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A wideband high-gain metasurface (MTS) antenna array loaded with substrate integrated cavity (SIC) is proposed. Benefiting from the wideband property of MTS-based structures and the high gain property of SIC structure, a novel wideband high-gain MTS antenna element is designed. By utilizing the slot mode, TM10 mode of the MTS, and the TM121 mode of the SIC, the cavity-backed slot-coupled MTS radiation mechanism and the high-order mode (HOM) SIC radiation mechanism are combined to realize wideband and high-gain radiation. A parametric study is conducted to investigate the design process. The simulated results of the proposed antenna element present an overlaid bandwidth of 40.3% from 7.43 to 11.18 GHz and a maximum gain of 10.40 dBi at 11.00 GHz. On this basis, a planar $4\times 4$ array fed by a two-layer feeding network based on substrate integrated waveguide (SIW) power divider is designed and fabricated. The measured results indicate that the proposed array has an overlaid bandwidth of 34.8% from 7.95 to 11.30 GHz, a measured gain of up to 19.90 dBi, and a maximum aperture efficiency of 80.0%.

Soft manipulators, a relatively novel class of robots, are increasingly prevalent in the field of robotics. Due to the material nonlinearity and the absence of links and joints which are typically used to derive their kinematics and dynamics, the exact modeling and effective control frameworks of such soft robots are much more difficult than the traditional rigid counterparts. To achieve global control of the end-effector position of the soft manipulator actuated by cables, this work proposes a hybrid control strategy by unifying the piecewise linear strain Cosserat model and radial basis function neural network to approximate the Jacobian matrix of any end-effector position in the whole workspace, and then designs a global control scheme based on the approximation of the Jacobian matrix. The theoretical convergence proof and experimental validation are provided for the designed global controller. The results corroborate that the proposed control strategy has excellent accuracy and robustness in tracking desired time-varying trajectories through different experiments.

Micro-milling is employed for the precise machining of small components with intricate characteristics, and the quality of micro-milling is significantly influenced by the uncertainty surrounding tool wear. Monitoring the wear status of micro-milling tools holds great significance in enhancing machining efficiency and sustainability. In this work, wear monitoring of micro-milling tools method was proposed based on Improved Siamese Neural Network. The Improved Siamese Neural Network used two different global feature extraction networks. The features were input into the t improved Siamese neural network model for similarity score calculation and anomaly detection, which improves the detection accuracy of the abnormal state of micro-milling tool wear. In addition, Generative Adversarial Network (GAN) data augmentation is used to address the issue of abnormal data imbalance during the data preparation stage. The experiments show that the classification accuracy and the precision of the model on the micro-milling tool wear dataset is 92.15% and 93.32% respectively, indicating that the model has good stability and effectiveness.

Model-based control for continuum robots is often based on the piecewise constant curvature (PCC) assumption. However, the actual physical motions of continuum robots deviate significantly from this assumption, posing challenges to achieving the desired stability and accuracy in control. In this article, a real-time model-based data-driven controller is designed to enhance the precision and stability of continuum robots. An algorithm is designed to construct the static model of the cable-driven continuum robots. A real-time data-based kinematics model is formulated based on the static model, and the multistate motions of the robot are described in this model. A nonlinear control strategy is proposed based on the data-based kinematics model. Validation through simulations and experiments demonstrates the method's robust stability and impressive precision, achieving a positioning accuracy of 0.0318 mm and a tracking accuracy of 0.0434 mm. This article provides a general paradigm for model-based control of continuum robots, which is crucial to the advancement of this industry.

ABSTRACTPrior research on catch-up strategies often provides insights from the technology-related perspective and ignores some non-technological factors. Through the multi-case study of China’s smartphone industry, we develop a theoretical framework explaining how latecomer firms catch up through diverse strategic choices. We identify two strategic paths that latecomer firms follow to catch up and surpass the incumbents. One path is to explore new business opportunities via deep market insights and then combine them with building up product technologies. Another path is from product technology build-up to market insights exploration. Firms following this path usually start with building up essential technologies and act as fast followers for new market insights. Then, as they continue developing their technological strengths, these firms devote efforts to improving their ability to capture new market insights. This study challenges the ‘first imitation, then innovation model’ discussed in the literature and shows that latecomer firms can pursue cutting-edge innovations in their early activities. The research also shows that, unlike previous studies, the technology build-up is not the only path to help latecomers catch up and challenge incumbent leaders.

