In this paper, a high order open and closed ILC (iterative learning control) scheme with initial state learning is presented. the convergent bounds are only dependent on the system uncertainties and disturbances but i...
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ISBN:
(纸本)0780386531
In this paper, a high order open and closed ILC (iterative learning control) scheme with initial state learning is presented. the convergent bounds are only dependent on the system uncertainties and disturbances but independent of the initialization errors. the scheme performs better than common ILC scheme with initial state learning both in convergence rate and transient performance. By adding closed loop, the whole algorithm has better performance in both stability and convergence than the open loop one alone. Furthermore, the effectiveness of the proposed method is illustrated by simulation experiments.
Under the environment of network, the second-order inertial object is controlled when the single-packet transmission and no data packet dropout, the goal of this paper is to design controller of numeric PID without ne...
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ISBN:
(纸本)0780386531
Under the environment of network, the second-order inertial object is controlled when the single-packet transmission and no data packet dropout, the goal of this paper is to design controller of numeric PID without network delay that satisfy relevant performance and stabilizability when network-induced delay is included. the dynamic smithcontroller and on-line time-delay identification are used;the specified methods of smith parameter are purposed when the network delay is greater or less sample time and satisfy the given index. It can be used as the base for fuzzy compensation controller under multiple-packet and data packet dropout.
In this paper, a Dynamic Fuzzy Q-Learning (DFQL) method navigating a mobile robot efficiently is presented. Self-organizing fuzzy inference is introduced to calculate actions and Q-functions which capable of enabling ...
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ISBN:
(纸本)0780386531
In this paper, a Dynamic Fuzzy Q-Learning (DFQL) method navigating a mobile robot efficiently is presented. Self-organizing fuzzy inference is introduced to calculate actions and Q-functions which capable of enabling us to deal with continuous-valued states and actions. Consequently, fuzzy rules can be generated automatically. Fuzzy inference systems provide a natural mean of incorporating the bias components for rapid reinforcement learning. Furthermore, the eligibility trace method is employed in our algorithm, leading to faster learning and alleviating the experimentation-sensitive problem where an arbitrarily bad training policy might result in a non-optimal policy. Experimental results demonstrate that the robot is able to learn the right policy with a few trials.
the problem of regulating a nonholonomic system in chained form to an equilibrium state is addressed and solved by a smooth time-varying control law. the proposed scheme based on Lyapunov analysis can guarantee asympt...
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ISBN:
(纸本)0780386531
the problem of regulating a nonholonomic system in chained form to an equilibrium state is addressed and solved by a smooth time-varying control law. the proposed scheme based on Lyapunov analysis can guarantee asymptotic stabilization and exponential stabilization, respectively, by simply changing a term in the controller expression. therefore, the controller can be used for theoretical analysis and practical application. the additional novelty of the proposed approach is that the parameters in our controller have clear physical meanings and are easily implemented and tuned. Simulation results based on a numerical example and a tricycle-type mobile robot are presented to demonstrate the effectiveness of the developed method.
this paper presents a platooning controller for a four-wheel-driving four-wheel-steering vehicle to follow another. the controller is based on the full-state tracking theory and utilizes a vehicular model that makes i...
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ISBN:
(纸本)0780386531
this paper presents a platooning controller for a four-wheel-driving four-wheel-steering vehicle to follow another. the controller is based on the full-state tracking theory and utilizes a vehicular model that makes it able to continue to operate when faults are detected at its steering systems or driving motors which are disabled accordingly. the unified controller is also able to track and follow the target either moving forward in front or moving backward in the back of the vehicle making the real-time implementation of different tracking modes simple. Tracking stability is secured by the proper selection of design parameters. Simulations show the proposed control scheme works properly even in the presence of faults at several different parts.
this paper presents a technique to controlthe inventory level on the warehouse automation by using continuous reviewing and forecasting system. the product demand that stored in the warehouse depends on orders from c...
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ISBN:
(纸本)0780386531
this paper presents a technique to controlthe inventory level on the warehouse automation by using continuous reviewing and forecasting system. the product demand that stored in the warehouse depends on orders from customers. For each product, the demand follows a Poisson process and the delivery lead-time is known. the demand forecast can predict the trend of order and redefine the reorder point (RP) of inventory that linked to automatic warehouse control system. the automatic warehouse plays an important role in the computer integration manufacturing system (CIMS). the functions of CIMS include production planning, material requirement planning, work order generation, process control, quality control, shipping planning, warehouse and inventory management and material cost accounting. [1] this paper focuses on implementing an automatic warehouse control and inventory management demand forecasting system.
this paper presents a localization method using motion vision. the proposed method locates a mobile robot relative to the object to which the robot moves. Two points are selected from the object as feature points. Con...
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ISBN:
(纸本)0780386531
this paper presents a localization method using motion vision. the proposed method locates a mobile robot relative to the object to which the robot moves. Two points are selected from the object as feature points. Consecutive two images containing the feature points are taken before and after the robot moves. then, the poses of the robot can be determined according to the image coordinates of the feature points. A search algorithm is also presented to enhance the localization precision. It can find more correct image coordinates of the feature points based on the really detected image coordinates of them. Many experiments are performed on real images to justify this search algorithm. the results show that it is effective.
A new parameter estimation method for time-varying systems is proposed in this paper. First, by introducing,a priori' knowledge into the performance index of least square (LS) algorithm, a modified LS algorithm is...
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ISBN:
(纸本)0780386531
A new parameter estimation method for time-varying systems is proposed in this paper. First, by introducing,a priori' knowledge into the performance index of least square (LS) algorithm, a modified LS algorithm is developed. then, a number of modifications have been proposed to improve some existed LS algorithms, such as the real-time recursive LS algorithm and the instrumental variable (IV) algorithm. Finally the newly proposed method is applied to a cement blending process. the test results show that the new LS algorithm has remarkably improved the estimation accuracy and the convergent rate of tracking to the true time-varying system parameters.
this paper presents a novel active contour model. In our model, the contour points are described in polar coordinates and limited to move along their radial directions. When implemented with greedy algorithm, the prop...
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ISBN:
(纸本)0780386531
this paper presents a novel active contour model. In our model, the contour points are described in polar coordinates and limited to move along their radial directions. When implemented with greedy algorithm, the proposed model has lower computation cost than the traditional snake described in Cartesian coordinates. To broaden the attraction range of the object boundary, improvements have been made on the internal energy and the external energy based on the polarized description of our model. the results of applying our model to segment cell nucleus of biopsy cell images show that it can track cell nucleus boundary efficiently and our model has superior performance than the traditional snake.
A new parametric approach for robust fault detection in matrix second-order linear (MSOL) systems with unknown disturbances is directly proposed in matrix second-order framework. the residual is generated through util...
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ISBN:
(纸本)0780386531
A new parametric approach for robust fault detection in matrix second-order linear (MSOL) systems with unknown disturbances is directly proposed in matrix second-order framework. the residual is generated through utilizing a Luenberger function observer of MSOL systems. Based on a recently proposed eigenstructure assignment approach for MSOL systems, parameterizations of the coefficient matrices of the Luenberger function observer are presented. By combining the parameterizations of the observer eigenvector matrix and an established condition for disturbance decoupling in MSOL systems, the effect of the disturbance to the residual signal is decoupled. A simple algorithm is presented. An example shows the effect of the proposed approach.
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