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In this article, a fast krill herd algorithm is developed for prognosis of hybrid mechatronic system using the improved Wiener degradation process. First, the diagnostic hybrid bond graph is used to model the hybrid mechatronic system and derive global analytical redundancy relations. Based on the global analytical redundancy relations, the fault signature matrix and mode change signature matrix for fault and mode change isolation can be obtained. Second, in order to determine the true faults from the suspected fault candidates after fault isolation, a fault estimation method based on adaptive square root cubature Kalman filter is proposed when the noise distributions are unknown. Then, the improved Wiener process incorporating nonlinear term is developed to build the degradation model of incipient fault based on the fault estimation results. For prognosis, the fast krill herd algorithm is proposed to estimate unknown degradation model coefficients. After that, the probability density function of remaining useful life is derived using the identified degradation model. Finally, the proposed methods are validated by simulations.
Ming Yu; Haotian Lu; Hai Wang; Chenyu Xiao; Dun Lan; Junjie Chen. Computational Intelligence-Based Prognosis for Hybrid Mechatronic System Using Improved Wiener Process. Actuators 2021, 10, 213 .
AMA StyleMing Yu, Haotian Lu, Hai Wang, Chenyu Xiao, Dun Lan, Junjie Chen. Computational Intelligence-Based Prognosis for Hybrid Mechatronic System Using Improved Wiener Process. Actuators. 2021; 10 (9):213.
Chicago/Turabian StyleMing Yu; Haotian Lu; Hai Wang; Chenyu Xiao; Dun Lan; Junjie Chen. 2021. "Computational Intelligence-Based Prognosis for Hybrid Mechatronic System Using Improved Wiener Process." Actuators 10, no. 9: 213.
This paper proposes a novel extreme learning machine (ELM)-based fixed time adaptive trajectory control for electronic throttle valve system with uncertain dynamics and external disturbances. The developed control strategy consists of a recursive full order terminal sliding mode structure based on the bilimit homogeneous property and a lumped uncertainty changing rate upper bound estimator via an adaptive ELM algorithm such that not only the fixed time convergence for both sliding variable and error states can be guaranteed, but also the chattering phenomenon can be suppressed effectively. The stability of the closed-loop system is proved rigorously based on Lyapunov theory. The simulation results are given to verify the superior tracking performance of the proposed control strategy.
Youhao Hu; Hai Wang; Amirmehdi Yazdani; Zhihong Man. Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine. Neural Computing and Applications 2021, 1 -13.
AMA StyleYouhao Hu, Hai Wang, Amirmehdi Yazdani, Zhihong Man. Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine. Neural Computing and Applications. 2021; ():1-13.
Chicago/Turabian StyleYouhao Hu; Hai Wang; Amirmehdi Yazdani; Zhihong Man. 2021. "Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine." Neural Computing and Applications , no. : 1-13.
This article presents a design strategy and stability analysis of modified repetitive sliding mode controller for uncertain linear systems. A modified repetitive controller is adopted to simultaneously track and reject periodic signals. A discrete-time sliding mode controller is combined to compensate the slow response of repetitive control and to provide robustness against plant parameters uncertainties. Stability analysis is provided to prove boundedness of the proposed control law and the convergence of sliding function and the tracking error. Comparative simulation results demonstrate that the proposed method is able to accurately track reference signal and to reject disturbance with fast transient response. The results also indicate that the closed-loop system remains stable in the presence of plant parameter changes.
Edi Kurniawan; Hai Wang; Bernadus H. Sirenden; Jalu A. Prakosa; Hendra Adinanta; Suryadi Suryadi. Discrete‐time modified repetitive sliding mode control for uncertain linear systems. International Journal of Adaptive Control and Signal Processing 2021, 1 .
AMA StyleEdi Kurniawan, Hai Wang, Bernadus H. Sirenden, Jalu A. Prakosa, Hendra Adinanta, Suryadi Suryadi. Discrete‐time modified repetitive sliding mode control for uncertain linear systems. International Journal of Adaptive Control and Signal Processing. 2021; ():1.