The effects of process parameters on the densification, microstructures, and mechanical properties, as well as the temperature dependence of the mechanical properties, of a NiCoCr medium-entropy alloy fabricated with selective laser melting were studied. The results indicate that the microstructures and mechanical properties are not linearly related to the volume energy density (VED) but are affected by the scanning speed and laser power. The optimal process parameters are identified as a scanning speed of 800 mm/s and a laser power of 250 W, while the VED is only 57 J/mm3lower than the highest value of 68 J/mm3. The yield strengths of the optimal sample are ∼819, ∼709 and ∼618 MPa at 77, 200, and 293 K, respectively. The temperature dependence of the mechanical properties is determined and verified by the experimental results.

Non-uniform sampling two-dimensional convolution (NUSC) maps spatially sampling data with irregular distribution to a regular grid by convolution. As the data scale and growth rate continue to increase, accelerating NUSC with the heterogeneous computing platform is a feasible way. However, the complex hardware architecture and storage hierarchy of the heterogeneous computing platform poses a challenge to programming and performance tuning. Therefore, this paper proposes a heterogeneous parallel programming model and runtime framework named AutoNUSC. For the programming difficulties of NUSC in heterogeneous computing environments, AutoNUSC abstracts and encapsulates the parallel execution process of NUSC. Task scheduling, data division, node communication, fault-tolerant recovery, and other parallelization tasks are managed by AutoNUSC. For the performance tuning issues of NUSC, this paper implements performance optimization strategies for AutoNUSC, including vectorization, memory access optimization, data reuse, etc. The experiments show that AutoNUSC effectively reduces the workload of users in developing NUSC applications in heterogeneous computing environments. Performance acceleration of up to 339 times is achieved within a single node compared to the serial program. AutoNUSC can efficiently perform task scheduling and fault-tolerant recovery across multiple nodes, with desirable scalability and robustness.

•We mined 12,880 articles related to biofertilizers in this study.•Biofertilizer research can be categorized into three phases.•Developing countries are keenly interested in the research of biofertilizers.•Biofertilizers provide nutrients, regulate crop growth, and improve soil conditions.•Pseudomonas, Azotobacter and Bacillus are the major microorganisms for biofertilizer.

In this article, the degradation of 234 nm AlGaN-based far-UVC light-emitting diodes (LEDs) under constant current stress is studied in-depth by the combination of optical and electrical characterization with an in situ testing method. In addition, the relationship between the degradation and the variation of defects is established by deep-level transient spectroscopy (DLTS) testing. In combination with the capacitance–voltage characteristics, it is found that the significant degradation of optical power is mainly related to the transition of hole trap “ ${h}_{{1}}$ ” with the energy level of Ev + (0.201–0.243 eV) to “ ${h}_{{2}}$ ” with the energy level of Ev + 0.624 eV in the active region. The transition is described as the separation of Mg from Mg $_{\mathbf {Ga}}$ to generate the VGa and combined with other defects to form the VGa-related complex defects. These complex defects as non-radiative recombination centers could contribute to the reduction of injection efficiency and directly lead to the reduction of optical power. On the n-side, the increased concentration of electron trap “ ${e}_{{2}}$ ” indicates that the crystal quality of material deteriorates further. The leakage current rises slightly, which is primarily due to the increase in the concentration of hole trap “ ${h}_{{3}}$ ” with deeper energy levels. This study about the defects behavior of 234 nm LED may provide a reference for the fabrication of AlGaN far-UVC LED with higher reliability.

The mechanized water direct seeding technology of rice has the advantages of saving time and labor, saving cost and increasing yield. The existing wheeled tractor direct seeding operation in paddy field mainly has technical problems such as large wheel rut, floating stubble blockage, and high-speed operation backwater, resulting in the quality of seedbed is not up to standard and cannot meet the requirements of direct seeding operation in paddy field. In view of the above problems, a high-speed rice seedbed preparation machine which can be matched with a wheeled tractor was developed. The overall scheme of the machine was put forward, and the structure design of key devices such as rut coverage, stubble burying and ditching was carried out. The corresponding motion analysis and simulation were carried out. Finally, the bench test and field test were carried out. The test results show that the designed operating machine can complete the rutting coverage, stubble burying, ditching and other operations at one time. The coverage rate of wheel track is 98.52%. The stubble rate was 98.89%; the ditch type of the ditching operation is complete and the ditch is clean. The components of the designed machine meet the design requirements, and the operation effect can better meet the operation requirements of high-speed rice seedbed preparation.

