Modeling and Design Adaptive Double Neural Network Controller for Eight-Rotor Micro Aircraft Vehicle

Di Li,Zhihong Lu,Xiang-jian Chen 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.11

In this article, a dynamic model of a six degrees of freedom (6 DOF) Eight-Rotor MAV (micro aerial vehicles) is derived on the basis of the Newton-Euler formalism. The derivation comprises determining equations of the motion of the Eight-Rotor MAV in three dimensions and approximating the actuation forces through the modelling of aerodynamic coefficients and electric motor dynamics. For Eight-Rotor MAV is inherently unstable as they are highly sensitive to external perturb, here provides an adaptive double neural network controller for the motion control of the Eight-Rotor MAV autonomous flight. This controller is developed in three parts around each of the variables. The experimental results show that the proposed adaptive double neural network controller outperforms the conventional PID controller due to its fast adaptive qualities in the presence of sensor measurement noise and the parameters variations of Eight-Rotor MAV.

Systematic Review of Single Large and/or Multinodular Hepatocellular Carcinoma: Surgical Resection Improves Survival

Yang, Xiang-Di,Pan, Ling-Hui,Wang, Lin,Ke, Yang,Cao, Ji,Yang, Chun,Zhong, Jian-Hong,Luo, Wang,Guo, Jiao,Li, Le-Qun Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.13

Background: The role of surgical resection for patients with single large (${\geq}5cm$) and/or multinodular (${\geq}2$) hepatocellular carcinoma (HCC) is still controversial. This systematic review was performed to evaluate the safety and efficacy of resection for patients with single large and/or multinodular HCC. Materials and Methods: Databases (the PubMed, Web of Science, Embase, and Cochrane databases) were systematically searched to identify relevant studies exploring the safety and efficacy of resection for single large and/or multinodular HCC, published between January 2000 and December 2014. Perioperative morbidity and mortality, overall survival, and disease-free survival of the resection group were calculated. In addition, these outcome variables were also calculated for the control group in the included studies. Results: One randomized controlled trial and 42 nonrandomized studies involving 9,580 patients were eligible for analysis. Eight (1,594 patients) of the 43 studies also reported the outcomes of transarterial chemoembolization (TACE). Although 51.4% of patients featured cirrhosis, 90.7% of them demonstrated Child-Pugh A liver function in the resection group. The median rates of morbidity (24.5%) and mortality (2.5%) after resection were significantly higher than that of TACE (11.0%, P<0.001; 1.9%, P<0.001). However, patients who underwent resection had significantly higher median one-, three-, and five-year overall survival (76.1%, 51.7%, and 37.4%) than those who underwent TACE (68.3%, 31.5%, and 17.5%, all P<0.001). The median 1-, 3-, and 5-year DFS rates after resection were 58.3%, 34.6%, and 24.0%, respectively. Conclusions: Although tumor recurrence after resection for patients with single large and/ or multinodular HCC continues to be a major problem, resection should be considered as a strategy to achieve long-term survival.

Radar Emitter Signals Identification with a Optimal Recurrent Type 2 Wavelet Fuzzy Neural Network

Xiang-jian Chen,Di Li,Xi-Bei Yang,Hongmei Li 한국항공우주학회 2018 International Journal of Aeronautical and Space Sc Vol.19 No.3

One optimal recurrent type 2-wavelet fuzzy neural network (RT2WFNN) is proposed in this paper to deal with the problem of emitter identification caused by some types of noise. The RT2WFNN has both an on-line parameter and structure learning ability. The new adaptive method based on gradient decent with Lyapunov theorem used for parameter learning can improve the learning ability of RT2WFNN; the type 2 FCM and optimal improved EKM algorithm are used to select the cluster centers of the membership functions in the antecedent part of fuzzy rules of the RT2WFNN for shortening the adjustment time. A number of simulations are presented to demonstrate the identification capability of the RT2WFNN algorithm for the radar emitter identification. The simulation and actual experimental results illustrated that the proposed RT2WFNN cannot only have better identification capability, but also is relatively more insensitive to noise and accelerate the computing speed.