Chicago/Turabian StyleEdi Kurniawan; Hai Wang; Bernadus H. Sirenden; Jalu A. Prakosa; Hendra Adinanta; Suryadi Suryadi. 2021. "Discrete‐time modified repetitive sliding mode control for uncertain linear systems." International Journal of Adaptive Control and Signal Processing , no. : 1.
This paper proposes a novel adaptive observer technique for estimating the state and disturbance of uncertain nonlinear systems. To remove the knowledge of the upper bounds of the disturbance and its derivative, a leakage-type (LT) algorithm is introduced to approximate the variations of their bounds. A state observer is first provided based on a conventional Walcott–Zak observer structure, and then, a disturbance observer is proposed by introducing an auxiliary dynamics. Due to the features of the LT adaptive law, the estimation error of the system state or the disturbance is bounded in a small neighborhood around zero in finite time. In addition, since the switching gain is automatically adapted to the disturbance change, the chattering in the estimation signal is effectively suppressed that is useful for the estimation precision in a practical system. Another important advantage of the proposed method lies in its simple structure compared to the existing finite-time observers. Lyapunov analysis demonstrates that for both types of observers, the estimation error is achieved to be globally uniformly ultimately bounded. To demonstrate the proposed method, simulation examples are separately carried out on a vehicle system and a linear motor system.
Ke Shao; Jinchuan Zheng; Hai Wang; XueQian Wang; Bin Liang. Leakage-type adaptive state and disturbance observers for uncertain nonlinear systems. Nonlinear Dynamics 2021, 105, 2299 -2311.
AMA StyleKe Shao, Jinchuan Zheng, Hai Wang, XueQian Wang, Bin Liang. Leakage-type adaptive state and disturbance observers for uncertain nonlinear systems. Nonlinear Dynamics. 2021; 105 (3):2299-2311.
Chicago/Turabian StyleKe Shao; Jinchuan Zheng; Hai Wang; XueQian Wang; Bin Liang. 2021. "Leakage-type adaptive state and disturbance observers for uncertain nonlinear systems." Nonlinear Dynamics 105, no. 3: 2299-2311.
This paper proposed a discrete-time integral terminal sliding mode (DITSM)-based forward speed tracking control for a robotic fish (RF). Due to the difficulty of quantification for the hydrodynamic model of RF during swimming, the head-yawing effect is considered in the obstructive thrust and then the RF dynamic model is further optimized via a data-driven approach. Compared with the traditional robotic fish model, the established model can provide sufficient thrust for the swimming of robotic fish and effectively improve the model accuracy. The DITSM control based on the accurate RF model is proposed by considering the head-yawing effect in order to achieve high-precision and robust speed tracking performance. The real-time experimental results are demonstrated to verify that the proposed control with head-yawing can provide with high-accuracy speed tracking for the RF.
Mao Ye; Hai Wang; Amirmehdi Yazdani; Shuping He; Zhaowu Ping; Weiwei Xu. Discrete-time integral terminal sliding mode-based speed tracking control for a robotic fish. Nonlinear Dynamics 2021, 1 -12.
AMA StyleMao Ye, Hai Wang, Amirmehdi Yazdani, Shuping He, Zhaowu Ping, Weiwei Xu. Discrete-time integral terminal sliding mode-based speed tracking control for a robotic fish. Nonlinear Dynamics. 2021; ():1-12.
Chicago/Turabian StyleMao Ye; Hai Wang; Amirmehdi Yazdani; Shuping He; Zhaowu Ping; Weiwei Xu. 2021. "Discrete-time integral terminal sliding mode-based speed tracking control for a robotic fish." Nonlinear Dynamics , no. : 1-12.
