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This paper proposes a new switching adaptive fuzzy controller and applies it to vibration control of a vehicle seat suspension equipped with a semi-active magnetorheological (MR) damper. The proposed control system consists of three functioned filters: (1) Filter 1: a model of interval type 2 fuzzy to compensate disturbances; (2) Filter 2: a ‘switching term’ to evaluate the magnitude of disturbance; and (3) Filter 3: a group of adaptation laws to enhance the robustness of control input. These filters play a role of powerful shields to improve control performance and guarantee the stability of the applied system subjected to external disturbances. After embedding a PID (proportional-integral-derivative) model into Riccati-like equation, main control parameters are updated based on the adaptation laws. The proposed controller is then synthesized in two different cases: high disturbance and small disturbance. For the high disturbance, a special type of sliding surface function, which relates to an exponential function and its t-norm, is used to increase the energy of control system. For the small disturbance, the energy from the modified t-norm of the sliding surface is neglected to reduce the energy consumption with maintaining the desired performance. To demonstrate the effectiveness of the proposed controller, a vehicle seat suspension installed with controllable MR damper is adopted to reflect the robustness against external disturbances corresponding to road excitations. It is validated from computer simulation that the proposed controller can provide better vibration control performance than other existing robust controllers showing excellent control stability with well-reduced displacement and velocity at the position of the seat.
Do Phu; Van Mien; Seung-Bok Choi. A New Switching Adaptive Fuzzy Controller with an Application to Vibration Control of a Vehicle Seat Suspension Subjected to Disturbances. Applied Sciences 2021, 11, 2244 .
AMA StyleDo Phu, Van Mien, Seung-Bok Choi. A New Switching Adaptive Fuzzy Controller with an Application to Vibration Control of a Vehicle Seat Suspension Subjected to Disturbances. Applied Sciences. 2021; 11 (5):2244.
Chicago/Turabian StyleDo Phu; Van Mien; Seung-Bok Choi. 2021. "A New Switching Adaptive Fuzzy Controller with an Application to Vibration Control of a Vehicle Seat Suspension Subjected to Disturbances." Applied Sciences 11, no. 5: 2244.
In this paper, a higher-order terminal sliding mode control is proposed for fault accommodation of a class of Lipschitz second-order nonlinear systems. This approach is designed based on a combining between a novel third-order fast terminal sliding mode surface (TOFTSMS), which is designed to preserve the merits of the PID sliding surface and the fast terminal sliding mode (FTSM) surface, and a continuous control law based on higher-order sliding mode (HOSM) control strategy. However, the proposed TOFTSMC requires an exact dynamics model of the system and the prior knowledge of the bounded value of the uncertainties and faults in the design. In order to exclude the requirements, an adaptive fuzzy neural network is integrated; yielding a novel adaptive fuzzy neural TOFTSMC (AFN-TOFTSMC). The proposed analytical results are then applied to the attitude control of a spacecraft. Simulation results clearly demonstrate the great performance of the proposed algorithm compared to other state-of-the-art methods.
Mien Van. Higher-order terminal sliding mode controller for fault accommodation of Lipschitz second-order nonlinear systems using fuzzy neural network. Applied Soft Computing 2021, 104, 107186 .
AMA StyleMien Van. Higher-order terminal sliding mode controller for fault accommodation of Lipschitz second-order nonlinear systems using fuzzy neural network. Applied Soft Computing. 2021; 104 ():107186.
Chicago/Turabian StyleMien Van. 2021. "Higher-order terminal sliding mode controller for fault accommodation of Lipschitz second-order nonlinear systems using fuzzy neural network." Applied Soft Computing 104, no. : 107186.
Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.
Mai The Vu; Tat-Hien Le; Ha Le Nhu Ngoc Thanh; Tuan-Tu Huynh; Mien Van; Quoc-Dong Hoang; Ton Duc Do. Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control. Sensors 2021, 21, 747 .
