For a class of uniformly observable nonlinear multi-input-multi-output (MIMO) systems with unknown parameters in both state and output equations, an adaptive observer is designed in a constructive manner based on the ...
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For a class of uniformly observable nonlinear multi-input-multi-output (MIMO) systems with unknown parameters in both state and output equations, an adaptive observer is designed in a constructive manner based on the techniques of high gain observer and adaptive estimation. The high gain adaptive observer for joint state and unknown parameter estimation is conceptually simple. The new algorithm makes use of a time varying gain matrix for unknown parameter estimation, which simplifies the initialization and parameter tuning. In order to establish the global exponential convergence of the adaptive observer, a persistent excitation condition is required. Consequently, the global exponential convergence for simultaneous estimation of states and unknown parameters is formally established following a simple procedure. A numerical example is presented to illustrate the performance of this adaptive observer.
Model is usually necessary for the design of a control loop. Due to *** and unknown dynamics, model plant mismatch is inevitable in the control loop. In process monitoring, detection of the mismatch and evaluation of ...
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Model is usually necessary for the design of a control loop. Due to *** and unknown dynamics, model plant mismatch is inevitable in the control loop. In process monitoring, detection of the mismatch and evaluation of its *** are both demanded. In this paper we .rstly present several mismatch measures based on *** model descriptions. Then we categorize them into *** groups from *** perspectives and compare their potential in detection and diagnosis. A case study on a mixing process is presented and some remarks on related aspects are given.
This paper introduces extremal optimization (EO) method to solve unit commitment problem for power systems. EO is a local-search heuristic algorithm and originally developed from the fundamentals of statistical physic...
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This paper introduces extremal optimization (EO) method to solve unit commitment problem for power systems. EO is a local-search heuristic algorithm and originally developed from the fundamentals of statistical physics. In the implementation of EO for unit commitment (UC) problem, a novel problem-specific mutation operator is introduced and rule-based heuristic constraint-repairing techniques are devised. Simulation results on power systems which are composed of up to 100-units over a scheduling horizon of 24-hours demonstrate competitive performance with EO method compared with other existing methods for UC problem.
A maxillofacial Multi-arm surgery robot is employed to assisting maxillofacial surgery, which can improve surgical precision and reduce surgeons' strain. Thus, the safety during the processing of the surgery is ne...
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ISBN:
(纸本)9781467303644
A maxillofacial Multi-arm surgery robot is employed to assisting maxillofacial surgery, which can improve surgical precision and reduce surgeons' strain. Thus, the safety during the processing of the surgery is necessary for protecting the patient and preventing the quality of the surgery. This paper presents the development of a collision and self-collision-detection scheme, for Maxillofacial Multi-arm Surgery Robot. The method is based on modeling the arm of Multi-arm robot and the obstacle in surgery environment by simple geometric primitives (cylinders and spheres). Methods of detecting collision about the cylinders and the spheres are introduced. By resorting to the pose of cylinder or sphere which presents in the workspace, many different types of collisions are introduced. The performance of the collision-avoidance scheme is demonstrated with Multi-arm robot via experiments.
Combined with modern imaging techniques and minimally invasive treatment techniques, microwave ablation surgeries have become one of the most effective methods in the modern comprehensive treatment of cancer. To solve...
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ISBN:
(纸本)9781467303644
Combined with modern imaging techniques and minimally invasive treatment techniques, microwave ablation surgeries have become one of the most effective methods in the modern comprehensive treatment of cancer. To solve the problems exist in traditional surgeries, microwave ablation surgical robot has been successfully developed. At first, this paper briefly introduces the robot auxiliary treatment process. Then analyzes the ultrasound-guided positioning system in detail. At last, the paper focuses on experimental research process such as robot localization experiment and precision experiment. The experimental results will verify the effectiveness of the robot system and the accuracy of the treatment. Meanwhile, the problems exist in the system are discussed and he future research direction is demonstrated.
Hysteretic optimization (HO) is a recently proposed heuristic physical optimization algorithm based on the well-known demagnetization process of magnetic materials in magnetism. The Capacitated Vehicle Routing Problem...
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Hysteretic optimization (HO) is a recently proposed heuristic physical optimization algorithm based on the well-known demagnetization process of magnetic materials in magnetism. The Capacitated Vehicle Routing Problem (CVRP) is an important variant of the vehicle routing problem which is one of the most important and intensively studied combinatorial optimization problems. In this study, we apply HO to the Capacitated Vehicle Routing Problem (CVRP), by generalizing the external field and endowing the configuration space with a proper distance. The experimental results with benchmark problems show the proposed method is competitive with other popular algorithms, such as particle swarm optimization, genetic algorithms.
This paper presents a parallel control system designed for managing emergent events in an urban rail transit system (URTS). The key features of the system include cloud computing, information fusion and expert systems...
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In this paper, we adopt the coarse graining method proposed by Lee H K et al. to develop a macroscopic model from the microscopic traffic model-GOVM. The proposed model inherits the parameter p which considers the inf...
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In this paper, we adopt the coarse graining method proposed by Lee H K et al. to develop a macroscopic model from the microscopic traffic model-GOVM. The proposed model inherits the parameter p which considers the influence of next-nearest car introduced in the GOVM model. The simulation results show that the new model is strictly consistent with the former microscopic model. Using this macroscopic model, we can avoid considering the details of each traffic on the road, and build more complex models such as road network model easily in the future.
A novel framework for process pattern construction and multi-mode monitoring is proposed. To identify process patterns, the framework utilizes a clustering method that consists of an ensemble moving window strategy al...
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Agent-based evacuation modeling approach is gained more and more attention for investigating human cognitive capabilities and social behaviors in building fires. This paper mainly overviews the research about various ...
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