It is well known that load torque disturbance and parametric uncertainties commonly exist in permanent magnet synchronous motor (PMSM) and may reduce the tracking accuracy especially when the reference trajectory is time-varying. Thus it is challenging to achieve precise speed tracking control with both load torque disturbance and parametric uncertainties being taken into account. This task can be formulated as a global robust output regulation problem (GRORP) of multi-input, multi-output nonlinear system. In this paper, a systematic internal model control (IMC) method is proposed to solve the GRORP. By constructing a suitable internal model, we convert the GRORP into a global stabilization problem of an augmented system, and then design a stabilization controller to globally stabilize the augmented system. To validate the advantages of the proposed IMC method, comparative studies with conventional proportional–integral speed control method and linear active disturbance rejection control method are conducted via simulations and experiments. It is worthy of mentioning that our method can not only achieve high precision speed tracking performance under time-varying reference speed and/or load torque disturbance, but also allow all the motor parameters to be uncertain.
Zhaowu Ping; Yaoyi Li; Yang Song; Yunzhi Huang; Hai Wang; Jun-Guo Lu. Nonlinear speed tracking control of PMSM servo system: A global robust output regulation approach. Control Engineering Practice 2021, 112, 104832 .
AMA StyleZhaowu Ping, Yaoyi Li, Yang Song, Yunzhi Huang, Hai Wang, Jun-Guo Lu. Nonlinear speed tracking control of PMSM servo system: A global robust output regulation approach. Control Engineering Practice. 2021; 112 ():104832.
Chicago/Turabian StyleZhaowu Ping; Yaoyi Li; Yang Song; Yunzhi Huang; Hai Wang; Jun-Guo Lu. 2021. "Nonlinear speed tracking control of PMSM servo system: A global robust output regulation approach." Control Engineering Practice 112, no. : 104832.
Long Chen; Jun Liu; Hai Wang; Youhao Hu; Xuefeng Zheng; Mao Ye; Jie Zhang. Correction to: Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode. Nonlinear Dynamics 2021, 104, 4753 -4753.
AMA StyleLong Chen, Jun Liu, Hai Wang, Youhao Hu, Xuefeng Zheng, Mao Ye, Jie Zhang. Correction to: Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode. Nonlinear Dynamics. 2021; 104 (4):4753-4753.
Chicago/Turabian StyleLong Chen; Jun Liu; Hai Wang; Youhao Hu; Xuefeng Zheng; Mao Ye; Jie Zhang. 2021. "Correction to: Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode." Nonlinear Dynamics 104, no. 4: 4753-4753.
In this article, we consider the distributed fault-tolerant resilient consensus problem for heterogeneous multiagent systems (MASs) under both physical failures and network denial-of-service (DoS) attacks. Different from the existing consensus results, the dynamic model of the leader is unknown for all followers in this article. To learn this unknown dynamic model under the influence of DoS attacks, a distributed resilient learning algorithm is proposed by using the idea of data-driven. Based on the learned dynamic model of the leader, a distributed resilient estimator is designed for each agent to estimate the states of the leader. Then, a new adaptive fault-tolerant resilient controller is designed to resist the effect of physical failures and network DoS attacks. Moreover, it is shown that the consensus can be achieved with the proposed learning-based fault-tolerant resilient control method. Finally, a simulation example is provided to show the effectiveness of the proposed method.
Chao Deng; Xiao-Zheng Jin; Wei-Wei Che; Hai Wang. Learning-Based Distributed Resilient Fault-Tolerant Control Method for Heterogeneous MASs Under Unknown Leader Dynamic. IEEE Transactions on Neural Networks and Learning Systems 2021, PP, 1 -10.
AMA StyleChao Deng, Xiao-Zheng Jin, Wei-Wei Che, Hai Wang. Learning-Based Distributed Resilient Fault-Tolerant Control Method for Heterogeneous MASs Under Unknown Leader Dynamic. IEEE Transactions on Neural Networks and Learning Systems. 2021; PP (99):1-10.
Chicago/Turabian StyleChao Deng; Xiao-Zheng Jin; Wei-Wei Che; Hai Wang. 2021. "Learning-Based Distributed Resilient Fault-Tolerant Control Method for Heterogeneous MASs Under Unknown Leader Dynamic." IEEE Transactions on Neural Networks and Learning Systems PP, no. 99: 1-10.