AMA StyleMai The Vu, Tat-Hien Le, Ha Le Nhu Ngoc Thanh, Tuan-Tu Huynh, Mien Van, Quoc-Dong Hoang, Ton Duc Do. Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control. Sensors. 2021; 21 (3):747.
Chicago/Turabian StyleMai The Vu; Tat-Hien Le; Ha Le Nhu Ngoc Thanh; Tuan-Tu Huynh; Mien Van; Quoc-Dong Hoang; Ton Duc Do. 2021. "Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control." Sensors 21, no. 3: 747.
This paper presents a novel method for fusing information from multiple sensor systems for bearing fault diagnosis. In the proposed method, a convolutional neural network is exploited to handle multiple signal sources simultaneously. The most important finding of this paper is that a deep neural network with wide structure can extract automatically and efficiently discriminant features from multiple sensor signals simultaneously. The feature fusion process is integrated into the deep neural network as a layer of that network. Compared to single sensor cases and other fusion techniques, the proposed method achieves superior performance in experiments with actual bearing data.
Duy Tang Hoang; Xuan Toa Tran; Mien Van; Hee Jun Kang. A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis. Sensors 2021, 21, 244 .
AMA StyleDuy Tang Hoang, Xuan Toa Tran, Mien Van, Hee Jun Kang. A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis. Sensors. 2021; 21 (1):244.
Chicago/Turabian StyleDuy Tang Hoang; Xuan Toa Tran; Mien Van; Hee Jun Kang. 2021. "A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis." Sensors 21, no. 1: 244.
In this paper, a robust fault tolerant control, which provides a global fixed-time stability, is proposed for robot manipulators. This approach is constructed based on an integration between a fixed-time second-order sliding mode observer (FxTSOSMO) and a fixed-time sliding mode control (FxTSMC) design strategy. First, the FxTSOSMO is developed to estimate the lumped disturbance with a fixed-time convergence. Then, based on the obtained disturbance estimation, the FxTSMC is developed based on a fixed-time sliding surface and a fixed-time reaching strategy to form a global fixed-time convergence of the system. The proposed approach is then applied for fault tolerant control of a PUMA560 robot and compared with other state-of-the-art controllers. The simulation results verify the outstanding fault estimation and fault accommodation capability of the proposed fault diagnosis observer and fault tolerant strategy, respectively.
Mien Van; Dariusz Ceglarek. Robust fault tolerant control of robot manipulators with global fixed-time convergence. Journal of the Franklin Institute 2020, 358, 699 -722.
AMA StyleMien Van, Dariusz Ceglarek. Robust fault tolerant control of robot manipulators with global fixed-time convergence. Journal of the Franklin Institute. 2020; 358 (1):699-722.
Chicago/Turabian StyleMien Van; Dariusz Ceglarek. 2020. "Robust fault tolerant control of robot manipulators with global fixed-time convergence." Journal of the Franklin Institute 358, no. 1: 699-722.
This study proposes a novel adaptive control method to deal with the dead-zone and time delay issues in actuators of vibration control systems. The controller is formulated based on a type-2 fuzzy neural network integrating with a new modification of Riccati-like equation. The developed new type Riccati-like equation is significant as it reduces energy consumption of control inputs to minimum. Two approaches are suggested to improve performance of the system using the basic elements of Riccati equation. In addition, a fuzzy neural network is applied to approximate the unmodeled dynamics and a sliding mode controller is developed to enhance the robustness of the system against uncertainties and disturbances. After proving the stability of the proposed controller via Lyapunov criterion, the effectiveness of the proposed approach is validated based on computer simulation for vibration control of a vehicle seat suspension. It is demonstrated that the unwanted vibrations due to external excitations are well controlled despite of the presence of dead-zone and time delay in actuators. Furthermore, when comparing with other two state-of-the-art robust controllers [23, 36], the proposed controller provides better vibration suppression capacity and requires less energy consumption.