The accuracy of simulation parameters for spinach sowing process was enhanced by establishing the seed simulation model based on the intrinsic parameters of spinach seeds using the Hertz–Mindlin model. Calibration of simulation parameters between spinach seeds and contact materials (ABS resins and stainless steel) was performed using free-fall collision method, inclined plane sliding method, and inclined plane rolling method. The results indicated: coefficients of restitution, static friction coefficients, and rolling friction coefficients between spinach and ABS resins were 0.310, 0.467 and 0.045, respectively. Coefficients of restitution, static friction coefficients and rolling friction coefficients between spinach and stainless steel were 0.346, 0.505 and 0.047, respectively. Considering inter-seed contact parameters, a study was conducted using the relative error between measured repose angle and simulated repose angle as the indicator. This involved steepest ascent experiment and three-factor five-level rotational combined design experiment with the optimisation goal of minimising relative error. Through optimal analysis of test data, the following results were obtained: coefficients of restitution, static friction coefficients, and rolling friction coefficients between spinach seeds were found to be 0.47, 0.37 and 0.04, respectively. Calibration results were validated through sowing verification experiments, demonstrating that the qualified rate, multiple rate and missing rate of both simulation and actual tests were less than 5.8%, verifying the reliability of the calibration results. The research findings can serve as a theoretical reference for the design and simulation optimisation of spinach sowing devices.

Change detection (CD) aims to identify differences in the same scene at different times. With the increasing amount of hyperspectral images (HSIs), more and more CD techniques use HSIs as the raw data. HSIs often contain redundant bands, where only a few are crucial for CD while others may be detrimental. However, most existing HSI-CD methods extract features directly from full-dimensional HSIs, leading to a degradation of feature discrimination. To tackle this issue, in this article, we propose an end-to-end HSI CD network based on band selection (ECDBS), unlocking the potential synergy between band selection (BS) and CD. The network compromises a deep learning-based BS module and cascaded band-specific spatial attention (BSA) blocks. The BS module selectively retains bands favorable to CD according to the importance of the bands measured based on band correlation. The BSA block tailors the feature extraction strategy for each band based on its feature distribution, allowing extracting sufficient features from each band. Experimental evaluations were conducted on three widely used HSI-CD datasets, demonstrating the effectiveness and superiority of our proposed method over other state-of-the-art techniques.

In this article, the leader-following consensus problem for multiagent systems (MASs) is considered. Each agent is assumed to be modeled by a linear multi-input system. A novel (generalized homogeneous) consensus control protocol is designed under the assumption that there are some uncertainties in the dynamic of the leader. Some conditions (linear matrix inequalities) are derived to select the control parameters in order to ensure the input-to-state stability and global finite-time stability of the consensus errors with desired homogeneity degrees. Some simulations are performed to illustrate the obtained results.

BackgroundEpigenetics makes substantial contribution to the aetiology of autism spectrum disorder (ASD) and may harbour a unique opportunity to prevent the development of ASD. We aimed to identify novel epigenetic genes involved in ASD aetiology.MethodsTrio-based whole exome sequencing was conducted on ASD families. Genome editing technique was used to knock out the candidate causal gene in a relevant cell line. ATAC-seq, ChIP-seq and RNA-seq were performed to investigate the functional impact of knockout (KO) or mutation in the candidate gene.ResultsWe identified a novel candidate gene NASP(nuclear autoantigenic sperm protein) for epigenetic dysregulation in ASD in a Chinese nuclear family including one proband with autism and comorbid atopic disease. The de novo likely gene disruptive variant tNASP(Q289X) subjects the expression of tNASPto nonsense-mediated decay. tNASPKO increases chromatin accessibility, promotes the active promoter state of genes enriched in synaptic signalling and leads to upregulated expression of genes in the neural signalling and immune signalling pathways. Compared with wild-type tNASP, tNASP(Q289X) enhances chromatin accessibility of the genes with enriched expression in the brain. RNA-seq revealed that genes involved in neural and immune signalling are affected by the tNASPmutation, consistent with the phenotypic impact and molecular effects of nasp-1 mutations in Caenorhabditis elegans. Two additional patients with ASD were found carrying deletion or deleterious mutation in the NASPgene.ConclusionWe identified novel epigenetic mechanisms mediated by tNASPwhich may contribute to the pathogenesis of ASD and its immune comorbidity.

