Switching System Research Articles

Arduino-based Automatic Light Switching System

This article focuses on the problem of high power consumption caused by long working hours of lights, and designs an automatic light switch system based on the number of people to achieve energy-saving effects. After experiencing the process of selecting hardware, designing circuits, writing programs, structural design, 3D modeling, 3D printing processing, assembly, etc., an automatic light on/off system has been designed, which is low-cost and can achieve automatic light on/off based on Arduino microcontroller technology, playing a role in saving electricity to a certain extent.

Tracking Control of Quadrotor with Intermittent Target Measurements: A Stochastic Switched Systems Approach

This paper is devoted to the investigation of target tracking control of quadrotor with intermittent measurements, i.e., the measurements of target position are not continuously available. A stochastic switched systems approach is utilized to formulate such a tracking process of quadrotor by splitting it into two modes according to whether the measurements are available. The mode switching of the underlying system is subject to a Markov process to account for the inherent non-memory randomness of the dwell time of each mode, in contrast with the existing studies that impractically require the duration of the measurements to be greater than a given constant. The stability criteria for the underlying system are derived, upon which a switched controller is designed for the quadrotor position control, rather than the determination of the bounds of the dwell time for given pre-designed controllers in each mode. Simulations are presented to demonstrate the effectiveness of the developed theoretical results and the superiority of the designed switched controller for tracking control of quadrotor with intermittent target measurements.

A new switching time optimization technique for multi-switching systems

<p style='text-indent:20px;'>For a multi-switching system, it consists of multiple parallel switching systems. The optimal control problem controlled by a multi-switching system is to determine the optimal time sequence for each of the parallel switching systems. The time-scaling transformation is a well-known switching time optimization approach which has been widely used in various problem settings. However, the time-scaling transformation requires that these parallel switching systems have the same number of subsystems and are designed to switch simultaneously. Thus, it is not applicable for solving optimal control problems of general multi-switching systems. This paper presents a new technique for optimizing the switching times of multi-switching systems.</p>

Dynamic Event-triggered Adaptive Control for Uncertain Nonlinear Switched Systems Based on MDADT Method

Dynamic Event-triggered Adaptive Control for Uncertain Nonlinear Switched Systems Based on MDADT Method

Deep neural network based adaptive learning for switched systems

In this paper, we present a deep neural network based adaptive learning (DNN-AL) approach for switched systems. Currently, deep neural network based methods are actively developed for learning governing equations in unknown dynamic systems. However, their efficiency can degenerate for switching systems, where structural changes exist at discrete time instants. In this new DNN-AL strategy, observed datasets are adaptively decomposed into subsets, such that no structural change within each subset. During the adaptive procedures, DNNs are hierarchically constructed, and unknown switching time instants are gradually identified. Especially, network parameters at previous iteration steps are reused to initialize networks for the later iteration steps, which provides efficient training procedures for the DNNs. For the DNNs obtained through our DNN-AL, the bounds of the prediction error are established. Numerical studies are conducted to demonstrate the efficiency of DNN-AL.

Mode Switching Control for Drag-Free Satellite Based on Region of Attraction

This paper aims to propose a switching rule to improve the efficiency and stability of the mode switching process for the drag-free satellite. The switching rules will ensure the stability of the different controllers during the switching process. Unlike traditional satellite switching control, the inner loop and the outer loop of the drag-free satellite are strongly coupled. The drag-free satellite not only needs to consider the controller design in the inner loop but also the controller design of the outer loop. In the outer loop, a Proportion Integration Differentiation control method is adopted to design the controller. In the inner loop, considering the release error effect of the test mass, a nonlinear sliding-mode control is employed as a controller before the mode switch. The H∞ mixed-sensitivity controller, to improve the robustness of the system and solve the problem of controller saturation, is designed after the mode switch. In the stability analysis of the switching system, the piecewise continuous Lyapunov function method is adopted. The region of attraction, which is used as the switching rule, is calculated based on the sum of squares. The obtained results demonstrate that the proposed switching rule satisfies the control accuracy and system stability.