Do Xuan Phu; Van Mien. Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network. Journal of the Franklin Institute 2020, 357, 12281 -12307.
AMA StyleDo Xuan Phu, Van Mien. Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network. Journal of the Franklin Institute. 2020; 357 (17):12281-12307.
Chicago/Turabian StyleDo Xuan Phu; Van Mien. 2020. "Robust control for vibration control systems with dead-zone band and time delay under severe disturbance using adaptive fuzzy neural network." Journal of the Franklin Institute 357, no. 17: 12281-12307.
In this paper, a sliding mode control scheme is developed to stabilise a class of nonlinear perturbed underactuated system with a non-integral momentum. In this scheme, by initially maintaining a subset of actuated variables on sliding manifolds, the underactuated system with the non-integrable momentum can be approximated by one with the integrable momentum in finite time. During sliding, a subset of the actuated variables converge to zero and a physically meaningful diffeomorphism is systematically calculated to transform the reduced order sliding motion into one in a strict feedback normal form in which the control signals are decoupled from the underactuated subsystem. Furthermore, based on the perturbed strict feedback form, it is possible to find a sliding mode control law to ensure the asymptotic stability of the remaining actuated and unactuated variables. The design efficacy is verified via a multi-link planar robot case study.
Lejun Chen; Mien Van. Sliding mode control of a class of underactuated system with non-integrable momentum. Journal of the Franklin Institute 2020, 357, 9484 -9504.
AMA StyleLejun Chen, Mien Van. Sliding mode control of a class of underactuated system with non-integrable momentum. Journal of the Franklin Institute. 2020; 357 (14):9484-9504.
Chicago/Turabian StyleLejun Chen; Mien Van. 2020. "Sliding mode control of a class of underactuated system with non-integrable momentum." Journal of the Franklin Institute 357, no. 14: 9484-9504.
In this study, a new optimal control law associated with sliding mode control is developed based on basis of the Bolza-Meyer criterion. The salient characteristic of the proposed controller is to have gains adjustability, where the gain values can be larger than one. This leads to enhancing control system performances with a given cost function. It should be pointed out that conventional optimal controllers usually have constant gains of one or less than one, and hence the control system performances such as the requirement on convergence speed may not be satisfactory. After formulating the proposed optimal control law for polynomial time-varying control systems, computer simulations are carried out to validate the benefits of the proposed approach. Firstly, as an illustrative example, three crucial index values including control gain index, main input control index and the state index are investigated. Secondly, the proposed controller is applied to a vehicle seat suspension system with magneto-rheological damper to evaluate vibration control performances. In simulation studies, a comparison between the proposed approach and a state-of-the-art optimal controller is undertaken to demonstrate additional benefits such as less power and faster convergence of the proposed optimal controller.
Do Xuan Phu; Van Mien; Phan Huu Thanh Tu; Ngoc Phi Nguyen; Seung-Bok Choi. A new optimal sliding mode controller with adjustable gains based on Bolza-Meyer criterion for vibration control. Journal of Sound and Vibration 2020, 485, 115542 .
AMA StyleDo Xuan Phu, Van Mien, Phan Huu Thanh Tu, Ngoc Phi Nguyen, Seung-Bok Choi. A new optimal sliding mode controller with adjustable gains based on Bolza-Meyer criterion for vibration control. Journal of Sound and Vibration. 2020; 485 ():115542.
Chicago/Turabian StyleDo Xuan Phu; Van Mien; Phan Huu Thanh Tu; Ngoc Phi Nguyen; Seung-Bok Choi. 2020. "A new optimal sliding mode controller with adjustable gains based on Bolza-Meyer criterion for vibration control." Journal of Sound and Vibration 485, no. : 115542.
