Switching Control Research Articles

Innovative Geotechnical Solutions for Sustainable Infrastructure Development

Aim: To examine innovative geotechnical solutions for sustainable infrastructure development. Problem Statement: The advancement in the world urbanization together with high rise in global population has alarmed the need for new infrastructures with additional innovative research to be conducted with already existing assets. Thus, It is important that geotechnical engineering should include basic practices targeting resource-efficient and environment-friendly techniques in order to add to sustainable development. Significance of Study: This technical review critically examines the innovative geotechnical solutions for sustainable infrastructure development. The content presented in this manuscript will be beneficial to professionals in the area of geotechnical engineering. Methodology: Recent relevant published articles in the area of innovative geotechnical solutions for sustainable infrastructure development were consulted. These include journal articles, conference papers, Asian Development Bank articles and unpublished doctoral documents. Discussion: The six main environmental objectives of the Taxonomy Regulation to ensure the contours of an environmentally sustainable infrastructure were stated to include: (1) sustainable protection and use of marine and water resources (2) pollution control and prevention (3) switch to a circular economy (4) mitigation of climate change (5) restoration and protection of ecosystems and biodiversity and (6) adaptation of climate change. The three phase methods for sustainability infrastructure development in geotechnics were critically discussed. An imaginary excavation site in the municipality of Rozzano was referenced as a case study to reveal the application of the proposed methodology to the soil treatment systems. It was noticed that the adoption of an LCA introduces additional deep knowledge and the required quantitative analysis for sizing the assessment. Conclusion: The examined innovative geotechnical solutions were contributory to sustainable infrastructure development.

Variable Structure Controller for Energy Savings in an Underwater Sensor Platform.

This paper introduces a new variable structure controller designed for depth control of an autonomous underwater sensor platform equipped with a variable buoyancy module. To that end, the prototype linear model is presented, and a finite element-based method is used to estimate one of its parameters, the hull deformation due to pressure. To manage potential internal disturbances like hull deformation or external disturbances like weight changes, a disturbance observer is developed. An analysis of the observer steady-state estimation error in relation to input disturbances and system parameter uncertainties is developed. The locations of the observer poles according to its parameters are also identified. The variable structure controller is developed, keeping energy savings in mind. The proposed controller engages when system dynamics are unfavorable, causing the vehicle to deviate from the desired reference, and disengages when dynamics are favorable, guiding the vehicle toward the target reference. A detailed analysis determines the necessary switching control actions to ensure the system reaches the desired reference. Finally, simulations are run to compare the proposed controller's performance with that of PID-based controllers recently developed in the literature, assessing dynamic response and energy consumption under various operating conditions. Both the VBM- and propeller-actuated vehicles were evaluated. The results demonstrate that the proposed controller achieves an average energy consumption reduction of 22% compared to the next most efficient PID-based controller for the VBM-actuated vehicle, though with some impact on control performance.

The value of error-correcting responses for cognitive assessment in games

Traditional conflict-based cognitive assessment tools are highly behaviorally restrictive, which prevents them from capturing the dynamic nature of human cognition, such as the tendency to make error-correcting responses. The cognitive game Tunnel Runner measures interference control, response inhibition, and response-rule switching in a less restrictive manner than traditional cognitive assessment tools by giving players movement control after an initial response and encouraging error-correcting responses. Nevertheless, error-correcting responses remain unused due to a limited understanding of what they measure and how to use them. To facilitate the use of error-correcting responses to measure and understand human cognition, we developed theoretically-grounded measures of error-correcting responses in Tunnel Runner and assessed whether they reflected the same cognitive functions measured via initial responses. Furthermore, we evaluated the measurement potential of error-correcting responses. We found that initial and error-correcting responses similarly reflected players’ response inhibition and interference control, but not their response-rule switching. Furthermore, combining the two response types increased the reliability of interference control and response inhibition measurements. Lastly, error-correcting responses showed the potential to measure response inhibition on their own. Our results pave the way toward understanding and using post-decision change of mind data for cognitive measurement and other research and application contexts.

Robust switching control of DC-DC converter under dynamic periodic event-triggered mechanism

Robust switching control of DC-DC converter under dynamic periodic event-triggered mechanism

Design of a Switching Controller for Tracking AUVs With an ASV

Design of a Switching Controller for Tracking AUVs With an ASV

Logic-Based Fixed-Time Control for Uncertain Nonlinear Systems With Unknown Control Directions.

The fixed-time control problem is investigated for a class of uncertain nonlinear systems subjected to multiple unknown control directions. The control coefficients of nonlinear systems under consideration are time varying and their signs are not required to be identical. To tackle this challenge, a switching mechanism along with a novel dynamic boundary function is proposed. Utilizing the devised dynamic boundary function, adaptive parameters are introduced into the controller to effectively handle system uncertainties. It is proved that the system output converges to a small neighborhood of the origin in fixed time and the boundedness of all system signals is maintained. Finally, two simulation examples are used to show the validity of the presented switching control strategy.

