controllability: a centrality measure based on a sensitivity analysis of the Laplacian matrix is employed to determine the average controllability, while graph distances form the basis of the modal controllability. The concepts of “choosing the best driver set” and “graph distances” are applied to measure the average controllability and the modal controllability, respectively. Based on these new techniques, we obtain important disease descriptors that visualize alterations in the disease trajectory by revealing densely connected hubs or sparser areas. Our results suggest that these two techniques can accurately describe the different node roles in controlling trajectories of brain networks.

Evaluation of Helicopter Ship Deck Landing Control Laws in Piloted Simulations

This paper describes the implementation and the evaluation of newly designed helicopter ship deck landing control modes in a piloted simulation study. The ship deck landing modes are embedded in a model-following controller architecture. The employed control design is a complete model-following control system, which imposes the desired command model dynamics on the controlled helicopter. Different command types combined with various hold functions are implemented to make the task easier for the pilots. Three basic command modes and three advanced command modes, one without ship communication and two with ship communication, are implemented. A piloted simulation study was performed in a simulator to evaluate and compare the implemented control modes within a complete maritime scenario design. The evaluation of control modes is based on the success of helicopter ship deck landings which is assessed by a quantitative as well as a qualitative assessment. Simulation results demonstrate that the advanced command modes improved the task performance as well as reduced the pilot workload extensively in comparison to the basic command modes.

Адаптивное скользящее управление бесколлекторным двигателем

Brushless DC motors offer many advantages over brushed DC motors. In this article, based on the constructed kinematic model of a brushless motor, a classical sliding mode of motor control is synthesized. A study of the sliding mode of motor control was carried out in the Matlab Simulink software environment and the shortcomings of the classical sliding controller were established. To eliminate these shortcomings, an adaptive sliding controller has been synthesized, consisting of a classical sliding controller and a PI controller. Simulation in the Matlab Simulink software environment proves the efficiency of a synthesized adaptive sliding controller that controls a brushless motor in an environment of noise and disturbances.

SSIOE: Self-Supervised Indoor Occupancy Estimation for Intelligent Building Management

This paper aims to estimate indoor occupancy given the real-time observed signals from the existing sensors; next, as a practical application, we build a dynamic control schedule for energy saving based on the estimated indoor occupancy. However, several issues need to be addressed. First, it is impossible to train the model with rich labels due to the expensive labeling cost. Second, manual annotation of the continuous occupancy rate is complex. Third, the mapping relationship between sensor data and occupancy will change in the long run. In this paper, we proposed a new algorithm named Self-Supervised Indoor Occupancy Estimation (SSIOE) to overcome the challenges. Specifically, our training scheme aims to (I) generate a set of pseudo labels in a simple way to mark the time periods believed to be either in a high or low occupancy state and (II) utilize these sparse labels for training a network to infer the continuous occupancy ratio. By reformulating the problem as a Wasserstein-distance-like estimation, SSIOE is a novel learning-based method that can rely only on the weak/sparse labels of either “high-occupancy” or “low-occupancy” and learn to estimate the continuous occupancy ratio. Furthermore, to deal with the scarce annotation problem, we proposed a novel physical constraint loss to model the physical prior. (III) Last but not least, to strengthen the adaptability, we integrated Model-Agnostic Meta-Learning (MAML) to train the model for dynamic model updating. Experimental results show that SSIOE can provide reliable occupancy estimation and flexibly adapt to various control modes without retraining the model. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the real-time occupancy estimation problem, which is crucial for building management systems to arrange lighting and air conditioning. A dynamic schedule adapted to the occupancy would help balance the user’s comfort and energy saving; however, installing the occupancy sensors raises additional costs. Therefore, this paper proposes SSIOE, a label-free machine learning algorithm that can learn to estimate the continuous occupancy ratio given the sensor status in real time. Prior works trained upon supervised machine learning methods suffer from heavy manual annotation workload, while the unsupervised machine learning approaches fail to provide continuous occupancy estimation values. This paper addresses the above challenges by proposing a novel self-supervised training scheme. Preliminary experiments suggest that this approach is feasible to work in real-world buildings. However, it should be noted that the occupancy estimated by SSIOE is a ratio (0.0-1.0), which is relative to the maximum and minimum occupancy of the training data (or fine-tuning data). For example, if the maximum number of occupants in the training data is 200 and the minimum number of occupants is 50, then the estimated occupancy value of 1.0 is about 200 occupants, and the occupancy value of 0.0 is about 50 occupants. When the maximum and minimum occupants of the space change, the model needs to be updated to capture the new mapping of the estimated occupancy ratio to the number of occupants. In future research, we plan to further improve and simplify the adaptation ability of SSIOE by continuously and automatically updating the system with the latest collected as the system runs.

Двухуровневый параметрический метод оптимизации траектории перелета с малой тягой

A direct method is proposed for solving the optimal control problem of a spacecraft equipped with a low-thrust engine. The control function is parameterized using polynomials and switching moments between active and passive control modes. The essence of the method lies in separating optimization parameters: at the outer level, the switching time moments of control modes are optimized, while at the inner level, the coefficients of auxiliary polynomials are optimized. The method’s performance is demonstrated on problems of interplanetary flight to Mars and the conversion of impulse control to continuous control.

