This paper provides an adaptive event-triggered method using adaptive dynamic programming (ADP) for the nonlinear continuous-time system. Comparing to the traditional method with fixed sampling period, the event-trigg...
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This paper provides an adaptive event-triggered method using adaptive dynamic programming (ADP) for the nonlinear continuous-time system. Comparing to the traditional method with fixed sampling period, the event-triggered method samples the state only when an event is triggered and therefore the computational cost is reduced. We demonstrate the theoretical analysis on the stability of the event-triggered method, and integrate it with the ADP approach. The system dynamics are assumed unknown. The corresponding ADP algorithm is given and the neural network techniques are applied to implement this method. The simulation results verify the theoretical analysis and justify the efficiency of the proposed event-triggered technique using the ADP approach.
For most practical nonlinear state estimation problems, the conventional nonlinear filters do not usually work well for some cases, such as inaccurate system model, sudden change of state-interested and unknown varian...
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For most practical nonlinear state estimation problems, the conventional nonlinear filters do not usually work well for some cases, such as inaccurate system model, sudden change of state-interested and unknown variance of measurement noise. In this paper, an adaptive cubature strong tracking information filter using variational Bayesian (VB) method is proposed to cope with these complex cases. Firstly, the strong tracking filtering (STF) technology is used to integrally improve performance of cubature information filter (CIF) aiming at the first two cases and an iterative scheme is presented to effectively evaluate a strong tracking fading factor. Secondly, the VB method is introduced to iteratively evaluate the unknown variance of measurement noise. Finally, the novel adaptive cubature information filter is obtained by perfectly combining the STF technology with the VB method, where the variance estimation provided by the VB method guarantees normal running of the strong tracking functionality.
OFDM is promising for underwater acoustic (UWA) communications due to its potential to combat the large delay spread. However, the performance of the OFDM system is seriously deteriorated by the inter-carrier interfer...
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ISBN:
(纸本)9781479982981
OFDM is promising for underwater acoustic (UWA) communications due to its potential to combat the large delay spread. However, the performance of the OFDM system is seriously deteriorated by the inter-carrier interference (ICI) caused by the transmitter/receiver motion and ocean waves. In this paper, we propose a novel ICI countermeasure. The key idea is to inactivate partial subcarriers according to index modulation and meanwhile transmit signals with opposite polarity on two adjacent active subcarriers for ICI self cancellation. Simulation results validate that the proposed scheme achieves much better bit error rate (BER) performance than many existing schemes in UWA communications.
The output synchronization problem is investigated for multiple linear agents with external disturbances that are guided by a leader with different dynamics. A method is presented for designing a networked controller ...
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The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theor...
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ISBN:
(纸本)9781629934884
The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theory of artificial neural networks. Simulation results are presented to show how well the method performs. It is shown that the results are superior to those achieved using Hebbian learning approaches such as nonlinear Hebbian learning. Some lines for possible future research and development are given.
The paper deals with the design of an adaptive cruise control system considering the optimal energy and fuel consumption of the vehicle as well as safety aspects of cornering maneuvers. In the velocity design the look...
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This paper presents a control study of the real Shiraz 250KW solar power plant together with a modeling and a monitoring interface. Here, a PID controller is developed to control the outlet oil temperature of the coll...
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This paper describes the effectiveness of observer-based output feedback for Unmanned Underwater Vehicle (UUV) with Linear Quadratic Regulation (LQR) performance. Tuning of observer parameters is crucial for tracking ...
This paper describes the effectiveness of observer-based output feedback for Unmanned Underwater Vehicle (UUV) with Linear Quadratic Regulation (LQR) performance. Tuning of observer parameters is crucial for tracking purpose. Prior to tuning facility, the ranges of observer and LQR parameters are obtained via system output cum error. The validation of this technique using unmanned underwater vehicles called Remotely Operated Vehicle (ROV) modelling helps to improve steady state performance of system response. The ROV modeling is focused for depth control using ROV 1 developed by the Underwater Technology Research Group (UTeRG). The results are showing that this technique improves steady state performances in term of overshoot and settling time of the system response.
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