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Article
A new super-predefined-time convergence and noise-tolerant RNN for solving time-variant linear matrix–vector inequality in noisy environment and its application to robot arm
Recurrent neural networks (RNNs) are excellent solvers for time-variant linear matrix–vector inequality (TVLMVI). However, it is difficult for traditional RNNs to track the theoretical solution of TVLMVI under...
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Article
A novel varying-parameter periodic rhythm neural network for solving time-varying matrix equation in finite energy noise environment and its application to robot arm
Solving matrix equation with noise interference is a challenging problem in mathematical and engineering applications. Unlike the traditional recurrent neural network, a novel varying-parameter periodic rhythm...
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Article
Robotic haptic adjective perception based on coupled sparse coding
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Article
Correction to: A Decomposition-Based Improved Broad Learning System Model for Short-Term Load Forecasting
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Article
A Decomposition-Based Improved Broad Learning System Model for Short-Term Load Forecasting
It is still a challenging problem for most existing forecasting methods to obtain accurate and rapid prediction performance in short-term load forecasting because of the complexity and non-linearity of the ele...
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Article
A novel decomposition-based ensemble model for short-term load forecasting using hybrid artificial neural networks
Highly accurate short-term load forecasting (STLF) is essential in the operation of power systems. However, the existing predictive methods cannot achieve an effective balance between prediction accuracy and c...
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Article
A decomposition-based approximate entropy cooperation long short-term memory ensemble model for short-term load forecasting
Short-term load forecasting with high accuracy is essential to power systems. Because power loads involve high volatility and uncertainty, it is challenging to accurately perform short-term load forecasting (S...
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Article
A novel hybrid approach of ABC with SCA for the parameter optimization of SVR in blind image quality assessment
Images may be distorted to different degrees in the process of acquisition, transmission, and reconstruction, which is not conducive to the perception and recognition of the human eye. Therefore, it is necessa...
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Article
Spiral-based chaotic chicken swarm optimization algorithm for parameters identification of photovoltaic models
Photovoltaic (PV) systems are becoming increasingly significant because they can convert solar energy into electricity. The conversion efficiency is related to the PV models’ parameters, so it is crucial to id...
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Article
Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle
This paper addresses the stability and tracking control problem of miniature unmanned multirotor aerial vehicle (MUMAV) in the presence of bounded uncertainty. The uncertainty may appear from unmodeled dynamic...
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Article
Collision detection for virtual environment using particle swarm optimization with adaptive cauchy mutation
Rapid and accurate detection of collision between virtual objects is crucial for many virtual reality based applications. In order to ensure a high-level of accuracy and to meet the real-time requirement, a fa...
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Article
Adaptive control for robot manipulators using multiple parameter models
In this paper, we propose multiple parameter models based adaptive switching control system for robot manipulators. We first uniformly distribute the parameter set into a finite number of smaller compact subse...
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Article
A novel sub-band adaptive filtering for acoustic echo cancellation based on empirical mode decomposition algorithm
Acoustic echo cancellation is one of the most severe requirements in hands-free telephone and teleconference communication. This paper proposes an Empirical Mode Decomposition (EMD)-based sub-band adaptive fil...
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Article
Adaptive tracking control of an MEMS gyroscope with H-infinity performance
Microelectromechanical systems (MEMSs) pose unique measurement and control problems compared with conventional ones because of their small size, low cost, and low power consumption. The vibrating gyroscope is ...
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Chapter and Conference Paper
Parameter Estimation for Time-Varying System Based on Combinatorial PSO
In this paper, a novel Particle Swarm Optimization (PSO) identification algorithm for time-varying systems with a colored noise is presented. Presented criterion function can show not only outside system outpu...
