Multi-mode control based on HSIC for double pendulum robot

Double pendulum robot has four equilibrium points: Down-Down, Down-Up, Up-Down, and Up-Up. Define the transfer control from one equilibrium point to another equilibrium point as acrobatic action of DPR, and there are total of 20 acrobatic actions. This paper proposes the multi-mode control algorithm based on Human Simulated Intelligent Control theory for the realization process of those acrobatic actions, which has the structure of multi sub-controllers and multi control modes. As an example, the acrobatic action from Down-Up to Up-Down is realized in simulation and real-time experiments, and the results demonstrate the effectiveness of the proposed algorithm

The control strength quantification analysis of outer pendulum rod for double inverted pendulum

Due to the complexity of the dynamics characteristics of an inverted pendulum, and the problem that the linearization analyze method cannot satisfy the controlling requirement, a nonlinear dynamics analyze method was proposed. Through decoupling the dynamics model of a double inverted pendulum, the outer pendulum rod motion equation was derived. And then, aiming at the control strength function of outer pendulum rod, the qualitative and quantitative relationship between spatial position of pendulum rod and the control strength of outer rod, and the quantification relationship between dynamics parameters and the control strength of outer rod were separately analyzed. And the simulation verified the correctness of the analysis

Titanium-mediated reductive cross-coupling reactions of imines with terminal alkynes: An efficient route for the synthesis of stereodefined allylic amines

Low-valency titanium species, generated in situ by using Ti(OiPr)4/2 c-C5H9MgCl reagent, react with imines to give a titanium-imine complex that can couple with terminal alkynes to provide azatitanacyclopentenes with excellent regioselectivity. Stereodefined allylic amines are obtained in good yields after hydrolysis or iodonolysis of the corresponding azatitanacyclopentenes. When ethynylcyclopropane is used as the coupling partner to react with imines in this reaction, the initially generated allylic amine undergoes an unexpected 1,3-amino migration on silica gel during the column chromatography

High Selective Separation of Flavonoids based on Crosslinked Chitosan Resin Grafted by Quercetin

In this study, crosslinked chitosan resin grafted by quercetin (QCCR) was used as a novel adsorbent to separate flavonoids. Functional quercetin groups were introduced to the adsorbent matrix, and the hydrophobic interaction occurred when these functional groups in the adsorbent approached the adsorbate with the same ring structure, which enhanced the adsorption selectivity towards flavonoids. The hydrophobic interaction played an important role in the selective adsorption. Atomic force microscopy provided intuitively the spatial conformation and the interactions between flavonoids and QCCR at the molecular level. The influences of functional groups of synthesized adsorbents on the adsorption selectivity and the optimum conditions were investigated in detail. QCCR was considered as an alternative material for obtaining the bioactive flavonoid compounds with high concentration

State of health estimation of LIB based on discharge section with multi-model combined

Accurate estimation of a battery's state of health (SOH) is essential in battery management systems (BMS). This study considers a complete analysis of combining incremental capacity (IC), differential thermal voltammetry (DTV), and differential temperature (DT) for SOH prediction in cases of discharge. Initially, the IC, DTV, and DT curves were derived from the current, voltage, and temperature datasets, and these curves underwent smoothing through the application of Lowess and Gaussian techniques. Subsequently, discerning healthy features were identified within the domains where the curve exhibited substantial phase transitions. Utilizing Pearson correlation analysis, features exhibiting the utmost correlation with battery capacity degradation were singled out. Finally, the state-of-health (SOH) prediction model was constructed using a bidirectional long short-term memory (BILSTM) neural network. Two datasets were used to validate the model, and the experimental results demonstrated that the SOH prediction had a root mean square error (RMSE) below 1.2% and mean absolute error (MAE) below 1%, which verified the feasibility and accuracy. This approach quantifies the internal electrochemical reactions of a battery using externally measured data, further enabling early SOH predictions

The impact of aerosol–radiation interactions on the effectiveness of emission control measures

Temporary emission control measures in Beijing and surrounding regions have become a prevailing practice to ensure good air quality for major events (e.g. the Asia-Pacific Economic Cooperation (APEC) Summit on 5–11 November 2014) and to mitigate the severity of coming pollution episodes. Since PM _2.5 affects meteorology via aerosol–meteorology interactions, a question arises how these interactions may impact the response of PM _2.5 to emission reductions and thus the effectiveness of emission control measures. Here we use the coupled meteorology-chemistry model WRF-Chem to investigate this issue with focus on aerosol–radiation interactions (ARI) for the APEC week and three more polluted episodes over North China. We find a quadratic relationship between PM _2.5 concentration changes due to emission reductions and PM _2.5 levels, instead of an approximately linear response in the absence of ARI. The ARI effects could only change the effectiveness of emission control by 6.7% during APEC in Beijing, but reach 21.9% under more polluted conditions. Our results reveal that ARI can strongly affect the attribution of PM _2.5 variability to emission changes and meteorology, and is thus important for assessing the effectiveness of emission control measures