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Article
Open AccessDesign and Control of a Flexure-Based Dual Stage Piezoelectric Micropositioner
In the field of advanced manufacturing technology, there is a growing need for high-precision micro/nano positioners. The traditional single stage actuated positioners have encountered performance limitation i...
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Article
Generalized adaptive gain sliding mode observer for uncertain nonlinear systems
This paper proposes a new generalized adaptive gain sliding mode observer (GAGSMO) for estimating the unavailable states of a class of multi-input multi-output uncertain nonlinear systems. To further improve t...
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Article
Adaptive full order sliding mode control for electronic throttle valve system with fixed time convergence using extreme learning machine
This paper proposes a novel extreme learning machine (ELM)-based fixed time adaptive trajectory control for electronic throttle valve system with uncertain dynamics and external disturbances. The developed con...
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Article
Extreme learning machine-based field-oriented feedback linearization speed control of permanent magnetic synchronous motors
An extreme learning machine (ELM)-based field-oriented feedback linearization speed control (ELMFOFLC) is proposed to enhance the robustness and tracking performance of a permanent magnetic synchronous motor (...
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Reference Work Entry In depth
Real-Time Control Systems with Applications in Mechatronics
In this chapter, the basic ideas of real-time control systems with applications in mechatronics will be discussed. The chapter starts with the introduction of a real-time system (RTS), real-time operating syst...
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Living Reference Work Entry In depth
Real-Time Control Systems with Applications in Mechatronics
In this chapter, the basic ideas of real-time control systems with applications in mechatronics will be discussed. The chapter starts with the introduction of a real-time system (RTS), real-time operating syst...
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Article
Special issue on extreme learning machine and deep learning networks
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Article
A new intelligent pattern classifier based on deep-thinking
A new intelligent pattern classifier based on the human being’s thinking logics is developed in this paper, aiming to approximate the optimal design process and avoid the matrix inverse computation in conventi...
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Chapter and Conference Paper
A Robust and Dynamically Enhanced Neural Predictive Model for Foreign Exchange Rate Prediction
In today’s highly interlinked international economy, accurate and timely real-time predictions of foreign exchange (fx) market offer tremendous business, social and political values to our community. In this w...
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Chapter and Conference Paper
Structured Learning-Based Sinusoidal Modelling for Gear Diagnosis and Prognosis
In this paper, a structured learning based sinusoidal modelling approach is developed for the prognostics of gear tooth cracking process. According to the vibration signal properties, a learning structure is f...
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Article
Design of a Robust Discrete-time Phase Lead Repetitive Control in Frequency Domain for a Linear Actuator with Multiple Phase Uncertainties
This paper presents a simple and effective design of a discrete-time repetitive control (RC) in frequency domain. Unlike existing phase lead RC designs, the proposed approach provides flexible phase lag compen...
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Book
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Article
Super twisting observer based repetitive control for aperiodic disturbance rejection in a brushless DC servo motor
This paper presents a super twisting observer based repetitive control (STORC), which can not only track the periodic signals precisely, but also reject aperiodic disturbances. Firstly, a stable repetitive con...
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Article
Robust adaptive position control of automotive electronic throttle valve using PID-type sliding mode technique
This paper proposes a robust adaptive position control scheme for automotive electronic throttle (ET) valve. Compared with the conventional throttle control systems, in this paper, a robust adaptive sliding mo...
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Article
Guest editorial: Special issue on Extreme learning machine and applications (II)
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Article
An optimal method for data clustering
An algorithm for optimizing data clustering in feature space is studied in this work. Using graph Laplacian and extreme learning machine (ELM) map** technique, we develop an optimal weight matrix W for feature ...
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Article
A recurrent neural network for modeling crack growth of aluminium alloy
A new recurrent neural model for crack growth process of aluminium alloy is developed in this work. It is shown that a recurrent neural network with the feedback loops at the output layer is constructed to mo...
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Article
Guest editorial: Special issue on Extreme learning machine and applications (I)
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Book and Conference Proceedings
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Book and Conference Proceedings
