| 1. |
|
|
| 2. |
- Lin, Hongyi, et al.
(författare)
-
How generative adversarial networks promote the development of intelligent transportation systems: A survey
- 2023
-
Ingår i: IEEE/CAA Journal of Automatica Sinica. - 2329-9274 .- 2329-9266. ; 10:9, s. 1781-1796
-
Tidskriftsartikel (refereegranskat)abstract
- In current years, the improvement of deep learning has brought about tremendous changes: As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) have been widely employed in various fields including transportation. This paper reviews the development of GANs and their applications in the transportation domain. Specifically, many adopted GAN variants for autonomous driving are classified and demonstrated according to data generation, video trajectory prediction, and security of detection. To introduce GANs to traffic research, this review summarizes the related techniques for spatio-temporal, sparse data completion, and time-series data evaluation. GAN-based traffic anomaly inspections such as infrastructure detection and status monitoring are also assessed. Moreover, to promote further development of GANs in intelligent transportation systems (ITSs), challenges and noteworthy research directions on this topic are provided. In general, this survey summarizes 130 GAN-related references and provides comprehensive knowledge for scholars who desire to adopt GANs in their scientific works, especially transportation-related tasks.
|
|
| 3. |
- Pham, Tuan, Professor, 1962-, et al.
(författare)
-
Classification of Short Time Series in Early Parkinson’s Disease With Deep Learning of Fuzzy Recurrence Plots
- 2019
-
Ingår i: IEEE/CAA Journal of Automatica Sinica. - 2329-9266 .- 2329-9274. ; 6:6, s. 1306-1317
-
Tidskriftsartikel (refereegranskat)abstract
- There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson's disease (PD). A recent development is the utilization of human interaction with computer keyboards for analyzing and identifying motor signs in the early stages of the disease. Current designs for classification of time series of computer-key hold durations recorded from healthy control and PD subjects require the time series of length to be considerably long. With an attempt to avoid discomfort to participants in performing long physical tasks for data recording, this paper introduces the use of fuzzy recurrence plots of very short time series as input data for the machine training and classification with long short-term memory (LSTM) neural networks. Being an original approach that is able to both significantly increase the feature dimensions and provides the property of deterministic dynamical systems of very short time series for information processing carried out by an LSTM layer architecture, fuzzy recurrence plots provide promising results and outperform the direct input of the time series for the classification of healthy control and early PD subjects.
|
|
| 4. |
- Wang, Zeguo, et al.
(författare)
-
Periodic Motion Planning and Control for Double Rotary Pendulum via Virtual Holonomic Constraints
- 2019
-
Ingår i: IEEE/CAA Journal of Automatica Sinica. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266 .- 2329-9274. ; 6:1, s. 291-298
-
Tidskriftsartikel (refereegranskat)abstract
- Periodic motion planning for an under-actuated system is rather difficult due to differential dynamic constraints imposed by passive dynamics, and it becomes more difficult for a system with higher underactuation degree, that is with a higher difference between the number of degrees of freedom and the number of independent control inputs. However, from another point of view, these constraints also mean some relation between state variables and could be used in the motion planning. We consider a double rotary pendulum, which has an underactuation degree 2. A novel periodic motion planning is presented based on an optimization search. A necessary condition for existence of the whole periodic trajectory is given because of the higher underactuation degree of the system. Moreover this condition is given to make virtual holonomic constraint (VHC) based control design feasible. Therefore, an initial guess for the optimization of planning a feasible periodic motion is based on this necessary condition. Then, VHCs are used for the system transformation and transverse linearization is used to design a static state feedback controller with periodic matrix function gain. The controller gain is found through another optimization procedure. The effectiveness of initial guess and performance of the closed-loop system are illustrated through numerical simulations.
|
|
| 5. |
- Gao, Shigen, et al.
(författare)
-
High-Speed Trains Automatic Operation with Protection Constraints : A Resilient Nonlinear Gain-based Feedback Control Approach
- 2019
-
Ingår i: IEEE-CAA JOURNAL OF AUTOMATICA SINICA. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2329-9266. ; 6:4, s. 992-999
-
Tidskriftsartikel (refereegranskat)abstract
- This paper addresses the control design for automatic train operation of high-speed trains with protection constraints. A new resilient nonlinear gain-based feedback control approach is proposed, which is capable of guaranteeing, under some proper non-restrictive initial conditions, the protection constraints control raised by the distance-to-go (moving authority) curve and automatic train protection in practice. A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains. The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability, no adaptations of unknown parameters, function approximation of unknown nonlinearities, and attenuation of external disturbances in the proposed control strategies. Finally, rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.
|
|
| 6. |
- Ge, Quanbo, et al.