This paper is concerned with the adaptive state observation and resilient control problem for a class of perturbed cyber-physical system against denial of service (DoS) attacks. An adaptive observer is firstly constructed to observe the compromised states under DoS attacks. Then based on the estimated sates, a resilient control strategy is developed to remedy the negative influence of DoS attacks and perturbations. By employing linear matrix inequality and Lyapunov stability theory, one can guarantee that the system states can track the desired signals of reference systems with time going to infinity. Furthermore, the state observation errors are guaranteed to remain a high accuracy. An aircraft system with different attack forms and attack modes is given to verify the effectiveness of designed adaptive observer and control methods.
Shao-Yu Lü; Xiao-Zheng Jin; Hai Wang; Chao Deng. Robust adaptive estimation and tracking control for perturbed cyber-physical systems against denial of service. Applied Mathematics and Computation 2021, 404, 126255 .
AMA StyleShao-Yu Lü, Xiao-Zheng Jin, Hai Wang, Chao Deng. Robust adaptive estimation and tracking control for perturbed cyber-physical systems against denial of service. Applied Mathematics and Computation. 2021; 404 ():126255.
Chicago/Turabian StyleShao-Yu Lü; Xiao-Zheng Jin; Hai Wang; Chao Deng. 2021. "Robust adaptive estimation and tracking control for perturbed cyber-physical systems against denial of service." Applied Mathematics and Computation 404, no. : 126255.
In this paper, the modelling of a reaction wheel bicycle robot (RWBR) is identified from a second-order mathematical model which is similar to an inverted pendulum, and an adaptive integral terminal sliding mode (AITSM) control scheme is developed for balancing purpose of the RWBR. The proposed AITSM control scheme can not only stabilize the bicycle robot and reject external disturbances generated by uncertainties and unmodelled dynamics, but also eliminate the need of the required bound information in the control law via the designed adaptive laws. The experimental results verify the excellent performance of the proposed control scheme in terms of strong robustness, fast error convergence in comparison with other control schemes.
Long Chen; Jun Liu; Hai Wang; Youhao Hu; Xuefeng Zheng; Mao Ye; Jie Zhang. Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode. Nonlinear Dynamics 2021, 104, 2291 -2302.
AMA StyleLong Chen, Jun Liu, Hai Wang, Youhao Hu, Xuefeng Zheng, Mao Ye, Jie Zhang. Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode. Nonlinear Dynamics. 2021; 104 (3):2291-2302.
Chicago/Turabian StyleLong Chen; Jun Liu; Hai Wang; Youhao Hu; Xuefeng Zheng; Mao Ye; Jie Zhang. 2021. "Robust control of reaction wheel bicycle robot via adaptive integral terminal sliding mode." Nonlinear Dynamics 104, no. 3: 2291-2302.
Recently, the global robust output regulation problem for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems which may not have well‐defined relative degree and are subject to a nonlinear exosystem has been studied based on a constructive nonlinear internal model. However, the proposed nonlinear internal model‐based control law is applicable to the case where the exogenous signals are reference input and/or measurable disturbance rather than unmeasurable disturbance. For this reason, this paper further studies the same control problem based on a general nonlinear internal model independent of the exogenous signal. It is shown that this control problem can be converted into a global robust stabilization problem of a more complicated MIMO nonlinear system with various uncertainties and well solved by a recursive state feedback controller design. Thus our approach applies to a broader class of output regulation problem of MIMO nonlinear systems.
Zhaowu Ping; Yaoyi Li; Yunzhi Huang; Jun‐Guo Lu; Hai Wang. Global robust output regulation of a class of MIMO nonlinear systems by nonlinear internal model control. International Journal of Robust and Nonlinear Control 2021, 1 .
AMA StyleZhaowu Ping, Yaoyi Li, Yunzhi Huang, Jun‐Guo Lu, Hai Wang. Global robust output regulation of a class of MIMO nonlinear systems by nonlinear internal model control. International Journal of Robust and Nonlinear Control. 2021; ():1.
Chicago/Turabian StyleZhaowu Ping; Yaoyi Li; Yunzhi Huang; Jun‐Guo Lu; Hai Wang. 2021. "Global robust output regulation of a class of MIMO nonlinear systems by nonlinear internal model control." International Journal of Robust and Nonlinear Control , no. : 1.