Modeling and designing intelligent adaptive sliding mode controller for an Eight-Rotor MAV

Xiang-jian Chen,Di Li 한국항공우주학회 2013 International Journal of Aeronautical and Space Sc Vol.14 No.2

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-Ⅱ fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-Ⅱ fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-Ⅱ fuzzy neural network based adaptive sliding mode controller could guarantee the Eight- Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-Ⅰ fuzzy neural network based sliding mode controller.

Modeling and Real-timecontrol of MAV with Multi-rotors

Xiang-jian Chen,Di Li,Zhi-jun Xu,Yue Bai 보안공학연구지원센터 2013 International Journal of Control and Automation Vol.6 No.5

Robusts Adaptive Interval Type II Fuzzy Neural Network Control for the Synchronization of Uncertain Chaotic Systems

Xiang-jian Chen,Di Li 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12

The proposed RAITIIFNNC system is comprised of a interval type II fuzzy neural network identifier and a robust controller. The identifier is utilized for online estimation of the compound uncertainties. The robust controller is used to attenuate the effects of the approximation error so that the perfect tracking and synchronization of chaotic systems are achieved. All the parameter learning algorithms are derived based on Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. From the simulation example, to synchronize two Lorenz chaotic systems, it has been shown that the effectiveness of the proposed method has been verified.

Modeling and designing intelligent adaptive sliding mode controller for an Eight-Rotor MAV

Chen, Xiang-Jian,Li, Di The Korean Society for Aeronautical and Space Scie 2013 International Journal of Aeronautical and Space Sc Vol.14 No.2

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

Nestin Is Required for the Proper Self-Renewal of Neural Stem Cells

Park, Donghyun,Xiang, Andy Peng,Mao, Frank Fuxiang,Zhang, Li,Di, Chun-Guang,Liu, Xiao-Mei,Shao, Yuan,Ma, Bao-Feng,Lee, Jae-Hyun,Ha, Kwon-Soo,Walton, Noah,Lahn, Bruce T. Wiley (John WileySons) 2010 Stem Cells Vol.28 No.12

Evolution of Microstructures and Compressive Properties in Al0.5CrFeNi2.1Mn0.8Tix High Entropy Alloys

Xu Chen,Di Gao,Yan Zhang,Jia Xuan Hu,Ye Liu,Feng Xiang 대한금속·재료학회 2021 METALS AND MATERIALS International Vol.27 No.1

The effects of Ti on the microstructures, macrohardness and compressive properties of the as-cast Al0.5CrFeNi2.1Mn0.8TixHEAs were investigated. The results showed that the microstructures of as-cast Al0.5CrFeNi2.1Mn0.8Tixalloys was changedfrom FCC phase to a mixture of FCC and BCC phases, then to a mixture of BCC phase and Ti-containing intermetalliccompound as the increasing of Ti content. Chrysanthemum-like eutectic microstructure was obtained in theAl0.5CrFeNi2.1Mn0.8Ti0.5and Al0.5CrFeNi2.1Mn0.8Tialloys. The area of flower core was composed of BCC2 phase, andeutectic microstructure was achieved in the petal area which contained BCC1 phase and BCC2 phase. Moreover, the macrohardnessof the as-cast alloys increased with the increasing of Ti, and the Al0.5CrFeNi2.1Mn0.8Ti0.5alloy showed excellentcomprehensive compressive properties.

FSO as backhaul and energizer for drone-assisted mobile access networks

Nirwan Ansari,Di Wu,Xiang Sun 한국통신학회 2020 ICT Express Vol.6 No.2

Drone mounted base stations (DBSs) can be flexibly deployed over some areas (such as hotspots and disaster struck areas) to speed up the communication between terrestrial base stations (TBSs) and users. In order to increase the capacity of the backhaul link between a DBS and its TBS, free space optical (FSO) communications is applied as the backhaul solution. However, the DBS and its TBS should be in line-of-sight (LoS). Thus, a new DBS placement method is introduced to maximize the number of served users while guaranteeing the LoS between the DBS and its TBS. In addition, in order to prolong the hovering time of a DBS, we propose to deploy an optical beam to facilitate simultaneous communications and charging. That is, an optical beam transmitted from a TBS to its DBS carries not only data but also energy. The DBS mounted with a solar panel and an FSO receiver receives both the data and energy carried by the optical beam simultaneously. Numerical results demonstrate that using an optical beam to charge and communicate with a DBS can gain 25% extra hovering time of the DBS and achieve high network throughput.