Optimal Power Flow Algorithm-Based Controller for Efficient Switching Between Grid-Connected and Islanded Modes in Hybrid Microgrids

Optimal Power Flow Algorithm-Based Controller for Efficient Switching Between Grid-Connected and Islanded Modes in Hybrid Microgrids

Audio Signal-Stimulated Multilayered HfOx/TiOy Spiking Neuron Network for Neuromorphic Computing.

As the key hardware of a brain-like chip based on a spiking neuron network (SNN), memristor has attracted more attention due to its similarity with biological neurons and synapses to deal with the audio signal. However, designing stable artificial neurons and synapse devices with a controllable switching pathway to form a hardware network is a challenge. For the first time, we report that artificial neurons and synapses based on multilayered HfOx/TiOy memristor crossbar arrays can be used for the SNN training of audio signals, which display the tunable threshold switching and memory switching characteristics. It is found that tunable volatile and nonvolatile switching from the multilayered HfOx/TiOy memristor is induced by the size-controlled atomic oxygen vacancy pathway, which depends on the atomic sublayer in the multilayered structure. The successful emulation of the biological neuron's integrate-and-fire function can be achieved through the utilization of the tunable threshold switching characteristic. Based on the stable performance of the multilayered HfOx/TiOy neuron and synapse, we constructed a hardware SNN architecture for processing audio signals, which provides a base for the recognition of audio signals through the function of integration and firing. Our design of an atomic conductive pathway by using a multilayered TiOy/HfOx memristor supplies a new method for the construction of an artificial neuron and synapse in the same matrix, which can reduce the cost of integration in an AI chip. The implementation of synaptic functionalities by the hardware of SNNs paves the way for novel neuromorphic computing paradigms in the AI era.

Adaptive fixed-time stabilization for high-order uncertain nonlinear systems with unknown measurement sensitivities

This paper investigates the adaptive fixed-time stabilization problem for a class of uncertain high-order nonlinear systems with unknown measurement sensitivities and unknown control magnitude. Compared to existing practical fixed-time control approaches, our control strategy is capable of driving all states of uncertain high-order systems to the origin within a fixed time, rather than just ensuring their boundedness. Additionally, this study relaxes the restrictions on the nonlinear functions of the system, while overcoming challenges such as unknown control magnitude and unknown measurement sensitivity without prior boundaries. To achieve the control objectives, our control strategy consists of two main steps. Firstly, we divide the initial value of the high-order system into two cases, and construct adaptive controllers separately for each case by adding a power integral technique and backstepping method. Subsequently, the reliance of the stability time of the closed-loop high-order system on the initial value is eliminated by designing an appropriate controller switching mechanism. Finally, we provide a simulation example to validate the effectiveness of our control strategy.

Differential Flatness Based Unmanned Surface Vehicle Control: Planning and Conditional Disturbance-Compensation

To achieve precise control of the symmetrical unmanned surface vehicle (USV) under strong external disturbances, we propose a disturbance estimation and conditional disturbance compensation control (CDCC) scheme. First, the differential flatness method is applied to convert the underactuated model into a fully actuated one, simplifying the controller design. Then, a nonlinear disturbance observer (NDOB) is designed to estimate the lumped disturbance. Subsequently, a continuous disturbance characterization index (CDCI) is proposed, which not only indicates whether the disturbance is beneficial to the system stability but also makes the controller switch smoothly and suppresses the chattering phenomenon greatly. Indicated by the CDCI, the proposed CDCC method can not only utilize the beneficial disturbance but also compensate for the detrimental disturbance, which improves the USV’s control performance under strong external disturbances. Moreover, a trajectory-planning method is designed to generate an obstacle avoidance reference trajectory for the controller. Finally, simulations verify the feasibility of applying the proposed control method to USV.

A homogeneous multi-vehicle cooperative group decision-making method in complicated mixed traffic scenarios

