Typical cover techniques adopted in the conventional secure communication schemes are the additive masking and modulation by multiplication. In order to enhance security, in this paper, the new masking and decryption ...
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Typical cover techniques adopted in the conventional secure communication schemes are the additive masking and modulation by multiplication. In order to enhance security, in this paper, the new masking and decryption methods were given by iterative learning control algorithm for secure communication. In order to enhance security, the paper proposed the nonlinear masking method to apply to the traditional items and used the iterative learning control algorithm to decrypt. The algorithm reconstructed the information signal completely and analyzed the robustness and convergence of learningalgorithm about the initial error and output error. The convergence conditions were given and the simulations shown in the algorithm can reconstruct the signal in secure communication.
The present paper proposes an iterativelearningcontrol (ILC) algorithm for accurate force tracking in a long range tribometer. The device is a nonlinear single input single output plant affected by repetitive and no...
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ISBN:
(纸本)9783952426937
The present paper proposes an iterativelearningcontrol (ILC) algorithm for accurate force tracking in a long range tribometer. The device is a nonlinear single input single output plant affected by repetitive and non repetitive perturbations in the output. The former perturbations result from the repetitive nature of the tests, and the latter ones are caused by friction phenomena in the guiding elements. Due to the characteristics of the device, it has been necessary to develop specific solutions to assure a robust behavior: on the one hand, analysis and identification techniques for the perturbations, and on the other hand, a spatial synchronization. The finally developed controller combines ILC with feedforward and feedback commands. The system is experimentally validated and the results show a substantial improvement in the performance compared to more classical approaches.
Creating animations for entertainment humanoid robots is a time consuming process because of high aesthetic quality requirements as well as poor tracking performance due to small actuators used in order to realize hum...
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ISBN:
(纸本)9781479926190
Creating animations for entertainment humanoid robots is a time consuming process because of high aesthetic quality requirements as well as poor tracking performance due to small actuators used in order to realize human size. Once deployed, such robots are also expected to work for years with minimum downtime for maintenance. In this paper, we demonstrate a successful application of an iterative learning control algorithm to automate the process of fine tuning choreographed human-speed motions on a 37 degree-of-freedom humanoid robot. By using good initial feed-forward commands generated by experimentally-identified joint models, the learningalgorithm converges in about 9 iterations and achieves almost the same fidelity as the manually fine tuned motion.
In this paper, for a class of NCS with uncertain time delay, a PD-type iterativelearningalgorithm (ILC) is proposed to compensate the time delay. Based on the strictly repetition of the initial state, the sufficient...
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ISBN:
(纸本)9781457720727
In this paper, for a class of NCS with uncertain time delay, a PD-type iterativelearningalgorithm (ILC) is proposed to compensate the time delay. Based on the strictly repetition of the initial state, the sufficient conditions which guarantee the uniform convergence of the ILC is given. And the limit output trajectories generated by the action of the ILC are also presented. Then, comparing with the efficiency of the P-type ILC algorithm, it is shown that the PD-type ILC is more effective to compensate the time delay. For the case that the range of the time delay becomes smaller, it can track the output trajectories more precisely than the P-type ILC algorithm. Moreover, under the same number of iteration, the PD-type ILC algorithm can track the state trajectories faster than the P-type ones.
In this paper, for a class of NCS with uncertain time delay, a PD-type iterativelearningalgorithm (ILC) is proposed to compensate the time delay. Based on the strictly repetition of the initial state, the sufficient...
详细信息
In this paper, for a class of NCS with uncertain time delay, a PD-type iterativelearningalgorithm (ILC) is proposed to compensate the time delay. Based on the strictly repetition of the initial state, the sufficient conditions which guarantee the uniform convergence of the ILC is given. And the limit output trajectories generated by the action of the ILC are also presented. Then, comparing with the efficiency of the P-type ILC algorithm, it is shown that the PD-type ILC is more effective to compensate the time delay. For the case that the range of the time delay becomes smaller, it can track the output trajectories more precisely than the P-type ILC algorithm. Moreover, under the same number of iteration, the PD-type ILC algorithm can track the state trajectories faster than the P-type ones.
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