(författare)
-
A Novel Adaptive Kalman Filter Based on Credibility Measure
- 2023
-
Ingår i: IEEE-CAA JOURNAL OF AUTOMATICA SINICA. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266. ; 10:1, s. 103-120
-
Tidskriftsartikel (refereegranskat)abstract
- It is quite often that the theoretic model used in the Kalman filtering may not be sufficiently accurate for practical applications, due to the fact that the covariances of noises are not exactly known. Our previous work reveals that in such scenario the filter calculated mean square errors (FMSE) and the true mean square errors (TMSE) become inconsistent, while FMSE and TMSE are consistent in the Kalman filter with accurate models. This can lead to low credibility of state estimation regardless of using Kalman filters or adaptive Kalman filters. Obviously, it is important to study the inconsistency issue since it is vital to understand the quantitative influence induced by the inaccurate models. Aiming at this, the concept of credibility is adopted to discuss the inconsistency problem in this paper. In order to formulate the degree of the credibility, a trust factor is constructed based on the FMSE and the TMSE. However, the trust factor can not be directly computed since the TMSE cannot be found for practical applications. Based on the definition of trust factor, the estimation of the trust factor is successfully modifled to online estimation of the TMSE. More importantly, a necessary and sufficient condition is found, which turns out to be the basis for better design of Kalman filters with high performance. Accordingly, beyond trust factor estimation with Sage-Husa technique (TFE-SHT), three novel trust factor estimation methods, which are directly numerical solving method (TFE-DNS), the particle swarm optimization method (PSO) and expectation max-imization-particle swarm optimization method (EM-PSO) are proposed. The analysis and simulation results both show that the proposed TFE-DNS is better than the TFE-SHT for the case of single unknown noise covariance. Meanwhile, the proposed EM-PSO performs completely better than the EM and PSO on the estimation of the credibility degree and state when both noise covariances should be estimated online.
|
|
| 7. |
- He, Xiaodong, et al.
(författare)
-
Exponential Set-Point Stabilization of Underactuated Vehicles Moving in Three-Dimensional Space
- 2022
-
Ingår i: IEEE/CAA Journal of Automatica Sinica. - 2329-9266. ; 9:2, s. 270-282
-
Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the stabilization of underactuated vehicles moving in a three-dimensional vector space. The vehicle's model is established on the matrix Lie group SE(3), which describes the configuration of rigid bodies globally and uniquely. We focus on the kinematic model of the underactuated vehicle, which features an underactuation form that has no sway and heave velocity. To compensate for the lack of these two velocities, we construct additional rotation matrices to generate a motion of rotation coupled with translation. Then, the state feedback is designed with the help of the logarithmic map, and we prove that the proposed control law can exponentially stabilize the underactuated vehicle to the identity group element with an almost global domain of attraction. Later, the presented control strategy is extended to set-point stabilization in the sense that the underactuated vehicle can be stabilized to an arbitrary desired configuration specified in advance. Finally, simulation examples are provided to verify the effectiveness of the stabilization controller.
|
|
| 8. |
- Wei, A., et al.
(författare)
-
Tracking control of leader-follower multi-agent systems subject to actuator saturation
- 2014
-
Ingår i: IEEE/CAA Journal of Automatica Sinica. - 2329-9266. ; 1:1, s. 84-91
-
Tidskriftsartikel (refereegranskat)abstract
- This paper addresses the tracking problem of leader-follower multi-agent systems subject to actuator saturation. A leader node or command generator is considered, which generates the desired tracking trajectory. To track such a leader, a new family of scheduled low-and-high-gain feedback controllers is designed for each follower, provided that the linear dynamic mode is asymptotically null controllable with bounded controls, and such control laws rely on the asymptotic property of a class of parametric algebraic Ricatti equations. We show that if the associated undirected graph of the system is connected, with the proposed control law, all the followers can track the leader eventually. A simulation example is finally given to illustrate the performance of the proposed control scheme.
|
|
| 9. |
- Yi, Xinlei, et al.
(författare)
-
A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization
- 2022
-
Ingår i: IEEE-CAA JOURNAL OF AUTOMATICA SINICA. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266. ; 9:5, s. 812-833
-
Tidskriftsartikel (refereegranskat)abstract
- The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal-dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We show that the proposed algorithm achieves the linear speedup convergence rate O(1/root nT) for general nonconvex cost functions and the linear speedup convergence rate O(1/nT)) when the global cost function satisfies the Polyak-Lojasiewicz (P-L) condition, where T is the total number of iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.
|
|
| 10. |
|
|
| 11. |
- Zhang, Yinlong, et al.
(författare)
-
Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework
- 2022
-
Ingår i: IEEE/CAA journal of automatica sinica. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-9266. ; 9:1, s. 146-159
-
Tidskriftsartikel (refereegranskat)abstract
- Reliable and accurate calibration for camera, inertial measurement unit (IMU) and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception. However, traditional calibrations suffer inaccuracy and inconsistency. To address these problems, this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework. In our method, the spatial relationship is geometrically correlated between the sensing units and robotic arm. The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization. Additionally, the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently. The calibration has been evaluated on our developed platform. In the experiments, the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7 degrees and 0.01 m, respectively. The comparisons with state-of-the-art results prove our calibration consistency, accuracy and effectiveness.
|
|
