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Three-Dimensional Optimal Trajectory Tracking control of Underactuated Autonomous Underwater Vehicles Using Double Closed-Loop control 5

Three-Dimensional Optimal Trajectory Tracking Control of Und...

引用

5th International Conference on Intelligent Autonomous Systems, ICoIAS 2022

作者： Gong, Huibin Joo, Meng Liu, Tianhe Zhao, Xudong Institute of Artificial Intelligence and Marine Robotics College of Marine Electrical Engineering Dalian Maritime University Dalian China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

In this paper, a double closed-loop control method is proposed for three-dimensional optimal trajectory tracking control of underactuated autonomous underwater vehicles (AUVs), Firstly, a five-degree-of-freedom mathematical model of under-Actuated AUV is established. Secondly, an output redefinition method is adopted to solve underactuated control problem. On this basis, a backstepping method is utilized to design the outer-loop controller where virtual velocity is derived using the error between input and output of the system. Next, an adaptive dynamic programming method is used to design the inner-loop controller, where the performance index function containing the disturbance upper bound is set, and a neural network is employed to solve the Hamilton-Jacobi-Bellman equation online. Finally, the Lyapunov theorem is used to establish that all signals of the closed-loop system are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed method. © 2022 IEEE.

关键词： Autonomous underwater vehicles

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The inverse kinematics analysis of the novel 6-DOF parallel mechanism

The inverse kinematics analysis of the novel 6-DOF parallel ...

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International Conference on Machine Learning and Cybernetics

作者： Wang, Hong-Rui Wang, Qing-Quan Alexander, Malikov Liu, Xiu-Ling Dong, Bin Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qin Huang Dao 066004 China Lab of Electronic and Information Engeering Hebei University Baoding 071002 China Kazan State Technical University Kazan Russia

ISBN: (纸本)9781424465262

In this paper, we present the inverse kinematical of a novel 6-DOF orthogonal parallel mechanism. The displacements Δli (i=1,...,6) of steering gears were deduced from the position and orientation of the moving platform. The desired trajectory was assumed to be more complex nonlinear curves, simulations are performed for the real time trajectory tracking of the mechanism. By using Matlab.software, the analysis and simulation of mechanism can be carried out conveniently, and the efficiency of the design can be upgraded. The simulation curves of each displacement were provided and analyzed though simulative research. The results will be used for synthesis of the control law in the form of error feedback, and measurements results of actual movements by means of sensors. The analysis can help to realize the trajectory tracking control fast and accurately. © 2010 IEEE.

关键词： Inverse kinematics

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Modeling parameter interactions in ranking SVM 15

Modeling parameter interactions in ranking SVM

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24th ACM International Conference on Information and Knowledge Management, CIKM 2015

作者： Zhang, Yaogong Xu, Jun Lan, Yanyan Guo, Jiafeng Xie, Maoqiang Huang, Yalou Cheng, Xueqi College of Computer and Control Engineering Nankai University China CAS Key Lab. of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China College of Software Nankai University China

ISBN: (纸本)9781450337946

Ranking SVM, which formalizes the problem of learning a ranking model as that of learning a binary SVM on preference pairs of documents, is a state-of-the-art ranking model in information retrieval. The dual form solution of Ranking SVM model can be written as a linear combination of the preference pairs, i.e., w = Σ(i,j)αij(xi - xj), where αij denotes the Lagrange parameters associated with each pair (i,j). It is obvious that there exist significant interactions over the document pairs because two preference pairs could share a same document as their items. Thus it is natural to ask if there also exist interactions over the model parameters αij, which we may leverage to propose better ranking model. This paper aims to answer the question. Firstly, we found that there exists a low-rank structure over the Ranking SVM model parameters αij, which indicates that the interactions do exist. Then, based on the discovery, we made a modification on the original Ranking SVM model by explicitly applying a low-rank constraint to the parameters. Specifically, each parameter αij is decomposed as a product of two low-dimensional vectors, i.e., αij = (υi,υj), where vectors vi and vj correspond to document i and j, respectively. The learning process, thus, becomes to optimize the modified dual form objective function with respect to the low-dimensional vectors. Experimental results on three LETOR datasets show that our method, referred to as Factorized Ranking SVM, can outperform state-of-the-art baselines including the conventional Ranking SVM. © 2015 ACM.

关键词： Information retrieval

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Tumor gene expressive data classification based on locally linear representation Fisher criterion

Tumor gene expressive data classification based on locally l...

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Li, Bo Tian, Bei-Bei Liu, Jin School of Computer Science and Technology Wuhan University of Science and Technology 430081 Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China State Key Lab. of Software Engineering Wuhan China

ISBN: (纸本)9783642394812

In this paper, a discriminant manifold learning method based on Locally Linear Embedding (LLE), which is named Locally Linear Representation Fisher Criterion (LLRFC), is proposed for the classification of tumor gene expressive data. In the proposed LLRFC, an inter-class graph and intra-class graph is constructed based on the class information of tumor gene expressive data, where the weights between nodes in both graph are optimized using locally linear representation trick. Moreover, a Fisher criterion is modeled to maximize the inter-class scatter and minimize the intra-class scatter simultaneously. Experiments on some benchmark tumor gene expressive data validate its efficiency. © 2013 Springer-Verlag.

