The look-ahead is a forbidding condition formalized by a set of forbidden rules that are checked after all assignment of objects to rules are done. The look-ahead mode can decrease the inherent non-determinism of P sy...
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The look-ahead is a forbidding condition formalized by a set of forbidden rules that are checked after all assignment of objects to rules are done. The look-ahead mode can decrease the inherent non-determinism of P systems and helps to the practical implementation of P systems on computers. In this work, the computational power of P systems with symport/antiport rules working in the look-ahead mode are investigated. Communication P systems with 3 membranes and the weight of symport and antiport rules being 2 and 1, respectively, working in the look-ahead mode, can recognize any recursively enumerable languages; a characterization of context-sensitive languages is obtained by communication P systems with 2 membranes working in the look-ahead mode.
In process industry, there exist many Wiener systems with input magnitude constraints for which, however, most of the existing control algorithms cannot guarantee to have sufficiently large regions of asymptotic stabi...
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In process industry, there exist many Wiener systems with input magnitude constraints for which, however, most of the existing control algorithms cannot guarantee to have sufficiently large regions of asymptotic stability. In this paper, the subspace method is applied to separate the nonlinear and linear blocks in a constrained multi-input/multi-output (MEMO) Wiener system and a novel dual-mode nonlinear model predictive control algorithm is developed to maximize the region of the asymptotic stability. Simulation results are presented to demonstrate the virtues of this new control algorithm. The limitation is the requirement that the state and input matrices of the Wiener system's linear block should be accurately identified. Copyright (C) 2009 John Wiley & Sons, Ltd.
By expanding each kernel using the orthonormal Laguerre series, a Volterra functional series is used to represent the input/output relation of a nonlinear dynamic system. With the feedback of the modeling error, we de...
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By expanding each kernel using the orthonormal Laguerre series, a Volterra functional series is used to represent the input/output relation of a nonlinear dynamic system. With the feedback of the modeling error, we design a novel *** observer, based oil which all Output feedback controller is derived for both the stabilization and tracking problems. The stability of the closed-loop system is analyzed theoretically. The aloorithm is effectively applied oil the continuous stirring tank reactor and chemical reactor temperature control system. Copyright (C) 2009 John Wiley & Soils. Ltd.
Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation proc...
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ISBN:
(纸本)9787894631046
Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation process. The goal of this study is to combine the control strategies based on patients' motion intention with an upper limb rehabilitation robot to improve the recovery for the patients. In this paper, we propose an integrated robot-assist rehabilitation system, in which a 3 degree-of-freedom (DOF) exoskeletal rehabilitation robot, an EMG-based intention recognition module and a VR game environment are seamlessly combined. According toharacteristics of EMG signals, the wavelet package analysis approach is applied to extract the features of EMG. The node energy is used to construct the feature vector instead of the original coefficients of wavelet package decomposition to resolve the time-invariance problem. Then feature projection results in the singularity problem of with-in scatter matrix during the feature dimension reduction. To overcome the disadvantage of the with-in scatter matrix, this paper uses a recursive algorithm which is proposed in our previous work. The reduced feature vector is recognized by a neural network classifier and the output of the classifier is used for the control inputs. Preliminary experiments are also performed to implement the control of the rehabilitation robotic system by using the proposed EMG reorganization method, together with a dart game realized in the virtual reality environment. Experimental results show that the performance of motion intention recognition is satisfactory and the entire integrated system is feasible.
This paper presents a robust tracking algorithm for infrared objects in the image sequence, which is based on particle filer. Particle filter is a powerful tool for tracking especially in non-Gaussian condition, but t...
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This paper presents a robust tracking algorithm for infrared objects in the image sequence, which is based on particle filer. Particle filter is a powerful tool for tracking especially in non-Gaussian condition, but the selection of samples is still a challenging problem. According to the frame-to-frame correlation, two basic assumptions are proposed. Borrowing the idea from Sequence Importance Sampling, Monte-Carlo method will be applied to solve the well-known shortcomings of Particle filter in this paper. Technologically, the proposed algorithm could also track multiple objects successfully. The experimental result has demonstrated its feasibility and validity.
Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We pro...
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Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We propose and demonstrate in this letter that spiking neural networks (SNN), consisting of spiking neurons that propagate information by the timing of spikes, are a better alternative to the coding scheme based on spike frequency (histogram) alone. The SNN model analyzes cortical neural spike trains directly without losing temporal information for generating more reliable motor command for cortically controlled prosthetics. In this letter, we compared the temporal pattern classification result from the SNN approach with results generated from firing-rate-based approaches: conventional artificial neural networks, support vector machines, and linear regression. The results show that the SNN algorithm can achieve higher classification accuracy and identify the spiking activity related to movement control earlier than the other methods. Both are desirable characteristics for fast neural information processing and reliable control command pattern recognition for neuroprosthetic applications.
Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, a discrete structure representation ...
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In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple sc...
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Shuffle operation on trajectories is useful in modeling parallel composition of words and languages. In this work, a new class of P systems with shuffle operation is presented. Such a system has language-objects and s...
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Shuffle operation on trajectories is useful in modeling parallel composition of words and languages. In this work, a new class of P systems with shuffle operation is presented. Such a system has language-objects and shuffle-operation rules in its regions. It can be used as a language generator; specifically it is used to generate languages from sets of languages. Some comparison results are obtained, which show that the power of shuffle operation is enlarged in the framework of P systems.
To drive a single joint of rehabilitation robotic arm, we propose a new PM-TS actuator comprising a Pneumatic Muscle (PM) and a Torsion Spring (TS). Unlike the traditional agonist/antagonist PM actuator, the PM is arr...
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To drive a single joint of rehabilitation robotic arm, we propose a new PM-TS actuator comprising a Pneumatic Muscle (PM) and a Torsion Spring (TS). Unlike the traditional agonist/antagonist PM actuator, the PM is arranged in appropriate place as agonist and the torsion spring provides opposing torque as antagonist in the proposed actuator. The 1-DOF and 2-DOF rehabilitation robotic arm models are derived considering the PM-TS dynamic model. To realize a high-accurate trajectory tracking control of the robotic arms, an intelligent PID controller based on an Echo State Neural Network (ESN) is proposed, where the ESN state is updated by the online Recursive Least Square (RLS) algorithm. Simulation results demonstrate the validity of PM-TS actuators. The performance of RLS-ESN based PID controller is found more satisfactory than conventional PID controller in our study.
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