The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming t...
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ISBN:
(数字)9798350372601
ISBN:
(纸本)9798350372618
The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities.
作者:
Tao YangShize QinFang XuSongbo DengHao ZhangYan ShiState Key Laboratory of Robotics
Chinese Academy of Sciences Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing PR China Laboratory of Aerospace Servo Actuation and Transmission
Beijing Institute of Precision Mechatronics and Controls Beijing PR China State Key Laboratory of Robotics
Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang PR China
To achieve the goal of an efficient full-state ground test of a 7DOF space manipulator, the kinematic and dynamical coupling characteristics of space manipulator are investigated, and a mirror test method based on the...
To achieve the goal of an efficient full-state ground test of a 7DOF space manipulator, the kinematic and dynamical coupling characteristics of space manipulator are investigated, and a mirror test method based on the principle of multiple decoupling is proposed to solve the problem of highly dynamic three-dimensional motion conditions of space manipulator that are difficult to verify by ground simulation. It firstly decouples the space manipulator into a 3dof unit,1dof unit and another 3dof unit combination. It achieves joint load reduction through inter-joint dynamics coupling. Afterwards, it designs an air-floating support device to realize the joint space 7DOF motion, and proposes a constant damping joint dynamics compensation control algorithm to eliminate the dynamics disturbances introduced by inter-joint decoupling. Then, an industrial mirror robot arm with consistent kinematic parameters and a highly dynamic mirror control algorithm are designed to map the joint motion states of the space manipulator to the ground robotic arm, and a ground simulation of the Cartesian space motion state of the space robot arm is realized by decoupling the joint space from the Cartesian space motion. Finally, the ground experiment of target grasping based on the physical mirroring method is designed to realize the high-speed full-state ground experiment verification of complex tasks of space manipulator.
Residential electricity consumption data have great mining value for electricity-theft analysis and electricity consumption forecasting. This paper designs an intelligent electricity consumption forecasting and electr...
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The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risk...
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作者:
Zehao WangHan ZhangJingchuan WangDepartment of Automation
Institute of Medical Robotics Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China
Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propos...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC.
Hip joint moments during walking are the key foundation for hip exoskeleton assistance control. Most recent studies have shown estimating hip joint moments instantaneously offers a lot of advantages compared to genera...
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To improve the operation efficiency and real-time scheduling capability of existing industrial control network systems, based on the existing industrial real-time Ethernet communication protocol technology, an industr...
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ISBN:
(数字)9798350385557
ISBN:
(纸本)9798350385564
To improve the operation efficiency and real-time scheduling capability of existing industrial control network systems, based on the existing industrial real-time Ethernet communication protocol technology, an industrial real-time Ethernet scheduling method based on time slot reuse is proposed. This method adopts the time-division multiplexing strategy, decomposes the continuous time into different time slots, configures the data of different types of nodes to be transmitted in their respective time slots, uses the peak shift clock synchronization method and timer trigger task mechanism to improve the real-time communication, and uses the time slot multiplexing mechanism to improve the data transmission efficiency; Finally, a test platform is built to verify the proposed method. The experimental results show that the proposed method has high clock synchronization accuracy and real-time scheduling capability.
Motor imagery (MI) EEG-based brain-computer interface (BCI) facilitates direct communication between the brain’s intentions and a computer. In essence, it allows a person to control external equipment by decoding EEG...
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ISBN:
(数字)9798350391916
ISBN:
(纸本)9798350391923
Motor imagery (MI) EEG-based brain-computer interface (BCI) facilitates direct communication between the brain’s intentions and a computer. In essence, it allows a person to control external equipment by decoding EEG signals during the mental imagery of limb movements. However, due to the intricate individual variances in EEG signals, creating a general decoding model with parameters applicable to all subjects is exceptionally challenging. Consequently, a prolonged calibration process is necessary to gather labeled subject-specific data for each individual, making it less user-friendly. A potential solution to this problem is transfer learning, a methodology that transfers knowledge from related domains to a target domain. To tackle the problem, this paper proposes a novel transfer learning approach on the Riemannian manifold framework in the context of multiclass MI EEG-based BCI classification. Particularly, a user-specific frequency band selection (FBS) method with MI EEG class distinctiveness is utilized to improve the accuracy and efficiency of Riemannian space calculations, which is measured using the inter-class distance and intra-class variance on the manifold. Then, the Riemannian space Alignment (RA) strategy is used to calibrate the MI EEG variances of different subjects. The comparative experiments between the proposed approach and baseline/conventional methods are conducted on a public dataset with four-class motor imagery EEG, including two-class transfer learning scenario and four-class transfer learning scenario. proposed transfer learning approach is outperformed. Compared with the baseline/conventional methods using a fixed wide frequency band, the preliminary results suggests that the proposed approach can significantly improve the transfer learning performance for the MI EEG signals from different subjects in Riemannian space.
Laser beams with ns pulse width are generally employed as an excitation source in the process of detecting inclusions and elemental segregation on a workpiece surface by microanalysis of the laser-induced breakdown **...
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Laser beams with ns pulse width are generally employed as an excitation source in the process of detecting inclusions and elemental segregation on a workpiece surface by microanalysis of the laser-induced breakdown *** addition,the ablation crater interval of laser sampling on the sample surface is generally 20μm or *** is difficult to detect the morphology of inclusions smaller than 50μm in diameter and the micro-segregation of ***,in this work,when the laser ablation crater is 10μm and the sampling resolution of the laser on the sample surface is 5μm,the morphology and distribution of spherical inclusions(20–60μm)in ductile iron can be detected according to the difference of the Fe spectrum on the Fe matrix and the spheroidal ***,the distribution of micro-segregation of Mg and Ti elements in ductile iron was also studied.
Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechani...
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