Bearing is one of the key components of a rotating machine. Hence, monitoring health condition of the bearing is of paramount importace. This paper develops a novel particle swarm optimization (PSO)-least squares wavelet support vector machine (PSO-LSWSVM) classifier, which is designed based on a combination between a PSO, a least squares procedure, and a new wavelet kernel function-based support vector machine (SVM), for bearing fault diagnosis. In this work, bearing fault classification is transformed into a pattern recognition problem, which consists of three stages of data processing. Firstly, a rich information dataset is built by extracting the features from the signals, which are decomposed by the nonlocal means (NLM) and empirical mode decomposition (EMD). Secondly, a minimum-redundancy maximum-relevance (mRMR) method is employed to determine a subset of feature that can provide an optimal performance. Thirdly, a novel classifier, namely LSWSVM, is proposed with the aid of a PSO, to provide higher classification accuracy. The key innovative science of this work is to propropose a new classifier with the aid of an new wavelet kernel type to increase the classification precision of bearing fault diagnosis. The merit features of the proposed approach are demonstrated based on a benchmark bearing dataset and a comprehensive comparison procedure.
Mien Van; Duy Tang Hoang; Hee Jun Kang. Bearing Fault Diagnosis Using a Particle Swarm Optimization-Least Squares Wavelet Support Vector Machine Classifier. Sensors 2020, 20, 3422 .
AMA StyleMien Van, Duy Tang Hoang, Hee Jun Kang. Bearing Fault Diagnosis Using a Particle Swarm Optimization-Least Squares Wavelet Support Vector Machine Classifier. Sensors. 2020; 20 (12):3422.
Chicago/Turabian StyleMien Van; Duy Tang Hoang; Hee Jun Kang. 2020. "Bearing Fault Diagnosis Using a Particle Swarm Optimization-Least Squares Wavelet Support Vector Machine Classifier." Sensors 20, no. 12: 3422.
This paper focuses on motion analysis of a coupled unmanned surface vehicle (USV)–umbilical cable (UC)–unmanned underwater vehicle (UUV) system to investigate the interaction behavior between the vehicles and the UC in the ocean environment. For this, a new dynamic modeling method for investigating a multi-body dynamics system of this coupling system is employed. Firstly, the structure and hardware composition of the proposed system are presented. The USV and UUV are modeled as rigid-body vehicles, and the flexible UC is discretized using the catenary equation. In order to solve the nonlinear coupled dynamics of the vehicles and flexible UC, the fourth-order Runge–Kutta numerical method is implemented. In modeling the flexible UC dynamics, the shooting method is applied to solve a two-point boundary value problem of the catenary equation. The interaction between the UC and the USV–UUV system is investigated through numerical simulations in the time domain. Through the computer simulation, the behavior of the coupled USV–UC–UUV system is analyzed for three situations which can occur. In particular, variation of the UC forces and moments at the tow points and the configuration of the UC in the water are investigated.
Mai The Vu; Mien Van; Duc Hong Phuc Bui; Quang Thang Do; Tuan-Tu Huynh; Sang-Do Lee; Hyeung-Sik Choi. Study on Dynamic Behavior of Unmanned Surface Vehicle-Linked Unmanned Underwater Vehicle System for Underwater Exploration. Sensors 2020, 20, 1329 .
AMA StyleMai The Vu, Mien Van, Duc Hong Phuc Bui, Quang Thang Do, Tuan-Tu Huynh, Sang-Do Lee, Hyeung-Sik Choi. Study on Dynamic Behavior of Unmanned Surface Vehicle-Linked Unmanned Underwater Vehicle System for Underwater Exploration. Sensors. 2020; 20 (5):1329.
Chicago/Turabian StyleMai The Vu; Mien Van; Duc Hong Phuc Bui; Quang Thang Do; Tuan-Tu Huynh; Sang-Do Lee; Hyeung-Sik Choi. 2020. "Study on Dynamic Behavior of Unmanned Surface Vehicle-Linked Unmanned Underwater Vehicle System for Underwater Exploration." Sensors 20, no. 5: 1329.
