In this paper, an optimal control scheme for a class of non-affine nonlinear systems with time-delays in state and control variables is developed using a new iterative adaptive dynamic programming (ADP) algorithm. By ...
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A yaw dynamic model of a small-scale unmanned helicopter with yaw rate feedback system is constructed according to its dynamic characteristics. With the data from flight experiment, a complete yaw dynamic state-space ...
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In this paper, an adaptive dynamic programming (ADP) method is developed for solving a class of continuoustime nonlinear two-person zero-sum games. The idea is to use iterative ADP technique to obtain the optimal cont...
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In this paper, a neural-network-based optimal control scheme for a class of nonlinear discrete-time systems with control constraints is proposed. The iterative adaptive dynamic programming (ADP) algorithm via globaliz...
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This paper proposes a supervised adaptive dynamic programming (SADP) algorithm for the full range Adaptive cruise control (ACC) system. The full range ACC system considers both the ACC situation in highway system and ...
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For extracting multi-planes from a large mount of 3D points obtained by a camera and range finders, it is necessary and important to improve the efficiency of RANSAC algorithm. To speed up the algorithm, the probabili...
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ISBN:
(纸本)9780889868106
For extracting multi-planes from a large mount of 3D points obtained by a camera and range finders, it is necessary and important to improve the efficiency of RANSAC algorithm. To speed up the algorithm, the probability to obtain good samples is improved with some measures such as 3D point segmentation, selecting samples within division, constraining and improving of samples. The proposed method also quickly evaluates local support for hypothesized models through randomly selecting a small number of points within division. Finally, simulations are presented to demonstrate the efficiency of the proposed method.
An intelligent optimal control scheme for unknown nonlinear discrete-time systems with discount factor in the cost function is proposed in this paper. An iterative adaptive dynamic programming (ADP) algorithm via glob...
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Inspired by the excellent performance of the biological visual system and relative experimental results, a three-layer spiking neural network is designed to extract the image information and it maps the information in...
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This paper is concerned with the design, optimization, and motion control of a radiocontrolled, multi-link, free-swimming biomimetic robotic fish based on an optimized kinematic and dynamic model of fish swimming. The...
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This paper is concerned with the design, optimization, and motion control of a radiocontrolled, multi-link, free-swimming biomimetic robotic fish based on an optimized kinematic and dynamic model of fish swimming. The performance of the robotic fish is determined by both the fish＇s morphological characteristics and kinematic parameters. By applying ichthyologic theories of propulsion, a design framework that takes into consideration both mechatronic constraints in physical realization and feasibility of control methods is presented, under which a multiple linked robotic fish that integrates both the carangiform and anguilliform swimming modes can be easily developed. Taking account of both theoretic hydrodynamic issues and practical problems in engineering realization, the optimal link-lengthratios are numerically calculated by an improved constrained cyclic variable method, which are successfully applied to a series of real robotic fishes. The rhythmic movements of swimming are driven by a central pattern generator （CPG） based on nonlinear oscillations, and up-and-down motion by regulating the rotating angle of pectoral fins. The experimental results verify that the presented scheme and method are effective in design and implementation.
An unmanned helicopter with navigation sensors and other onboard sensors applied to terrain modeling is introduced, which is effective and useful for many applications. It can substitute human efforts where human part...
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An unmanned helicopter with navigation sensors and other onboard sensors applied to terrain modeling is introduced, which is effective and useful for many applications. It can substitute human efforts where human participation is dangerous, inefficient, and impossible. The terrain modeling is used to capture the three-dimensional (3D) information including longitude, latitude and altitude of the region of interest (ROI) and then depicting the accurate 3D structures of terrains. The aerial robotic system for terrain modeling consists of a small unmanned helicopter, two suites of carrier phase DGPS equipment, two palm computers, a laser rangefinder with high precision and a micro-processor with ARM 9. The integration can capture the accurate 3D information of terrains and ultimately build the 3D terrain models.
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