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Model and Simulation of Multipath Error in DLL for GPS Receiver

Chinese Journal of Electronics 2025年第3期23卷 508-515页

作者： Lan Cheng Jie Chen Gang Xie Taiyuan University of Technology Taiyuan China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Although different multipath error models of Delay lock loop (DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product (DOT) power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expression, is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.

关键词： Analytical models Tracking loops Codes Error analysis Simulation Receivers US Department of Transportation Mathematical models MATLAB Global Positioning system

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Design and development of a new autonomous transportation robot for finished vehicles docking transportation in RO/RO logistics terminal

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Advanced Engineering Informatics 2025年 66卷

作者： Xu, Yongkang Zhang, Lin Liu, Zhi Wang, Shoukun Wang, Junzheng State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

With the continuous growth of the automobile trade, the inefficiency of traditional cargo transshipment in Roll-On/Roll-Off (RO/RO) terminals has become increasingly pronounced. As a result, the adoption of autonomous transportation robot (ATR) for the automatic handling of finished vehicles has seen significant growth. However, ATRs designed for this purpose face several limitations, including suboptimal mobility performance and the necessity for additional infrastructure to support their operation. This paper introduces a novel ATR that offers enhanced flexibility and operational capability. To further optimize the positioning of LiDAR, we develop a multi-stage LiDAR fusion algorithm for the precise localization of finished vehicles, incorporating an event-triggered decision-making approach to improve positioning accuracy. Based on the accurate positioning data, we propose a docking strategy consisting of two key phases: the approach phase and the docking phase. During the docking phase, an enhanced Model Predictive control (MPC) algorithm, integrated with a Radial Basis Function (RBF) neural network, is designed to enable real-time adjustment of the robot's docking attitude. The effectiveness of the proposed approach is validated through real-world robot experimentals demonstrating its practical viability. © 2025

关键词： Autonomous vehicles

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A MPC-based Planner Applied on a Parallel Wheel-legged Robot for Obstacle Avoidance 25

A MPC-based Planner Applied on a Parallel Wheel-legged Robot...

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Proceedings of the 4th International Conference on Computer, Artificial Intelligence and control Engineering

作者： Fei Guo Huan Yu Wanhong Lin Shoukun Wang National Key Laboratory of Human Factors Engineering China Astronaut Research and Training Center Beijing China Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9798400712647

A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effectively improves the terrain adaptability, which concerns our planning concentration. We introduced an optimization-based whole-body trajectory planning algorithm to navigate robot in rugged terrain. The planner combines terrain data and stability, allowing lower-level motion generator and controller to operate more efficiently. The Model Predictive control(MPC)-based method updates the footholds and CoG trajectories, which builds upon the support polygon constraints on optimization. The simulations of methodology working in several structure-obstacle scene demonstrated and compared the availability of approach.

关键词： Reconfigurable robot

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Hybrid optimization of dynamic deployment for networked fire control system

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Journal of systems Engineering and Electronics 2013年第6期24卷 954-961页

作者： Chen Chen Jie Chen Bin Xin School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.

关键词： deployment optimization artificial potential field （APF） constraint handling generation of feasible solutions memetic algorithm

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Trajectory synchronization of multi-cylinder electrohydraulic lift system with huge load

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Journal of Beijing Institute of Technology 2013年第2期22卷 228-234页

作者：何玉东王军政李静赵江波 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

A kind of four degree-of-freedom （DOF） electrohydraulic lift system is studied in this pa- per, after analyzing the motion characteristics and the mathematic model of the hydraulic cylinders, a cross-coupled synchronization method with load force and synchronization error feedback had been proposed to solve the synchronization problem encountered when realizing the needed roll and pitch attitude of the lift system. In this paper, mathematic model of asymmetric hydraulic cylinder was es- tablished and the lift system had been simplified to a dual-cylinder system. By incorporating the load force and the displacement of each cylinder, a cross-coupled synchronized control method was pro- posed to fit each cylinder＇ s tracking performance and multi-cylinder＇ s trajectory synchronization property. The proposed method not only solved the synchronization problem when multi-cylinder had a same trajectory, but also could fit the coordinated synchronization need when different trajectories of multi-cylinder were desired. Simulations and experiments on a four DOF electrohydraulic lift sys- tem with load of 100 tons verified the effectiveness of the proposed method.

关键词： hydraulic cylinder lift system trajectory synchronization

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Effective approach for outdoor obstacle detection by clustering LIDAR data context

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Journal of Beijing Institute of Technology 2016年第4期25卷 483-490页

作者：王军政乔佳楠李静 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.

关键词： context modeling clustering algorithm based on fast search and discovery of densitypeaks（CBFD） Hull algorithm obstacle detection obstacle fusion

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Motion Planning Method for Obstacle Avoidance of 6-DOF Manipulator Based on Improved A* Algorithm

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Journal of Donghua University(English Edition) 2015年第1期32卷 79-85页

作者：汪首坤朱磊 Key Laboratory of Intelligent Control and Decision for Complex System Beijing Institute of Technology

The conventional A* algorithm may suffer from the infinite loop and a large number of search data in the process of motion planning for manipulator. To solve the problem,an improved A* algorithm is proposed in this paper by the means of selecting middle points and applying variable step segments searching during the searching process. In addition,a new method is proposed for collision detection in the workspace. In this paper,the MOTOMAN MH6 manipulator with 6-DOF is applied for motion plan. The algorithm is based on the basis of the simplification for the manipulator and obstacles by cylinder enveloping. Based on the analysis of collision detection,the free space can be achieved which makes it possible for the entire body to avoid collisions with obstacles. Compared with the Conventional A*,the improved algorithm deals with less searching points and performs more efficiently. The simulation developed in VC + + with OpenGL and the actual system experiments prove effectiveness and feasibility of this improved method.

关键词： manipulator collision detection A* algorithm variable step segments searching OpenGL

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A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

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Chinese Journal of Aeronautics 2014年第3期27卷 622-633页

作者： Zhang Xing Chen Jie Xin Bin Peng Zhihong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.

关键词： Approximate gradient Dubins traveling salesmanproblem with neighborhood Local search Memetic algorithm Unmanned aerial vehicles

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Online adaptive Q-learning method for fully cooperative linear quadratic dynamic games

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Science China(Information Sciences) 2019年第12期62卷 164-177页

作者： Xinxing LI Zhihong PENG Lei JIAO Lele XI Junqi CAI School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.

关键词： adaptive dynamic programming reinforcement learning Q-learning fully cooperative linear quadratic dynamic games policy iteration off-policy

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