This paper develops a new strategy for robust fault tolerant control (FTC) of robot manipulators using an adaptive fuzzy integral sliding mode control and a disturbance observer (DO). First, an integral sliding mode control (ISMC) is developed for the FTC system. The major features of the approach are discussed. Then, to enhance performance of the system, a fuzzy logic system (FLS) approximation and a DO are introduced to approximate the unknown nonlinear terms, which include the model uncertainty and fault components, and estimates the compounded disturbance, respectively, and then integrated into the ISMC. Next, a switching term based on an adaptive two-layer super-twisting algorithm is designed to compensate the disturbance estimated error and guarantee stability and convergence of the whole system. The nominal controller of the ISMC is reconstructed using backstepping control technique to achieve stable for the nominal system based on Lyapunov criteria. The computer simulation results demonstrate the effectiveness of the proposed approach.
Mien Van; Shuzhi Sam Ge. Adaptive Fuzzy Integral Sliding-Mode Control for Robust Fault-Tolerant Control of Robot Manipulators With Disturbance Observer. IEEE Transactions on Fuzzy Systems 2020, 29, 1284 -1296.
AMA StyleMien Van, Shuzhi Sam Ge. Adaptive Fuzzy Integral Sliding-Mode Control for Robust Fault-Tolerant Control of Robot Manipulators With Disturbance Observer. IEEE Transactions on Fuzzy Systems. 2020; 29 (5):1284-1296.
Chicago/Turabian StyleMien Van; Shuzhi Sam Ge. 2020. "Adaptive Fuzzy Integral Sliding-Mode Control for Robust Fault-Tolerant Control of Robot Manipulators With Disturbance Observer." IEEE Transactions on Fuzzy Systems 29, no. 5: 1284-1296.
Ant colony optimization is a swarm intelligence metaheuristic inspired by the foraging behavior of some ant species. Ant colony optimization has been successfully applied to challenging optimization problems. This article investigates existing ant colony optimization algorithms specifically designed for combinatorial optimization problems with a dynamic environment. The investigated algorithms are classified into two frameworks: evaporation-based and population-based. A case study of using these algorithms to solve the dynamic traveling salesperson problem is described. Experiments are systematically conducted using a proposed dynamic benchmark framework to analyze the effect of important ant colony optimization features on numerous test cases. Different performance measures are used to evaluate the adaptation capabilities of the investigated algorithms, indicating which features are the most important when designing ant colony optimization algorithms in dynamic environments.
Michalis Mavrovouniotis; Shengxiang Yang; Mien Van; Changhe Li; Marios Polycarpou. Ant Colony Optimization Algorithms for Dynamic Optimization: A Case Study of the Dynamic Travelling Salesperson Problem [Research Frontier]. IEEE Computational Intelligence Magazine 2020, 15, 52 -63.
AMA StyleMichalis Mavrovouniotis, Shengxiang Yang, Mien Van, Changhe Li, Marios Polycarpou. Ant Colony Optimization Algorithms for Dynamic Optimization: A Case Study of the Dynamic Travelling Salesperson Problem [Research Frontier]. IEEE Computational Intelligence Magazine. 2020; 15 (1):52-63.
Chicago/Turabian StyleMichalis Mavrovouniotis; Shengxiang Yang; Mien Van; Changhe Li; Marios Polycarpou. 2020. "Ant Colony Optimization Algorithms for Dynamic Optimization: A Case Study of the Dynamic Travelling Salesperson Problem [Research Frontier]." IEEE Computational Intelligence Magazine 15, no. 1: 52-63.
This paper proposes a robust fault tolerant control scheme for a class of second-order uncertain nonlinear systems. First, a novel PI full-order sliding mode (PI-FOSM) control, which integrates a new PI-FOSM sliding surface and a continuous control law, is developed. The crucial parameters of the controller are optimally selected by Bat algorithm so that the nearly optimal performance of the controller can be achieved. In addition, the unknown system dynamics is approximated by using a radial basic function neural network (RBFNN) so that the proposed controller does not require an exact model of the system. Compared with other existing sliding mode controllers for fault tolerant control system, the proposed method provides very strong robustness, low oscillation, fast convergence and high precision. The superior performance of the proposed robust fault tolerant controller is proved through simulation results for attitude control of a spacecraft.