The ionic polymer metal composite (IPMC) actuator is a kind of soft actuator that can work for underwater applications. However, IPMC actuator control suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, for underwater applications, they are highly exposed to parametric uncertainties and external disturbances due to the inherent characteristics and working environment. Those factors significantly affect the positioning accuracy and reliability of IPMC actuators. Hence, feedback control techniques are vital in the control of IPMC actuators for suppressing the system uncertainty and external disturbance. In this paper, for the first time an adaptive full-order recursive terminal sliding-mode (AFORTSM) controller is proposed for the IPMC actuator to enhance the positioning accuracy and robustness against parametric uncertainties and external disturbances. The proposed controller incorporates an adaptive algorithm with terminal sliding mode method to release the need for any prerequisite bound of the disturbance. In addition, stability analysis proves that it can guarantee the tracking error to converge to zero in finite time in the presence of uncertainty and disturbance. Experiments are carried out on the IPMC actuator to verify the practical effectiveness of the AFORTSM controller in comparison with a conventional nonsingular terminal sliding mode (NTSM) controller in terms of smaller tracking error and faster disturbance rejection.
Romina Ekbatani; Ke Shao; Jasim Khawwaf; Hai Wang; Jinchuan Zheng; Xiaoqi Chen; Mostafa Nikzad. Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode. Actuators 2021, 10, 33 .
AMA StyleRomina Ekbatani, Ke Shao, Jasim Khawwaf, Hai Wang, Jinchuan Zheng, Xiaoqi Chen, Mostafa Nikzad. Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode. Actuators. 2021; 10 (2):33.
Chicago/Turabian StyleRomina Ekbatani; Ke Shao; Jasim Khawwaf; Hai Wang; Jinchuan Zheng; Xiaoqi Chen; Mostafa Nikzad. 2021. "Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode." Actuators 10, no. 2: 33.
This paper proposes an adaptive tracking control scheme for an electronic throttle valve (ETV) based on recursive terminal sliding mode (RTSM) control strategy in the presence of parametric uncertainties and lumped disturbance. The developed RTSM dynamical structure for the controller is composed of a fast nonsingular terminal sliding surface and a recursive integral terminal sliding function, such that not only is the reaching phase eliminated, but also a sequential finite-time zero-convergence of both the recursive sliding surfaces and position tracking error are guaranteed. Due to the difficulty in ensuring a satisfactory tracking performance with respective to a broad range of operation conditions in practice, an adaptive mechanism is further developed to estimate both the lumped uncertainty bound and the sliding mode parameters, such that no prior knowledge of the system is required in the controller leading to the effective improvement of the flexibility and simplicity of sliding mode-based ETV control systems. Comparative experiments are conducted to verify that the proposed control enjoys a fast finite-time convergence and superior robustness with respect to uncertainties and disturbances.
Youhao Hu; Hai Wang; Shuping He; Jinchuan Zheng; Zhaowu Ping; Ke Shao; Zhenwei Cao; Zhihong Man. Adaptive Tracking Control of an Electronic Throttle Valve Based on Recursive Terminal Sliding Mode. IEEE Transactions on Vehicular Technology 2020, 70, 251 -262.
AMA StyleYouhao Hu, Hai Wang, Shuping He, Jinchuan Zheng, Zhaowu Ping, Ke Shao, Zhenwei Cao, Zhihong Man. Adaptive Tracking Control of an Electronic Throttle Valve Based on Recursive Terminal Sliding Mode. IEEE Transactions on Vehicular Technology. 2020; 70 (1):251-262.
Chicago/Turabian StyleYouhao Hu; Hai Wang; Shuping He; Jinchuan Zheng; Zhaowu Ping; Ke Shao; Zhenwei Cao; Zhihong Man. 2020. "Adaptive Tracking Control of an Electronic Throttle Valve Based on Recursive Terminal Sliding Mode." IEEE Transactions on Vehicular Technology 70, no. 1: 251-262.