关键词： Genes

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An Improved NSGAII Algorithm for Flexible Job-shop Scheduling Problem Based on A New Decoding Mechanism

An Improved NSGAII Algorithm for Flexible Job-shop Schedulin...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Man Li Kai Ma Shiliang Guo Shuai Li Bin Yang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

The flexible job-shop scheduling problem (FJSP) is a famous combinatorial optimization problem. FJSP is widely used in process manufacturing industry, so it is of great significance to study FJSP to improve production efficiency. In this paper, a non-dominated sorting genetic algorithm II based on a new decoding mechanism (NSGAII_NDM) is proposed. Firstly, the opposite-based learning strategy is introduced on the basis of NSGAII, and the sufficiency of global search is improved by generating the opposite value. Secondly, an improved adaptive crossover and mutation probability strategy is added, which can dynamically adjust the inherent crossover and mutation probability with the number of iterations and improve the convergence speed of the algorithm. Furthermore, based on fully active scheduling strategy, a new decoding mechanism is proposed, which can get a better scheduling scheme by arranging the machines and starting time of each process more reasonably. Finally, the improved algorithm is tested in a standard test case, which verifies the superiority of NSGAII_NDM in solving the flexible job-shop scheduling problem.

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Cooperative Spectrum Sensing Based on Double Thresholds Energy Detection over Imperfect Reporting Channels

Cooperative Spectrum Sensing Based on Double Thresholds Ener...

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International Conference on Instrumentation, Measurement, computer, Communication and control (IMCCC)

作者： Zi Zhang Xinbin Li Zhixin Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei China

ISBN: (纸本)9781467377249

In this paper, the problem of hierarchical cooperative spectrum sensing using double thresholds energy detector over imperfect reporting channels will be investigated. When taking error effect on reporting decision into consideration, the sensing performance will be affected. In the proposed scheme, we analyze the performance of hierarchical cooperative spectrum sensing over imperfect reporting channels and the "majority-decision-aided" weighting rule will be used in the fusion center. The analysis and simulation results show that there is a significant performance loss when the decisions based on hierarchical spectrum sensing are transmitted over imperfect reporting channels and the sensing performance is improved by employing the new weighting rule.

关键词： Sensors Cognitive radio Signal to noise ratio computers Propagation losses Reliability Fading channels

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A fuzzy-PI hybrid controller based on a disturbance observer

A fuzzy-PI hybrid controller based on a disturbance observer

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International Conference on Natural Computation (ICNC)

作者： Manjun Cai Yue Wang Key lab of industrial computer control engineering in Hebei province Yanshan University Qinhuangdao China

This paper proposes a fuzzy PI hybrid speed controller for a PMSLM (Permanent Magnet Synchronous Linear Motor), which is based on a friction disturbance observer. It can improve the problems caused by the friction disturbance and the system parameters perturbation. Also the problem of the blind area for fuzzy control is eventually eliminated, because of the introduction of the PI control. Finally, through the simulation test and comparative analysis with the traditional PID control method, the validity and rationality of the control scheme is illustrated.

关键词： Observers Mathematical model Fuzzy control PD control Steady-state Equations Friction

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The study of NAO robot arm based on direct kinematics by using D-H method

The study of NAO robot arm based on direct kinematics by usi...

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UKACC International Conference on control (control)

作者： Shuhui Wen Zhiyuan Ma Shuhuan Wen Yongsheng Zhao Jiantao Yao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University QinHuangDao China

Direct and inverse kinematics are commonly implemented to determine main parameters affecting humanoid robots behavior and specify the reliable method to control motion and preserve stability. This paper presents a direct kinematics method for humanoid NAO model. The approach is analytical based on classic methods like Denavit-Hartenberg convention which are employed to derive forward kinematics equations. Firstly, it analyses the upper limb topology of NAO model and establishes the kinematics models. Secondly, the homogeneous transformation matrix of upper limb joints of the robot is derived in this paper. Finally, the simulations are given by using the Robotic Toolbox from MATlab.software to test the derivation.

关键词： Robot kinematics Kinematics Joints Mathematical model MATlab Grasping

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Sensor Fault Detection of Continuous Casting Mold Vibration System Driven by Servo Motor

Sensor Fault Detection of Continuous Casting Mold Vibration ...

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Chinese control Conference (CCC)

作者： Xia Wu Jianxiong Li Yiming Fang Zhiqiang Wang Key Lab of Industrial Computer Control Engineering of Yanshan University Qinhuangdao Hebei Province China

The problem of sensor fault diagnosis and reconstruction of the continuous casting mold vibration displacement system driven by servo motor is investigated in this paper, and a fault reconstruction method based on adaptive sliding mode observer is proposed. Firstly, the matching condition of the observer is satisfied by constructing an auxiliary output, and a new state variable is selected as the low-pass filter with the fault vector output. Then an adaptive sliding mode observer is designed for the auxiliary output system in the present of the unknown upper bound of the fault, in which the adaptive switching gain is updated online. The gain matrix of the observer is obtained by solving a LMI optimization problem. And a linear transforming matrix is introduced to realize the direct estimation of the fault by the principle of the equivalent control output error injection. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

关键词： Observers Casting Mathematical model Servomotors Adaptive systems Vibrations Upper bound

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An Ameliorated Moth-flame Optimization Algorithm

An Ameliorated Moth-flame Optimization Algorithm

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Chinese control Conference

作者： Xiao-dong Zhao Yi-ming Fang Zhuang Ma Miao Xu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

To improve the global search ability under the condition of ensuring convergence speed, it is still a major challenge for most meta-heuristic optimization algorithms. The Moth-Flame Optimization (MFO) algorithm is an innovative nature-inspired algorithm. To improve the precision of the solution and to quicken the convergence speed and to increase the stability of MFO, an ameliorated Moth-flame optimization algorithm (A-MFO) that combines the crisscross optimization algorithm with MFO is proposed to solve this problems that are mentioned above. The performance of proposed A-MFO is demonstrated on six benchmark mathematical function optimization problems regarding superior accuracy and lower computational time achieved compared to other well-known nature-inspired algorithms.

关键词： Optimization Fires Convergence Sociology Statistics Benchmark testing Heuristic algorithms

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