Mien Van; Xuan Phu Do. Optimal adaptive neural PI full-order sliding mode control for robust fault tolerant control of uncertain nonlinear system. European Journal of Control 2020, 54, 22 -32.
AMA StyleMien Van, Xuan Phu Do. Optimal adaptive neural PI full-order sliding mode control for robust fault tolerant control of uncertain nonlinear system. European Journal of Control. 2020; 54 ():22-32.
Chicago/Turabian StyleMien Van; Xuan Phu Do. 2020. "Optimal adaptive neural PI full-order sliding mode control for robust fault tolerant control of uncertain nonlinear system." European Journal of Control 54, no. : 22-32.
In this study, a new optimal control law associated with the sliding mode control is developed for the linear time-varying system based on the Bolza-Meyer criterion. The salient characteristic of the controller proposed in this work is to have adjustable gains in which the gain values can be larger than 1. This leads to the enhancement of control performances with the given cost function. It is noted here that conventional optimal control laws have a constant gain of 1 or less than 1, and hence, control performances such as the convergence speed are not satisfactory. After formulating the proposed optimal control law for linear time-varying systems, several illustrative examples are adopted and control performances were evaluated to show some benefits of the proposed controller. In particular, three crucial index values of control gain index, main input control index and the state index were investigated. Among illustrative examples, one is related to vibration control problem of the vehicle seat suspension system with magnetorheological (MR) damper. This example is specially treated to evaluate the practical applicability of the proposed optimal controller by considering the measured road profiles; two different random road excitations.
Do Xuan Phu; Van Mien; Seung-Bok Choi. A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems. Applied Sciences 2019, 9, 5050 .
AMA StyleDo Xuan Phu, Van Mien, Seung-Bok Choi. A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems. Applied Sciences. 2019; 9 (23):5050.
Chicago/Turabian StyleDo Xuan Phu; Van Mien; Seung-Bok Choi. 2019. "A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems." Applied Sciences 9, no. 23: 5050.
In this work, a new robust controller is developed for robot manipulator based on an integrating between a novel self-tuning fuzzy proportional–integral–derivative (PID)-nonsingular fast terminal sliding mode control (STF-PID-NFTSM) and a time delay estimation (TDE). A sliding surface based on the PID-NFTSM is designed for robot manipulators to get multiple excited features such as faster transient response with finite time convergence, lower error at steady-state and chattering elimination. However, the system characteristics are hugely affected by the selection of the PID gains of the controller. In addition, the design of the controller requires an exact dynamics model of the robot manipulators. In order to obtain effective gains for the PID sliding surface, a fuzzy logic system is employed and in order to get an estimation of the unknown dynamics model, a TDE algorithm is developed. The innovative features of the proposed approach, i.e., STF-PID-NFTSM, is verified when comparing with other up-to-date advanced control techniques on a PUMA560 robot.
Mien Van; Xuan Phu Do; Michalis Mavrovouniotis. Self-tuning fuzzy PID-nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators. ISA Transactions 2019, 96, 60 -68.
AMA StyleMien Van, Xuan Phu Do, Michalis Mavrovouniotis. Self-tuning fuzzy PID-nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators. ISA Transactions. 2019; 96 ():60-68.
Chicago/Turabian StyleMien Van; Xuan Phu Do; Michalis Mavrovouniotis. 2019. "Self-tuning fuzzy PID-nonsingular fast terminal sliding mode control for robust fault tolerant control of robot manipulators." ISA Transactions 96, no. : 60-68.