This paper addresses diagnosis and prognosis problems for an electric scooter subjected to parameter uncertainties and compound faults (i.e., permanent fault and intermittent fault with non-monotonic degradation). First, the diagnostic bond graph in linear fractional transformation form is used to model the uncertain electric scooter and derive the analytical redundancy relations incorporating the nominal part and uncertain part, based on which the adaptive thresholds for robust fault detection and the fault signature matrix for fault isolation can be obtained. Second, an adaptive enhanced unscented Kalman filter is proposed to identify the fault magnitudes and distinguish the fault types where an auxiliary detector is introduced to capture the appearing and disappearing moments of intermittent fault. Third, a dynamic model with usage dependent degradation coefficient is developed to describe the degradation process of intermittent fault under various usage conditions. Due to the variation of degradation coefficient and the presence of non-monotonic degradation characteristic under some usage conditions, a sequential prognosis method is proposed where the reactivation of the prognoser is governed by the reactivation events. Finally, the proposed methods are validated by experiment results.
Ming Yu; Haotian Lu; Hai Wang; Chenyu Xiao; Dun Lan. Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties. Actuators 2020, 9, 128 .
AMA StyleMing Yu, Haotian Lu, Hai Wang, Chenyu Xiao, Dun Lan. Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties. Actuators. 2020; 9 (4):128.
Chicago/Turabian StyleMing Yu; Haotian Lu; Hai Wang; Chenyu Xiao; Dun Lan. 2020. "Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties." Actuators 9, no. 4: 128.
In this article, a novel active front steering (AFS) control strategy including the upper controller and the lower controller is proposed to improve the yaw stability and maneuverability for steer-by-wire (SbW) vehicles. The adaptive recursive integral terminal sliding mode (ARITSM) control is adopted in the upper controller for guaranteeing the convergence performance of both the actual sideslip angle and the yaw rate with strong robustness and fast convergence rate. Then, a fast nonsingular terminal sliding mode (FNTSM) control with extreme learning machine (ELM) estimator to estimate its equivalent control is designed in the lower controller to track the desired front wheel steering angle calculated from the upper controller for driving the sideslip angle and the yaw rate to converge ideal value. It is shown that the upper controller takes two controlled variables (vehicle sideslip angle and yaw rate) and only one control input (front steering angle) into consideration, which can obtain a better performance compared with the case of using only one of these values. Since using the ELM technique in the lower controller to estimate the equivalent control of the FNTSM, not only the dependence of SbW system dynamics can be alleviated in the process of designing controller but also the excellent steering control performance can be achieved. Comparative simulations are carried out by utilizing Carsim and Matlab software to validate the excellent performance of the proposed control strategy for different steering maneuvers.
Jie Zhang; Hai Wang; Mingyao Ma; Ming Yu; Amirmehdi Yazdani; Long Chen. Active Front Steering-Based Electronic Stability Control for Steer-by-Wire Vehicles via Terminal Sliding Mode and Extreme Learning Machine. IEEE Transactions on Vehicular Technology 2020, 69, 14713 -14726.
AMA StyleJie Zhang, Hai Wang, Mingyao Ma, Ming Yu, Amirmehdi Yazdani, Long Chen. Active Front Steering-Based Electronic Stability Control for Steer-by-Wire Vehicles via Terminal Sliding Mode and Extreme Learning Machine. IEEE Transactions on Vehicular Technology. 2020; 69 (12):14713-14726.
Chicago/Turabian StyleJie Zhang; Hai Wang; Mingyao Ma; Ming Yu; Amirmehdi Yazdani; Long Chen. 2020. "Active Front Steering-Based Electronic Stability Control for Steer-by-Wire Vehicles via Terminal Sliding Mode and Extreme Learning Machine." IEEE Transactions on Vehicular Technology 69, no. 12: 14713-14726.