Output Feedback Control for Switched Systems With Unmatched Uncertainties Based on the Common Robust Integral Sliding Mode

Output Feedback Control for Switched Systems With Unmatched Uncertainties Based on the Common Robust Integral Sliding Mode

Implementation of proportional-integral-plus control to a high redundancy actuator for a track switch system

The railway network is equipped with track switches that enable trains to move from one track to another. Existing track switch actuation is performed in open loop. Closed-loop control and redundant actuation can be applied to provide an opportunity to enhance the reliability of the railway track switch system. This paper looks at the control design development applied to a laboratory scale demonstrator of a redundant actuation concept. Open-loop control is first applied to this High Redundancy Actuation (HRA) track switch lab prototyping. According to the open-loop experimental input and output, a simplified linear model of the system is identified and estimated. A model-based Proportional-Integral-Plus (PIP) controller is then developed and tested, including nominal control and fault tolerant control. The results show that the proposed control method can meet the actuation requirements of the track switch system with high redundancy actuation. Another innovation of this paper is direct model-based control design, and this small HRA prototyping provides valuable insight into the future full-scale system.

A two-strain model of infectious disease spread with asymmetric temporary immunity periods and partial cross-immunity.

We introduce a two-strain model with asymmetric temporary immunity periods and partial cross-immunity. We derive explicit conditions for competitive exclusion and coexistence of the strains depending on the strain-specific basic reproduction numbers, temporary immunity periods, and degree of cross-immunity. The results of our bifurcation analysis suggest that, even when two strains share similar basic reproduction numbers and other epidemiological parameters, a disparity in temporary immunity periods and partial or complete cross-immunity can provide a significant competitive advantage. To analyze the dynamics, we introduce a quasi-steady state reduced model which assumes the original strain remains at its endemic steady state. We completely analyze the resulting reduced planar hybrid switching system using linear stability analysis, planar phase-plane analysis, and the Bendixson-Dulac criterion. We validate both the full and reduced models with COVID-19 incidence data, focusing on the Delta (B.1.617.2), Omicron (B.1.1.529), and Kraken (XBB.1.5) variants. These numerical studies suggest that, while early novel strains of COVID-19 had a tendency toward dramatic takeovers and extinction of ancestral strains, more recent strains have the capacity for co-existence.

Modeling the Impact of Route Recommendations in Road Traffic

In this work, effects of real-time route recommendations between two alternative routes are analyzed. The aim is to assess the consequences of route planner applications (apps) on road congestion. For this purpose, the considered model takes the form of a state-dependent switching system that describes a supply-demand mechanism, based on established macroscopic traffic flow models. Through a comprehensive stability analysis of the system, with an emphasis on the dependence on the system parameters (such as road capacities, critical densities, traffic demand), it is shown that real-time recommendations can cause congestion in the network and failure to satisfy user demand.

Simulation of Sequential Turbocharging Switching Control System for Low Speed Diesel Engines

In order to study the sequential turbocharging switching process of low-speed diesel engine, this paper uses GT-power software to establish a simulation model of sequential turbocharging low-speed diesel engine. It is enhanced and improved into a model of a sequential supercharged diesel engine. Modules such as load, governor, valve control, and surge margin are set up in the simulation model. Then parameters such as switching speed, valve opening time and response time are set in the model. Through the above preparations, the thesis has carried out the simulation calculation of the sequential supercharging transient switching process and verified the rationality of the setting parameters and the accuracy of the module setting. This provides a certain reference for the valve control strategy of the sequential supercharging switching system of low-speed diesel engines.

A Redundancy Switching System of Airport Weather Radar Based on Domestic FPGA

A Redundancy Switching System of Airport Weather Radar Based on Domestic FPGA

Quantifying Impact on Safety from Cyber-Attacks on Cyber-Physical Systems

We propose a novel framework for modeling attack scenarios in cyber-physical control systems: we represent a cyber-physical system as a constrained switching system, where a single model embeds the dynamics of the physical process, the attack patterns, and the attack detection schemes. We show that this is compatible with established results in hybrid automata, namely, constrained switching linear systems. The proposed attack modeling approach admits a large class of non-deterministic attack policies and enables the characterization of system safety as an asymptotic property. By calculating the maximal safe set, the resulting new impact metrics intuitively quantify the degradation of safety and the impact of cyber attacks on the safety properties of the system under attack. We showcase our results via an illustrative example.

Retracted: Accelerated Iterative Learning Control for Linear Discrete Time Invariant Switched Systems

Retracted: Accelerated Iterative Learning Control for Linear Discrete Time Invariant Switched Systems

Secure Event-Triggered Vehicle Platooning Control with Proportional Integral Observers under Denial of Service Attacks

This paper addresses the problem of secure event-triggered platooning control for multiple automated vehicles where the vehicle-to-vehicle communication network suffers from limited resource constraint and denial-of-service (DoS) attacks. A novel distributed proportional-integral observer (PIO) with a forgetting integral term is first proposed for each platoon vehicle to estimate its full state. In light of the PIOs, a distributed dynamic event-triggered platoon controller is then constructed under a bandwidth-sensitive dynamic event-triggered mechanism (DETM). Furthermore, a switching system model is presented to overcome the challenge of complex time series coming from DETM and DoS attacks. A sufficient co-design condition is derived to receive the desired controller gain. Finally, an illustrative example is provided to validate the derived main results.