In this paper, a new control methodology is developed to enhance the tracking performance of fully actuated surface vessels based on an integrating between an adaptive integral sliding mode control (AISMC) and a disturbance observer (DO). First, an integral sliding mode control (ISMC), in which the backstepping control technique is used as the nominal controller, is designed for the system. The major features, i.e., benefits and drawbacks, of the ISMC are discussed thoroughly. Then, to enhance the tracking performance of the system, an adaptive technique and a new disturbance observer based on sliding mode technique are developed and integrated into the ISMC. The stability of the closed-loop system is proved based on Lyapunov criteria. Computer simulation is performed to illustrate the tracking performance of the proposed controller and compare with the existing controllers for the tracking control of a surface vessel. The simulation results demonstrate the superior performance of the proposed strategy.
Mien Van. An enhanced tracking control of marine surface vessels based on adaptive integral sliding mode control and disturbance observer. ISA Transactions 2019, 90, 30 -40.
AMA StyleMien Van. An enhanced tracking control of marine surface vessels based on adaptive integral sliding mode control and disturbance observer. ISA Transactions. 2019; 90 ():30-40.
Chicago/Turabian StyleMien Van. 2019. "An enhanced tracking control of marine surface vessels based on adaptive integral sliding mode control and disturbance observer." ISA Transactions 90, no. : 30-40.
This paper develops a novel adaptive neural integral sliding‐mode control to enhance the tracking performance of fully actuated uncertain surface vessels. The proposed method is built based on an integrating between the benefits of the approximation capability of neural network (NN) and the high robustness and precision of the integral sliding‐mode control (ISMC). In this paper, the design of NN, which is used to approximate the unknown dynamics, is simplified such that just only one simple adaptive rule is needed. The ISMC, which can eliminate the reaching phase and offer higher tracking performance compared to the conventional sliding‐mode control, is designed such that the system robust against the approximation error and stabilize the whole system. The design procedure of the proposed controller is constructed according to the backstepping control technique so that the stability of the closed‐loop system is guaranteed based on Lyapunov criteria. The proposed method is then tested on a simulated vessel system using computer simulation and compared with other state‐of‐the‐art methods. The comparison results demonstrate the superior performance of the proposed approach.
Mien Van. Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels. International Journal of Robust and Nonlinear Control 2018, 29, 1537 -1557.
AMA StyleMien Van. Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels. International Journal of Robust and Nonlinear Control. 2018; 29 (5):1537-1557.
Chicago/Turabian StyleMien Van. 2018. "Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels." International Journal of Robust and Nonlinear Control 29, no. 5: 1537-1557.
This work proposes a novel composite adaptive controller based on the prescribed performance of the sliding surface and applies it to vibration control of a semi-active vehicle seat suspension system subjected to severe external disturbances. As a first step, the online fast interval type 2 fuzzy neural network system is adopted to establish a model and two sliding surfaces are used; conventional surface and prescribed surface. Then, an equivalent control is determined by assuming the derivative of the prescribed surface is zero, followed by the design of a controller which can guarantee both stability and robustness. Then, two controllers are combined and integrated with adaptation laws using the projection algorithm. The effectiveness of the proposed composite controller is validated through both simulation and experiment by undertaking vibration control of a semi-active seat suspension system equipped with a magneto-rheological (MR) damper. It is shown from both simulation and experimental realization that excellent vibration control performances are achieved with a small tracking error between the proposed and prescribed objectives. In addition, the control superiority of the proposed controller to conventional sliding mode controller featuring one sliding surface and proportional-integral-derivative (PID) controllers are demonstrated through a comparative work.
Do Xuan Phu; Ta Duc Huy; Van Mien; Seung-Bok Choi. A new composite adaptive controller featuring the neural network and prescribed sliding surface with application to vibration control. Mechanical Systems and Signal Processing 2018, 107, 409 -428.
AMA StyleDo Xuan Phu, Ta Duc Huy, Van Mien, Seung-Bok Choi. A new composite adaptive controller featuring the neural network and prescribed sliding surface with application to vibration control. Mechanical Systems and Signal Processing. 2018; 107 ():409-428.
