9 research outputs found

    Adaptive Sliding Mode Control of Mobile Manipulators with Markovian Switching Joints

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    The hybrid joints of manipulators can be switched to either active (actuated) or passive (underactuated) mode as needed. Consider the property of hybrid joints, the system switches stochastically between active and passive systems, and the dynamics of the jump system cannot stay on each trajectory errors region of subsystems forever; therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this paper, we consider stochastic stability and sliding mode control for mobile manipulators using stochastic jumps switching joints. Adaptive parameter techniques are adopted to cope with the effect of Markovian switching and nonlinear dynamics uncertainty and follow the desired trajectory for wheeled mobile manipulators. The resulting closed-loop system is bounded in probability and the effect due to the external disturbance on the tracking errors can be attenuated to any preassigned level. It has been shown that the adaptive control problem for the Markovian jump nonlinear systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. Finally, a numerical example is given to show the potential of the proposed techniques

    Optimal Energy Consumption for Mobile Manipulators Executing Door-Opening Task

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    As a substitute for humans, the mobile manipulator has become increasingly vital for on-site rescues at Nuclear Power Plants (NPPs) in recent years. The high energy efficiency of the mobile manipulator when executing specific rescue tasks is of great importance for the mobile manipulator. This paper focuses on the energy consumption of a robot executing the door-opening task, in a scenario mimicking an NPP rescue. We present an energy consumption optimization scheme to determine the optimal base position and joint motion of the manipulator. We developed a two-step procedure to solve the optimization problem, taking the quadric terms of the joint torques as the objective function. Firstly, the rotational motion of the door is parameterized by using piecewise fifth-order polynomials, and the parameters of the polynomials are optimized by minimizing the joint torques at the specified base position using the Quasi-Newton method. Second, the global optimal movement of the manipulator for executing the door-opening task is acquired by means of searching a grid for feasible base positions. Comprehensive door-opening experiments using a mobile manipulator platform were conducted. The effectiveness of the proposed method has been demonstrated by the results of physical experiments

    High-Performance Zwitterionic Organohydrogel Fiber in Bioelectronics for Monitoring Bioinformation

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    Bioinformation plays an imperative role in day-to-day life. Wearable bioelectronics are important for sensing bioinformation in real-time and conductive hydrogel fibers are a key component in next generation wearable bioelectronics. However, current conductive hydrogel fibers have remarkable disadvantages such as insufficient conductivity, stability, and bioinformation sensing ability. Here, we report the synthesis of a zwitterionic organohydrogel (ZOH) fiber by the combination of the mold method and solvent replacement strategy. The ZOH fiber shows transparency (92.1%), stretchability (905.8%), long-term stability, anti-freezing ability (−35–60 °C), and low light transmission loss (0.17 dB/cm). Then, we integrate the ZOH fiber into fabric for use as a bioinformation sensor, the results prove its capability as a bioinformation monitor, monitoring information such as motion and bioelectric signals. In addition, the potential of the ZOH fiber in optogenetic applications is also confirmed

    <i>In Situ</i> Cas12a-Based Allele-Specific PCR for Imaging Single-Nucleotide Variations in Foodborne Pathogenic Bacteria

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    In situ profiling of single-nucleotide variations (SNVs) can elucidate drug-resistant genotypes with single-cell resolution. The capacity to directly “see” genetic information is crucial for investigating the relationship between mutated genes and phenotypes. Fluorescence in situ hybridization serves as a canonical tool for genetic imaging; however, it cannot detect subtle sequence alteration including SNVs. Herein, we develop an in situ Cas12a-based amplification refractory mutation system-PCR (ARMS-PCR) method that allows the visualization of SNVs related to quinolone resistance inside cells. The capacity of discriminating SNVs is enhanced by incorporating optimized mismatched bases in the allele-specific primers, thus allowing to specifically amplify quinolone-resistant related genes. After in situ ARMS-PCR, we employed a modified Cas12a/CRISPR RNA to tag the amplicon, thereby enabling specific binding of fluorophore-labeled DNA probes. The method allows to precisely quantify quinolone-resistant Salmonella enterica in the bacterial mixture. Utilizing this method, we investigated the survival competition capacity of quinolone-resistant and quinolone-sensitive bacteria toward antimicrobial peptides and indicated the enrichment of quinolone-resistant bacteria under colistin sulfate stress. The in situ Cas12a-based ARMS-PCR method holds the potential for profiling cellular phenotypes and gene regulation with single-nucleotide resolution at the single-cell level
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