Connected and Automated Vehicles (CAVs) are expected to reshape the transportation system, and cooperative group intelligence of CAVs has great potential for improving transportation efficiency and safety. One challenge for CAV group driving is the decision-making under scenarios mixed with CAV and human-driven vehicles (HDV). Current studies mainly use methods based on single physical rules such as platoon driving or formation switch control, failing to reach a balanced and homogeneous state of optimal efficiency and risk in mixed traffic environments. In addition, most studies focus only on one specific type of scene, lacking the scene adaptability to various surrounding conditions. This paper proposes a homogeneous multi-vehicle cooperative group decision-making method targeting mixed traffic scenarios. A bi-level framework composed of behavior-level and trajectory-level decision-making is established to achieve balanced optimal cooperation. A region-driven behavioral decision mechanism is designed to decompose vehicle actions into a unified form of sequential target regions. Solutions are derived based on Cooperative Driving Safety Field, a risk assessment module inspired by field energy theory. The trajectory-level decision module takes the target regions as input and generates the control quantities of the CAVs through target point selection, conflict reconciliation, and dynamic constraint consideration. Experimental results on 19 various scenarios and continuous traffic flow scenes indicate that the proposed method significantly increases passing efficiency, reduces driving risk, and improves scene adaptability. In addition, experiments on multiple kinds of scenarios including intersections, ramps, bottlenecks, etc. prove that our method can adapt to various road topology structures. Feasibility is also verified through scaled physical platform validations and real-vehicle road tests.

Fixed-time synchronization of interconnected memristive neural networks with energy consumption via switched control

The fixed-time synchronization of time-delay interconnected memristive neural networks is probed in this article. Firstly, according to the conventional controller, a new type of switching controller is proposed, which can complement each other. By utilizing the theory of Lyapunov stability and differential inclusion, it is proved that interconnected memristive neural networks can achieve synchronization within a fixed time under the designed controller. In addition, to control engineering costs, the upper limit of energy consumption, which is produced by the controller from the initial time to the settling-time, is estimated. Finally, numerical examples are provided to verify the validity of the theoretical results.

Efficient electrical control of magnetization switching and ferromagnetic resonance in flexible La0.7Sr0.3MnO3 films

Efficient electrical control of magnetization switching and ferromagnetic resonance in flexible La0.7Sr0.3MnO3 films

Finite-Time Convergence Guidance Law for Hypersonic Morphing Vehicle

Aiming at the interception constraint posed by defensive aircrafts against hypersonic morphing vehicles (HMVs) during the terminal guidance phase, this paper designed a guidance law with the finite-time convergence theory and control allocation methods based on the event-triggered theory, achieving evasion of the defensive aircraft and targeting objectives for a morphing vehicle in the terminal guidance phase. Firstly, this paper established the aircraft motion model; the relative motion relationships between HMV, defensive aircraft, and target; and the control equations for the guidance system. Secondly, a guidance law with finite-time convergence was designed, establishing a controller with the angle between the aircraft–target–defense aircraft triplet as the state variable and lift as the control variable. By ensuring the angle was non-zero, the aircraft maintained a certain relative distance from the defense aircraft, achieving evasion of interception. The delay characteristic of the aircraft’s flight controller was considered, analyzing its delay stability and applying control compensation. Thirdly, a multi-model switching control allocation method based on an event-triggered mechanism was designed. Optimal attack and bank angles were determined based on acceleration control variables, considering different sweep angles. Finally, simulations were conducted to validate the effectiveness and robustness of the designed guidance laws.

Tunable multifunctional terahertz metamaterial device based on metal-dielectric-vanadium dioxide

The Electromagnetically Induced Transparency (EIT) effect in terahertz (THz) metamaterial devices has garnered extensive attention owing to its distinctive advantages in the slow light devices and quantum communication. However, the application of EIT has been constrained by the limitation to a single transparent window and the fixed intensity of the electromagnetic response at the transmission peak after fabrication. To achieve a dual-frequency EIT effect and enable active tunability, this paper presents a tunable multifunction THz metamaterial device based on vanadium dioxide (VO2). The transition of VO2 from the insulator to the metal allows for the active control of EIT and multi-band absorption switching in the THz range. When VO2 is in its dielectric state, two EIT-like windows could be observed with a maximum value of 86.9 % and 71.7 % of the transmission amplitude, respectively. By adjusting the temperature of the VO2, a modulation depth of up to 99 % can be achieved, enabling active control of the EIT-like effect. In addition, active adjustment of group delay of up to 5.47 ps was demonstrated. When VO2 is in the metallic state, the device serves as a tunable multiband absorber, capable of achieving perfect absorption and modulation amplitude of up to 92 %. The results indicated that the presented devices hold significant value for research in the THz range, particularly for applications related to switching and slow light devices. Therefore, the tunable multifunctional THz metamaterial device is of great significance for THz technology.