Vulnerability of the Building Construction Safety System Based on ANP-SD

The study aims to analyze the evolution trend of system vulnerability under the interactive relationship of building construction risk factors. Based on social technology theory, the influencing factors are analyzed from four subsystems: individual, technology, organization management, and internal and external environment. By using the method of “network AHP” (ANP), the “relative value” and “absolute value” of each factor are established. A comprehensive simulation model is established to simulate and analyze the “single” and “combined” control modes. The results show that, compared with the vulnerability of the building construction system in the initial state, the minimum decline of the vulnerability evolution trend of the building construction system is only 1.28%, and the maximum is only 14.2% after adopting a single control measure. Among them, the biggest decline in the vulnerability evolution trend is the construction of enhanced safety culture in personal subsystem control measures. After taking joint control measures, the decline of vulnerability evolution trend of the housing construction system is [25.96%, 36.8%]. The control effect of joint control measures is not that the more control measures are taken, the better. However, it depends on the absolute coefficient of the related factors of the influencing factors of the trunk center and the subsystem to which they belong to provide a reference for the risk control of housing construction.

Broken Rotor Bars Detection in Inverter-Fed Induction Motors Under Continuous Switching of Different Speed Modes

Broken rotor bars (BRBs) fault detection of inverter-fed induction motors operating in transient regime is difficult, and even more challenging under continuous switching of constant speed, acceleration, and deceleration modes (CADM). In this condition, the BRBs caused amplitude-modulation of fundamental harmonic can be used as a fault indicator. However, the amplitude and frequency of the fundamental harmonic vary widely in continuous switching of CADM, which causes tremendous difficulty in the fault feature extraction. In this paper, a novel approach called Adaptive Window Short-time Esprit (AWSTE) is developed to overcome the described problem. It can track the fundamental frequency and extract the envelope of fundamental harmonic under continuous switching of CADM. Experimental results demonstrate the validity of the proposed approach at different control modes, different load levels, and different noise levels.

PID/FOPID Tuning Rule Based on a Second Order Inverse Response Process Model with Robustness Considerations

This paper deals with the design of a proportional-integral-derivative (PID) and fractional-order proportional-integral-derivative (FOPID) controller tuning rule for second-order controlled processes with inverse response. The design of the rules takes into account specific levels of robustness and performance for both load disturbance rejection and set-point tracking tasks. In the first step, the optimal parameters for both controllers are obtained from optimizations that seek to minimize the error in both control modes while maintaining the robustness constraint. Subsequently, fitting functions to the optimal parameters are sought to capture their behavior with the possibility of finding optimal parameters with the tuning rule designed between certain ranges of the model parameters. For FOPID and PID controllers, the rule IRM-RoT (Inverse Response Model Robust Tuning) have been developed. The performance of the controllers was compared using examples, and the results showed that fractional order controllers provide a novel solution for inverse response dynamics in process control.

Two-Layer Asynchronous Control for a Class of Nonlinear Jump Systems: An Interval Segmentation Approach.

This article proposes the two-layer asynchronous control scheme for a class of networked nonlinear jump systems. For the constructed system in a network environment, the data transmission may suffer from many restrictions, such as incomplete acceptable mode information and transition information, nonlinearity of system and inadequate bandwidth resources, etc. Then, the two-layer asynchronous controller is developed to stabilize the plant constructed by Takagi-Sugeno (T-S) fuzzy method and semi-Markov theory (SMT). Herein, the hidden semi-Markov process with time-varying emission probability is introduced to establish the relation between the system modes and the controller modes, in which the interval segmentation method is presented to deal with this time-varying probability. Compared with some published results, this method can make full use of the transition rate information, which may lead to the reduction of conservatism in the proposed asynchronous control design. At the same time, the limited bandwidth problem in the communication channel is addressed by introducing the bilateral quantization strategy, and the new sufficient conditions are derived on the stochastic stability of the nonlinear jump system with/without incomplete transition and sojourn-time information. Finally, the numerical simulation examples about DC motor illustrate the effectiveness and the feasibility of the proposed approach.

Trajectory Deformation-Based Multi-Modal Adaptive Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

Adaptive compliance control is critical for rehabilitation robots to cope with the varying rehabilitation needs and enhance training safety. This article presents a trajectory deformation-based multi-modal adaptive compliance control strategy (TD-MACCS) for a wearable lower limb rehabilitation robot (WLLRR), which includes a high-level trajectory planner and a low-level position controller. Dynamic motion primitives (DMPs) and a trajectory deformation algorithm (TDA) are integrated into the high-level trajectory planner, generating multi-joint synchronized desired trajectories through physical human-robot interaction (pHRI). In particular, the amplitude modulation factor of DMPs and the deformation factor of TDA are adapted by a multi-modal adaptive regulator, achieving smooth switching of human-dominant mode, robot-dominant mode, and soft-stop mode. Besides, a linear active disturbance rejection controller is designed as the low-level position controller. Four healthy participants and two stroke survivors are recruited to conduct robot-assisted walking experiments using the TD-MACCS. The results show that the TD-MACCS can smoothly switch three control modes while guaranteeing trajectory tracking accuracy. Moreover, we find that appropriately increasing the upper bound of the deformation factor can enhance the average walking speed (AWS) and root mean square of trajectory deviation (RMSTD).

Метод проверки робастного качества управления для линейных одномерных дискретных систем управления

The article deals with one-dimensional linear control objects in discrete time. It is assumed that the operators of the control object have structural and parametric inaccuracies in the description. In this paper, a criterion for the robust quality of control is obtained for a system consisting of a discrete control object with structural perturbations and a modal controller. Based on this criterion, a numerical method for checking the robust quality of control has been developed. The effectiveness of the method is illustrated by an example.