The acquisition of wide geophysical data of vast oceans by satellites can be impeded by clouds, which may result in gaps in the data acquired in the infrared and visual bands, such as sea surface temperature (SST) data, leading to limited data usage. To address this issue, we proposed a general and robust method, named the empirical function (EF) method, which involves expanding an ocean field with space-time-separation functions and determining the functions by minimizing the expansion’s residual on the observation data while considering the prior-knowledge constraint that an ocean field varies smoothly in space and time. To test the effectiveness of the EF method, we applied it to reconstruct the 14-year cloud-free SST data in the Gulf Stream region spanning from 24.5°N to 44°N and from 82.5°W to 54.5°W. The original data consist of the 0.025 $^{\circ }\,\,\times0.025^{\circ }$ gridded daily composite daytime SST products of the Moderate-Resolution Imaging Spectroradiometer on the Aqua Sun-synchronous satellite, with an annual data-missing rate fluctuating around 78% in the region. In addition, we validated the reconstructed data against in situ buoy measurements. The reconstructed SST data’s accuracies are $-0.11\,\,^{\circ }\text{C}\,\,\pm $ 0.91 °C (bias ± standard deviation of error) and $-0.12\,\,^{\circ }\text{C}\,\,\pm $ 0.67 °C in the areas without and with satellite observations, respectively, which are slightly lower and higher than the gappy satellite SST products’ accuracy of $-0.14\,\,^{\circ }\text{C}\,\,\pm $ 0.77 °C.

This brief deals with the tracking problem for the unicycle mobile robot (UMR) with slippage effects. A homogeneous controller (HC) is developed based on a particular cascade control strategy. The robustness of the closed-loop system is studied. The design is essentially based on the canonical homogeneous norm being a Lyapunov function of the system. The (finite-time or exponential) convergence rate of the HC can be tuned by a proper selection of the so-called homogeneity degree. Some experimental results illustrate the performance of the proposed homogeneous control in the UMR QBot2 by Quanser.

Soft slender robots have attracted more and more research attentions in these years due to their continuity and compliance natures. However, mechanics modeling for soft robots interacting with environment is still an academic challenge because of the nonlinearity of deformation and the nonsmooth property of the contacts. In this work, starting from a piece-wise local strain field assumption, we propose a nonlinear dynamic model for soft robot via Cosserat rod theory using Newtonian mechanics, which handles the frictional contact with environment and transfer them into the nonlinear complementary constraint (NCP) formulation. Moreover, we smooth both the contact and friction constraints in order to convert the inequality equations of NCP to the smooth equality equations. The proposed model allows us to compute the dynamic deformation and frictional contact force under common optimization framework in real time when the soft slender robot interacts with other rigid or soft bodies. In the end, the corresponding experiments are carried out which valid our proposed dynamic model.

Nanoparticles (NPs) represent an important advance for delivering diagnostic and therapeutic agents across the blood–brain barrier. However, NP clearance is critical for safety and therapeutic applicability. Here we report on a study of the clearance of model organic and inorganic NPs from the brain. We find that microglial extracellular vesicles (EVs) play a crucial role in the clearance of inorganic and organic NPs from the brain. Inorganic NPs, unlike organic NPs, perturb the biogenesis of microglial EVs through the inhibition of ERK1/2 signalling. This increases the accumulation of inorganic NPs in microglia, hindering their elimination via the paravascular route. We also demonstrate that stimulating the release of microglial EVs by an ERK1/2 activator increased the paravascular glymphatic pathway-mediated brain clearance of inorganic NPs. These findings highlight the modulatory role of microglial EVs on the distinct patterns of the clearance of organic and inorganic NPs from the brain and provide a strategy for modulating the intracerebral fate of NPs.

The pipe roofing method is widely used in tunnel construction because it can realize a flexible section shape and a large section area of the tunnel, especially under good ground conditions. However, the pipe roofing method has rarely been applied in soft ground, where the prediction and control of the ground settlement play important roles. This study proposes a sliced-soil–beam (SSB) model to predict the settlement of ground due to tunnelling using the pipe roofing method in soft ground. The model comprises a sliced-soil module based on the virtual work principle and a beam module based on structural mechanics. As part of this work, the Peck formula was modified for a square-section tunnel and adopted to construct a deformation mechanism of soft ground. The pipe roofing system was simplified to a three-dimensional Winkler beam to consider the interaction between the soil and pipe roofing. The model was verified in a case study conducted in Shanghai, China, in which it provided the efficient and accurate prediction of settlement. Finally, the parameters affecting the ground settlement were analyzed. It was clarified that the stiffness of the excavated soil and the steel support are the key factors in reducing ground settlement.

