#### Filter Results:

- Full text PDF available (39)

#### Publication Year

1999

2017

- This year (3)
- Last 5 years (37)
- Last 10 years (71)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

#### Method

Learn More

- Ching-Hung Lee, Ching-Cheng Teng
- IEEE Trans. Fuzzy Systems
- 2000

This paper proposes a recurrent fuzzy neural network (RFNN) structure for identifying and controlling nonlinear dynamic systems. The RFNN is inherently a recurrent multilayered connectionist network for realizing fuzzy inference using dynamic fuzzy rules. Temporal relations are embedded in the network by adding feedback connections in the second layer of… (More)

- Ti-Chung Lee, Kai-Tai Song, Ching-Hung Lee, Ching-Cheng Teng
- IEEE Trans. Contr. Sys. Techn.
- 2001

The tracking control problem with saturation constraint for a class of unicycle-modeled mobile robots is formulated and solved using the backstepping technique and the idea from the LaSalle’s invariance principle. A global result is presented in which several constraints on the linear and the angular velocities of the mobile robot from recent literature are… (More)

- Ching-Hung Lee, Fu-Kai Chang
- Expert Syst. Appl.
- 2010

Based on the electromagnetism-like algorithm, an evolutionary algorithm, improved EM algorithm with genetic algorithm technique (IEMGA), for optimization of fractional-order PID (FOPID) controller is proposed in this article. IEMGA is a population-based meta-heuristic algorithm originated from the electromagnetism theory. It does not require gradient… (More)

- 〈Ching-Hung Lee, Jang-Lee Hong, Yu-Ching Lin, Ching-Hung Lee, Jang-Lee Hong, Yu-Ching Lin
- 2002

This paper presents a type-2 fuzzy neural network system (type-2 FNN) and its learning using genetic algorithm. The so-called type-1 fuzzy neural network (FNN) has the properties of parallel computation scheme, easy to implement, fuzzy logic inference system, and parameters convergence. And, the membership functions (MFs) and the rules can be designed and… (More)

- Ching-Hung Lee, Hung-Yi Pan
- Fuzzy Sets and Systems
- 2009

This paper proposes a novel intelligent control scheme using type-2 fuzzy neural network type-2 FNN system. The control scheme is developed using a type-2 FNN controller and an adaptive compensator. The type-2 FNN combines the type-2 fuzzy logic system FLS , neural network, and its learning algorithm using the optimal learning algorithm. The properties of… (More)

- Ching-Hung Lee
- IEEE Trans. Systems, Man, and Cybernetics, Part B
- 2004

In this paper, an adaptive parallel control architecture to stabilize a class of nonlinear systems which are nonminimum phase is proposed. For obtaining an on-line performance and self-tuning controller, the proposed control scheme contains recurrent fuzzy neural network (RFNN) identifier, nonfuzzy controller, and RFNN compensator. The nonfuzzy controller… (More)

- Ching-Hung Lee, Ching-Cheng Teng
- Fuzzy Sets and Systems
- 2002

This paper presents a PID tuning method for unstable processes using an adaptive-network-based-fuzzy-inference system (ANFIS) for given gain and phase margin (GPM) speci)cations. PID tuning methods are widely used to control stable processes. However, PID controller for unstable processes is less common. In this paper, the PID controller parameters can be… (More)

- Ching-Hung Lee, Yu-Ching Lin, Wei-Yu Lai
- CIRA
- 2003

- Ching-Hung Lee, Feng-Yu Chang, Chih-Min Lin
- IEEE Trans. Cybernetics
- 2014

This paper aims to propose a more efficient control algorithm for chaos time-series prediction and synchronization. A novel type-2 fuzzy cerebellar model articulation controller (T2FCMAC) is proposed. In some special cases, this T2FCMAC can be reduced to an interval type-2 fuzzy neural network, a fuzzy neural network, and a fuzzy cerebellar model… (More)