Chicago/Turabian StyleDo Xuan Phu; Ta Duc Huy; Van Mien; Seung-Bok Choi. 2018. "A new composite adaptive controller featuring the neural network and prescribed sliding surface with application to vibration control." Mechanical Systems and Signal Processing 107, no. : 409-428.
This paper develops an enhanced robust fault tolerant control using a novel adaptive fuzzy proportional-integral-derivative-based nonsingular fast terminal sliding mode (AF-PID-NFTSM) control for a class of second-order uncertain nonlinear systems. In this approach, a new type of sliding surface, called proportional-integral-derivative (PID)-nonsingular fast terminal sliding mode (NFTSM) (PID-NFTSM) which combines the benefits of the PID and NFTSM sliding surfaces, is proposed to enhance the robustness and reduce the steady-state error, whilst preserving the great property of the conventional NFTSM controller. A fuzzy approximator is designed to approximate the uncertain system dynamics and an adaptive law is developed to estimate the bound of the approximation error so that the proposed robust controller does not require a need of the prior knowledge of the bound of the uncertainties and faults and the exact system dynamics. The proposed approach is then applied for attitude control of a spacecraft. The simulation results verify the superior performance of the proposed approaches over other existing advanced robust fault tolerant controllers.
Mien Van. An Enhanced Robust Fault Tolerant Control Based on an Adaptive Fuzzy PID-Nonsingular Fast Terminal Sliding Mode Control for Uncertain Nonlinear Systems. IEEE/ASME Transactions on Mechatronics 2018, 23, 1362 -1371.
AMA StyleMien Van. An Enhanced Robust Fault Tolerant Control Based on an Adaptive Fuzzy PID-Nonsingular Fast Terminal Sliding Mode Control for Uncertain Nonlinear Systems. IEEE/ASME Transactions on Mechatronics. 2018; 23 (3):1362-1371.
Chicago/Turabian StyleMien Van. 2018. "An Enhanced Robust Fault Tolerant Control Based on an Adaptive Fuzzy PID-Nonsingular Fast Terminal Sliding Mode Control for Uncertain Nonlinear Systems." IEEE/ASME Transactions on Mechatronics 23, no. 3: 1362-1371.
This paper develops a novel control methodology for tracking control of robot manipulators based on a novel adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC). In this approach, a novel backstepping nonsingular fast terminal sliding mode controller (BNFTSMC) is developed based on an integration of integral nonsingular fast terminal sliding mode surface and a backstepping control strategy. The benefits of this approach are that the proposed controller can preserve the merits of the integral nonsingular fast terminal sliding mode control (NFTSMC) in terms of high robustness, fast transient response, and finite-time convergence, as well as backstepping control strategy in terms of globally asymptotic stability based on Lyapunov criterion. However, the major limitation of the proposed BNFTSMC is that its design procedure is dependent on the prior knowledge of the bound value of the disturbance and uncertainties. In order to overcome this limitation, an adaptive technique is employed to approximate the upper bound value; yielding an ABNFTSMC is recommended. The proposed controller is then applied for tracking control of a PUMA560 robot and compared with other state-of-the-art controllers, such as computed torque controller, PID controller, conventional PID-based sliding mode controller, and NFTSMC. The comparison results demonstrate the superior performance of the proposed approach.
Mien Van; Michalis Mavrovouniotis; Shuzhi Sam Ge. An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2018, 49, 1448 -1458.
AMA StyleMien Van, Michalis Mavrovouniotis, Shuzhi Sam Ge. An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2018; 49 (7):1448-1458.
Chicago/Turabian StyleMien Van; Michalis Mavrovouniotis; Shuzhi Sam Ge. 2018. "An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators." IEEE Transactions on Systems, Man, and Cybernetics: Systems 49, no. 7: 1448-1458.