Lung-targeting RNA-carrying lipid nanoparticles (LNPs) are often intravenously administered and accumulate in the pulmonary endothelium. However, most respiratory diseases are localized in the airway or the alveolar epithelium. Inhalation has been explored as a more direct delivery method, but it presents its own challenges. We believe that one reason LNPs have failed to transfect RNA into alveolar epithelial cells is their interaction with the lung surfactant (LS). We propose that inhalable LNP design should take inspiration from biological agents and other nanoparticles to overcome this barrier. Screening should first focus on LS penetration and then be optimized for cell uptake and endosomal release. This will enable more efficient applications of RNA-LNPs in lung diseases.

A wideband function reconfigurable metamaterial (FRM) with a miniaturized periodic unit that is capable of switching between cancellation and absorption responses is proposed for radar cross section (RCS) reduction. The proposed FRM unit is a 3-D structure comprising metal ground and two pairwise orthogonally arranged circuit substrates. By regulating the p-i-n diodes (ON and OFF states), the responses of the proposed FRM unit can switch between two modes. In one mode, wideband absorption is realized for the TE and TM polarized waves. In the other mode, the TE and TM waves are completely reflected with a nearly 180° reflection phase difference. Equivalent circuit models (ECMs) are constructed to provide physical insight into the working mechanism of the switchable structure. Furthermore, a chessboard-like FRM is designed based on the proposed FRM unit to satisfy the phase cancellation principle. The measured results indicate that the proposed FRM can achieve a 10 dB RCS reduction from 2.84 to 7.30 GHz in absorption function and a 10 dB RCS reduction in the range of 2.50–7.44 GHz in cancellation function. The operating frequency bands of these two functions almost overlap. Good agreements between the measured and simulated results are obtained.

In this article, we investigate the event-triggered state estimation for networked switched systems with (a)synchronous switching. A new multimode output predictor-based sampled-data observer and an event-triggered mechanism are proposed. Between event-triggered sampling times, an output predictor is utilized to compensate for the impact of sampling, and at the sampling instants, the predicted output is reset with the updated sampled output. Two scenarios are considered: the observer's switching signal is synchronous with the system's switching signal, and the switching signals among them are asynchronous, and frequent switching is allowed during interevent intervals. Average dwell time and linear matrix inequalities techniques are employed to guarantee the global uniform exponential convergence of the proposed observer. Moreover, Zeno phenomenon can be ruled out by proving the existence of a positive lower bound of interevent intervals. Finally, the effectiveness of the proposed approach is illustrated by a circuit system and an academic example.

In recent years, concrete and reinforced concrete piles have been widely used to stabilize soft ground under embankments. Previous research has shown that bending failure, particularly during rapid filling on soft ground, is the critical failure mode for pile-supported embankments. Here, we propose an efficient two-stage method that combines a test-verified soil deformation mechanism and Poulos’ solution for pile–soil interaction to investigate the bending behavior of piles supporting embankments on soft ground. The results reveal that there are three possible bending failure scenarios for such piles: at the interface between the soft and firm ground layers, at mid-depths of the fan zone, and at the boundary of the soil deformation mechanism. The location of the bending failure depends on the position and relative stiffness of the given pile. Furthermore, the effect of embedding a pile into a firm ground layer on the bending behavior was investigated. When the embedded length of a pile exceeded a critical value, the bending moment at the interface between the soft and firm ground layers reached a limiting value. In addition, floating piles that are not embedded exhibit an overturning pattern of movement in the soft ground layer, and a potential failure is located in the upper part of these piles.

Emerging evidence supports shifting the focus from the quantity of macronutrients to quality to obtain greater benefits for the prognosis of ovarian cancer (OC). Additionally, despite the high relevance between macronutrient quality and quantity, the interaction of these parameters on OC survival remains unknown.