Fatigue driving (FD) is one of the main causes of traffic accidents. Traditionally, machine learning technologies such as back propagation neural network (BPNN) and support vector machine (SVM) are popularly used for fatigue driving detection. However, the BPNN exhibits slow convergence speed and many adjustable parameters, while it is difficult to train large-scale samples in the SVM. In this paper, we develop extreme learning machine (ELM)-based FD detection method to avoid the above disadvantages. Further, since the randomness of the weight and biases between the input layer and the hidden layer of the ELM will influence its generalization performance, we further apply a differential evolution ELM (DE-ELM) method to the analysis of the driver’s respiration and heartbeat signals, which can effectively judge the driver fatigue state. Moreover, not only will the Doppler radar and smart bracelet be used to obtain the driver respiration and heartbeat signals, but also the sample database required for the experiment will be established through extensive signal collections. Experimental results show that the DE-ELM has a better performance on driver’s fatigue level detection than the traditional ELM and SVM.
Long Chen; Xiaojie Zhi; Hai Wang; Guanjin Wang; Zhenghua Zhou; Amirmehdi Yazdani; Xuefeng Zheng. Driver Fatigue Detection via Differential Evolution Extreme Learning Machine Technique. Electronics 2020, 9, 1850 .
AMA StyleLong Chen, Xiaojie Zhi, Hai Wang, Guanjin Wang, Zhenghua Zhou, Amirmehdi Yazdani, Xuefeng Zheng. Driver Fatigue Detection via Differential Evolution Extreme Learning Machine Technique. Electronics. 2020; 9 (11):1850.
Chicago/Turabian StyleLong Chen; Xiaojie Zhi; Hai Wang; Guanjin Wang; Zhenghua Zhou; Amirmehdi Yazdani; Xuefeng Zheng. 2020. "Driver Fatigue Detection via Differential Evolution Extreme Learning Machine Technique." Electronics 9, no. 11: 1850.
This letter proposes a novel junction temperature estimation method for IGBT module to adapt to various operating conditions and improve computing efficiency. By using superposition theorem and odd/even mode analysis, the input power loss is decomposed into the even and odd mode loss. Further, the thermal model considering the thermal coupling between the upper and lower arms is equivalently decomposed into the even and odd mode thermal model according to structure symmetry. The odd mode power loss is the cause of the thermal coupling between the upper and lower arms, and the odd mode junction temperature variation is used as an indicator to measure the thermal coupling. Based on frequency domain analysis, the dividing line for operating condition with weak thermal coupling and strong thermal coupling can be obtained. Finally, experimental results verify the validity of the theoretical analysis and the accuracy of the proposed thermal estimation method.
Weisheng Guo; Mingyao Gae Ma; Hai Wang; Shuying Yang; Xing Zhang; Xuesong Yan; Wenjie Chen; Guoqing Cai. A Thermal Estimation Method for IGBT Module Adaptable to Operating Conditions. IEEE Transactions on Power Electronics 2020, 36, 6147 -6152.
AMA StyleWeisheng Guo, Mingyao Gae Ma, Hai Wang, Shuying Yang, Xing Zhang, Xuesong Yan, Wenjie Chen, Guoqing Cai. A Thermal Estimation Method for IGBT Module Adaptable to Operating Conditions. IEEE Transactions on Power Electronics. 2020; 36 (6):6147-6152.
Chicago/Turabian StyleWeisheng Guo; Mingyao Gae Ma; Hai Wang; Shuying Yang; Xing Zhang; Xuesong Yan; Wenjie Chen; Guoqing Cai. 2020. "A Thermal Estimation Method for IGBT Module Adaptable to Operating Conditions." IEEE Transactions on Power Electronics 36, no. 6: 6147-6152.
This article is concerned with the robust adaptive fault-tolerant control (FTC) circuit designs for a class of continuous-time disturbed systems. A circuit realization method is investigated to convert the robust adaptive FTC control schemes into analog control circuits. An adaptive compensation control scheme against state-dependent and partially bounded actuator faults and disturbances is first developed to demonstrate the approach clearly, then its equivalent control circuits are implemented by using the circuit theory. Compared with simulation results achieved by MATLAB and professional circuit simulation software, the effectiveness of the proposed robust adaptive FTC circuits is validated by a rocket fairing system and a Chua's circuit system.
Xiao-Zheng Jin; Wei-Wei Che; Zheng-Guang Wu; Hai Wang. Analog Control Circuit Designs for a Class of Continuous-Time Adaptive Fault-Tolerant Control Systems. IEEE Transactions on Cybernetics 2020, PP, 1 -12.