Mechanochromism and aggregation-induced emission in a fluorene-fumaronitrile-based molecular system: The influence of supramolecular control on donor-acceptor interactions

Effective control and reversible switching of solid-state luminescence in organic molecules are crucial for optoelectronic applications. This study presents a novel molecular system based on fluorene-diphenylfumaronitrile-fluorene (FDF), which exhibits mechanochromism and aggregation-induced emission (AIE). The design utilizes fluorene as the donor, leveraging its high photoluminescent quantum yield, thermal stability, and optimal solubility. The diphenylfumaronitrile moiety, used as the acceptor, is characterized by antiparallel dipoles, which align orthogonally with the chromophore's long axis, promoting effective self-assembly and supramolecular control of interchromophore interactions, in association with the cooperative hydrogen bonding of the amide end-functional groups. FDF demonstrates significant mechanochromic properties, in which mechanical stress induces a reversible shift from greenish-yellow to red emission due to alterations in molecular packing and hydrogen bonding. Additionally, FDF exhibits pronounced AIE behavior in DMF/water mixtures, transitioning from non-emissive in DMF to highly fluorescent upon nanoparticle formation. The investigation reveals that the control over donor-acceptor interactions is critical in modulating these luminescent properties, offering potential applications in stress sensing, bioimaging, and optoelectronic devices. These findings provide deeper insights into the molecular mechanisms underlying mechanochromism and AIE, highlighting the dual-functional nature of FDF and its applicability in advanced materials sciences.

Distributed consensus time‐varying optimization algorithm for multi‐agent systems in predefined time via event‐triggered sliding mode control

This paper proposes a distributed consensus algorithm in predefined time of time‐varying optimization with inequality constrains for multi‐agent systems (MASs) with external disturbances over an undirected graph. Firstly, by utilizing exponential function, a novel criterion with respect to the stability in predefined time is developed for the nonlinear systems. Secondly, a new distributed switching control protocol, which can inhibit the external unbounded disturbances, is piecewise designed to drive the states of agents to the sliding mode surface via the predefined‐time set by users. Subsequently, under the designed event‐triggered controller (ETC), the states of agents achieve consensus in predefined time on the sliding mode surface. Meanwhile, with the help of log barrier function, the consensus states of agents reach the feasible region and converge to the optimal solution in predefined time. Finally, the correctness and availability of the proposed optimization control algorithm are verified by a simulation example.

Analysis and experimental evaluation of an inertial eddy current damper for vibration control

Electromagnetic damping features non-contact operation, easy adjustability, convenient processing, and high energy consumption. Combined with the damping efficiency enhancement effect of the inertial system, it is conducive to further improving its damping effect. This paper proposes an inertial mass damper, named the Inertial Eddy Current Damper (IECD). The proposed IECD has the advantage of adjustability, meaning that the eddy current damping force can be adjusted by regulating the current in the coil. First, the mechanical model of the IECD was proposed through theoretical methods. Secondly, performance tests were conducted to verify the accuracy of the proposed mechanical model. Finally, numerical models of structures employing various applications of the IECD were established to conduct seismic response analysis. The results show that the proposed mechanical model effectively reflects the actual performance of the IECD. When used for energy dissipation and vibration reduction, the IECD demonstrates superior control performance in terms of displacement and velocity compared to the LVD, and the switch control strategy can address the issue of poor acceleration control performance. Combining the IECD with isolation bearings not only further reduces the seismic response of the superstructure but also enhances the safety of the isolation bearings, preventing excessive deformation.

Fixed-time controller for altitude/yaw control of mini-drone based on nonsingular terminal sliding mode: Real-time implementation with uncertainties

To obtain fixed-time stability and finite-time convergence of altitude and yaw motions of a mini-quadrotor subjected to perturbations, this paper proposes a new altitude/yaw motion finite-time tracking control. First, a nonsingular terminal sliding manifold is proposed for both subsystems whose states converge to their desired values in finite-time. To address the uncertainties of the system, a robust fixed-time switching controller is proposed whose stability is proposed and its settling-time depends only on control of the parameters and not the initial conditions. The validation of the proposed approach is presented based on a real mini-quadrotor.

State Feedback Via Judicious Pole Placement and Linear Quadratic Regulator – Application to Rotary Inverted Pendulum

In the control system regulatory concept, placing closed loop poles too far from the origin in the stability region produces fast regulation time but requires huge forcing energy as a trade-off. As such, stabilizing an unstable system with minimum energy is needed, though this presents a challenge to the designer. At the design phase, the designer may ponder the optimized energy while compromising the possibility of catastrophic stabilization phenomena due to minimal forcing thrust towards the poles. In this manuscript, a simple Linear Quadratic Regulator (LQR) is proposed as an alternative to full state feedback (FSF) with judicious pole placement. The efficacy of both approaches was observed by exploiting a Rotary Inverted Pendulum (RIP) as a testbed. Beforehand, the RIP system dynamics were developed in the time domain. RIP is an under-actuated mechanical system that is inherently nonlinear and unstable. The main control objectives of RIP are swing-up control, stabilization control, switching control, and trajectory control. The methodology involved the appearance of weighted matrices that were necessary for the minimum cost function. The Riccati and Lyapunov criteria are also exploited to facilitate design. The result shows the comparative transient performances of the two approaches, where the LQR outperforms the FSF in many aspects.