Closed-Loop Kinematic and Indirect Force Control of a Cable-Driven Knee Exoskeleton: A Lyapunov-Based Switched Systems Approach

Closed-Loop Kinematic and Indirect Force Control of a Cable-Driven Knee Exoskeleton: A Lyapunov-Based Switched Systems Approach

Distributed output-feedback resilient fault-tolerant tracking control of uncertain heterogeneous linear MASs under directed topologies and DoS attacks

This paper presents a distributed output-feedback resilient tracking fault-tolerant control (FTC) protocol for uncertain heterogeneous linear multi-agent systems (MASs) with directed topologies and DoS attacks. The uncertainty, actuator fault and nonidenticality in agents and DoS attacks in directed communication topologies, make it a challenging task to achieve distributed output-feedback FTC objective. In order to solve this difficulty, a hierarchical framework is introduced. The basic idea is to design distributed resilient observers under directed topologies and DoS attacks. By virtue of switching systems theory, the upper bounds of attack frequency and attack duration are obtained. Based on neural networks approximation technique and model reference tracking method, a novel output-feedback FTC scheme is proposed. Lastly, simulation example indicates the validity of the proposed method.

Dynamic weight routing and optical-code algorithm based on SDN

Optical transport networks are evolving towards multi-granularity switching and software management but require that the architecture of the existing control plane be adapted to multi-service and network management requirements. So a dynamic weighting algorithm based on optical code resources and the matching degree between service request and channel is proposed for a multi-granularity optical switching system. In which, Software Defined Networking (SDN) controller collects network resource information in real time, dynamically changes the weight of each path and use it for path calculation, provides a more matched path on the premise of load balancing, and combines its channel matching weights for resource allocation. The simulation results show that the multi-granularity switching system with the proposed algorithm can reduce the generation of optical code fragments and improve resource utilization effectively. In the end of the paper, the optical code routing algorithms are simulated and implemented, and their performances are compared and analyzed. The simulation results show that the blocking rate of the matching algorithm on the NSFNET network is reduced by an average of 4% compared with the traditional algorithm, and the resource utilization of the optical code is improved by 9%.

Smart Switching Power Supply System for Evaporative Air Coolers

The energy consumption by residential air conditioners could cost about half of the total energy consumption of the building. A combination of conventional and renewable energy is still an emerging technology. Therefore, using solar photovoltaic panels to provide electricity to the air conditioner is a substantial application. This research shows the possibility of using photovoltaic panels as a power source for air conditioners in a sequence exchange with the conventional grid. A smart switching system has been offered to organize the power supply between the grid and solar panels. The photovoltaic panels have been connected to the conditioner across a power inverter module for adopting a reliable and accurate quantity of power supply to the conditioner unit. The smart switching system provides an intelligent connection between the solar power source and the grid, ensuring an uninterrupted electricity supply between the two power sources.

Improving cooperativity of transcription activators by oligomerization domains in mammalian cells

Cooperative activation is critical for the applications of synthetic biology in mammalian cells. In this study, we have developed cooperative transcription factor by fusing oligomerization domain in mammalian cells. Firstly, we demonstrated that two oligomerized domains (CI434 and CI) successfully improved transcription factor cooperativity in bacterial cells but failed to increase cooperativity in mammalian cells, possibly because the additional mammalian activation domain disrupted their oligomerization capability. Therefore, we chose a different type of oligomerized domain (CarHC), whose ability to oligomerize is not dependent on its C-terminal domains, to fuse with a transcription factor (RpaR) and activation domain (VTR3), forming a potential cooperative transcription activator RpaR-CarH-VTR3 for mammalian regulatory systems. Compared with RpaR-VTR3, the cooperativity of RpaR-CarH-VTR3 was significantly improved with higher Hill coefficient and a narrower input range in the inducible switch system in mammalian cells. Moreover, a mathematical model based on statistical mechanics model was developed and the simulation results supported the hypothesis that the tetramer of the CarH domain in mammalian cells was the reason for the cooperative capacity of RpaR-CarH-VTR3.