AMA StyleXiao-Zheng Jin, Wei-Wei Che, Zheng-Guang Wu, Hai Wang. Analog Control Circuit Designs for a Class of Continuous-Time Adaptive Fault-Tolerant Control Systems. IEEE Transactions on Cybernetics. 2020; PP (99):1-12.
Chicago/Turabian StyleXiao-Zheng Jin; Wei-Wei Che; Zheng-Guang Wu; Hai Wang. 2020. "Analog Control Circuit Designs for a Class of Continuous-Time Adaptive Fault-Tolerant Control Systems." IEEE Transactions on Cybernetics PP, no. 99: 1-12.
In this paper, the position and attitude trajectory tracking problem of a class of quadrotor aircrafts with bounded external disturbances and state-dependent internal uncertainties is addressed. Neural network (NN)-based methods are adopted to approximate the unknown uncertainties, while adaptive technique is used to estimate the unknown bounds of disturbances. Then, an adaptive compensation control scheme based on neural networks is proposed to compensate for the effects of disturbances and uncertainties. On the basis of Lyapunov stability theorem, bounded trajectory tracking of a position subsystem and asymptotic trajectory tracking of an attitude subsystem can be achieved by using the NN-based adaptive compensation control scheme in the presence of internal uncertainties and external disturbances. A numerical simulation is carried out to verify the effectiveness of the designed control method of quadrotor aircrafts.
Xiao-Zheng Jin; Tao He; Xiao-Ming Wu; Hai Wang; Jing Chi. Robust adaptive neural network-based compensation control of a class of quadrotor aircrafts. Journal of the Franklin Institute 2020, 357, 12241 -12263.
AMA StyleXiao-Zheng Jin, Tao He, Xiao-Ming Wu, Hai Wang, Jing Chi. Robust adaptive neural network-based compensation control of a class of quadrotor aircrafts. Journal of the Franklin Institute. 2020; 357 (17):12241-12263.
Chicago/Turabian StyleXiao-Zheng Jin; Tao He; Xiao-Ming Wu; Hai Wang; Jing Chi. 2020. "Robust adaptive neural network-based compensation control of a class of quadrotor aircrafts." Journal of the Franklin Institute 357, no. 17: 12241-12263.
Prognosis of discrete component with intermittent fault in hybrid systems is challenging since the component has only two states (i.e., ON and OFF) and no associated physical parameter in the model can quantify the degradation. This article aims to solve the discrete component prognosis problem under the model-based paradigm. First, the fault detection and isolation module help find the possible faulty discrete components. Based on the isolated possible faulty discrete components, Levy flight biogeography-based optimization is proposed to identify the faulty discrete component states, as well as the fault appearing and fault disappearing instants. Second, a Weibull function-based degradation model which can capture the duration evolution of intermittent fault of discrete component in observation window (OW) is developed using coordinate reconstruction approach, and the degradation model coefficients can be calculated from the fault identification results. After that, the concept of failure threshold for faulty discrete component is defined based on the ratio of fault duration to OW, which enables the prognosis of intermittent fault in discrete component. Finally, the proposed methodologies are validated by experiment results.
Chenyu Xiao; Ming Yu; Bin Zhang; Hai Wang; Canghua Jiang. Discrete Component Prognosis for Hybrid Systems Under Intermittent Faults. IEEE Transactions on Automation Science and Engineering 2020, PP, 1 -12.
AMA StyleChenyu Xiao, Ming Yu, Bin Zhang, Hai Wang, Canghua Jiang. Discrete Component Prognosis for Hybrid Systems Under Intermittent Faults. IEEE Transactions on Automation Science and Engineering. 2020; PP (99):1-12.
Chicago/Turabian StyleChenyu Xiao; Ming Yu; Bin Zhang; Hai Wang; Canghua Jiang. 2020. "Discrete Component Prognosis for Hybrid Systems Under Intermittent Faults." IEEE Transactions on Automation Science and Engineering PP, no. 99: 1-12.