Tumoricidal photodynamic (PDT) and photothermal (PTT) therapies harness light to eliminate cancer cells with spatiotemporal precision by either generating reactive oxygen species or increasing temperature. Great strides have been made in understanding biological effects of PDT and PTT at the cellular, vascular and tumor microenvironmental levels, as well as translating both modalities in the clinic. Emerging evidence suggests that PDT and PTT may synergize due to their different mechanisms of action, and their nonoverlapping toxicity profiles make such combination potentially efficacious. Moreover, PDT/PTT combinations have gained momentum in recent years due to the development of multimodal nanoplatforms that simultaneously incorporate photodynamically- and photothermally active agents. In this review, we discuss how combining PDT and PTT can address the limitations of each modality alone and enhance treatment safety and efficacy. We provide an overview of recent literature featuring dual PDT/PTT nanoparticles and analyze the strengths and limitations of various nanoparticle design strategies. We also detail how treatment sequence and dose may affect cellular states, tumor pathophysiology and drug delivery, ultimately shaping the treatment response. Lastly, we analyze common experimental design pitfalls that complicate preclinical assessment of PDT/PTT combinations and propose rational guidelines to elucidate the mechanisms underlying PDT/PTT interactions.

Graphene (G), as a typical two-dimensional material, is often used as an additive for liquid lubricants. However, graphene is mostly added to liquid lubricants in a one-time manner in friction; it mainly exists in the form of multilayer agglomerated structures due to the π−πstacking between graphene sheets, making it unable to fully exert the synergistic lubrication function. Herein, we propose a new macroscopic superlubric system of graphene/potassium hydroxide (G/KOH) solution; and the graphene additive involved is exfoliated in-situfrom graphene/epoxy (G/EP) friction pair by friction, continuously providing freshly-peeled graphene into KOH solution and minimizing the adverse effects of graphene agglomeration. Moreover, the in-situproduced graphene additive has thinner thickness and better anti-aggregation ability, which provide more graphene to accommodate OH−, form more stacked sandwich structures of OH−/graphene/OH−between friction pairs (i.e., equivalent to a moving pulley block with more wheels), and finally realize superlubricity. This study develops a new liquid superlubric system suitable for alkaline environments, and at the same time proposes a new way to gradually release graphene additives in situ, rather than adding them all at once, deepening the understanding to liquid superlubricity mechanism, and paving the experimental foundation for the practical application of macroscopic superlubricity.

Lipid nanoparticles (LNPs) have achieved clinical success in delivering small interfering RNAs (siRNAs) for targeted gene therapy. However, endosomal escape of siRNA into the cytosol remains a fundamental challenge for LNPs. Herein, we report a strategy termed light-activated siRNA endosomal release (LASER) to address this challenge. We established a porphyrin-LNP by incorporating porphyrin-lipids into the clinically approved Onpattro formulation. The porphyrin-LNP maintained the physical properties of an LNP and generated reactive oxygen species (ROS) when irradiated with near-infrared (NIR) light. Using confocal microscopy, we revealed that porphyrin-lipids within the LNP translocate to endosomal membranes during endocytosis. The translocated porphyrin-lipids generated ROS under light irradiation and enabled LASER through endosomal membranes disruption as observed through GAL-9 recruitment and transmission electron microscopy (TEM). By establishing a quantitative confocal imaging method, we confirmed that porphyrin-LNPs can increase siRNA endosomal escape efficiency by up to 2-fold via LASER and further enhance luciferase target knockdown by 4-fold more in luciferase-transfected prostate cancer cells. Finally, we formulated porphyrin-LNPs encapsulated with gold nanoparticles (GNP) and visualized the LASER effect within prostate tumors via TEM, confirming the light-activated endosomal membrane disruption and subsequent GNP release into cytosols in vivo. Overall, porphyrin-LNPs and the LASER approach enhanced siRNA endosomal escape and significantly improved knockdown efficacy. We believe the versatility of this technology could be applied to various LNP-based RNA therapeutics.

Conducting polymer (CP) actuator has nonlinear dynamic characteristics during its charge process. In this study, we proposed an electromechanic model and an optimal controller for a type of ionic electroactive polymer (IEPA) actuator with submillimeter scale, which can produce large deformation under low actuation voltage. The electronic model is to describe the evolution of charge state in time domain. The mechanic model is to calculate the deformation of CP actuator under the actuation force and external force. Based on the electromechanic coupling model, a parameter identification method is proposed to estimate the nonlinear parameter of CP actuator. The experiments show that our electromechanic model successfully predicts the deformation of actuator under different input voltages with the identified parameters. In the last step, an optimal controller is designed to control the orientation of IEAP actuator, which achieves at a high control performance in our experiments. The success of the modeling and control lays the foundation work for the subsequent biomedical applications.