Fusion of soft computing and hard computing techniques: a review of applications

Soft computing (SC) is an emerging collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty, and partial truth to achieve robustness, tractability, and low total cost. It differs from conventional hard computing (HC) in the sense that, unlike hard computing, it uses intuition or subjectivity. Therefore, soft computing provides an attractive opportunity to represent ambiguity in human thinking with the real life uncertainty. Fuzzy logic (FL), neural networks (NN), and genetic algorithms (GA) are the core methodologies of soft computing. However, FL, NN, and GA should not be viewed as competing with each other but synergistic and complementary instead, as emphasized by Dr. Zadeh . Considering the available literature, it is easy to conclude that the fusion of individual soft computing methodologies has been advantageous in numerous applications. In this paper, we give a review of applications where the fusion of soft computing and hard computing has provided innovative solutions for demanding real-world problems. A representative list of references is provided with evaluative discussions and conclusions.

[1]  Anthony Tzes,et al.  Genetic-based fuzzy clustering for DC-motor friction identification and compensation , 1998, IEEE Trans. Control. Syst. Technol..

[2]  Changjiu Zhou,et al.  Integration of linguistic and numerical information for hybrid intelligent control , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[3]  Soon-H. Kwon,et al.  A fuzzy logic-based gain tuner for PID controllers , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[4]  B.K. Bose,et al.  Neural network based estimation of feedback signals for a vector controlled induction motor drive , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[5]  L. Wozniak,et al.  Hydrogenerator system identification using a simple genetic algorithm , 1997 .

[6]  Kwang Y. Lee,et al.  An autonomous control system for boiler-turbine units , 1996 .

[7]  Z. Papp.  An identification and adaptive control scheme using fuzzy parameterized linear filters , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[8]  Matsumoto Hiroshi,et al.  Startup optimization of a combined cycle power plant based on cooperative fuzzy reasoning and a neural network , 1997 .

[9]  Rolf Isermann,et al.  Modeling and design methodology for mechatronic systems , 1996 .

[10]  Kwang Y. Lee,et al.  Hybrid feedforward and feedback controller design for nuclear steam generators over wide range operation using genetic algorithm , 1997 .

[11]  Minoru Sasaki,et al.  Self-tuning PID control of a flexible micro-actuator using neural networks , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[12]  Y. K. Wong,et al.  Hybrid fuzzy two-stage controller for an induction motor , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[13]  Abdollah Homaifar,et al.  VSTOL aircraft longitudinal control using fuzzy logic , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[14]  Wen-Shyong Yu,et al.  PID controller design using dynamical neural networks , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

[15]  Lih-Chang Lin,et al.  Feedback linearization and fuzzy control for conical magnetic bearings , 1997, IEEE Trans. Control. Syst. Technol..

[16]  Seul Jung,et al.  Neural network impedance force control of robot manipulator , 1998, IEEE Trans. Ind. Electron..

[17]  Ying-Yu Tzou,et al.  Fuzzy-tuning current-vector control of a three-phase PWM inverter for high-performance AC drives , 1998, IEEE Trans. Ind. Electron..

[18]  Michifumi Yoshioka,et al.  Skill-based PID control by using neural networks , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[19]  Xiao Zhi Gao,et al.  Comparison of conventional and soft computing-based control methods in a power regulation application , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[20]  Peter Kwong-Shun Tam,et al.  Lyapunov-function-based design of fuzzy logic controllers and its application on combining controllers , 1998, IEEE Trans. Ind. Electron..

[21]  George W. Irwin,et al.  Hybrid neural adaptive control for bank-to-turn missiles , 1997, IEEE Trans. Control. Syst. Technol..

[22]  Marley M. B. R. Vellasco,et al.  Comparison of different evolutionary methodologies applied to electronic filter design , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[23]  K. Benmahammed,et al.  A two layer robot control design , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[24]  Andrew A. Goldenberg,et al.  Neural network architecture for trajectory generation and control of automated car parking , 1996, IEEE Trans. Control. Syst. Technol..

[25]  Shigenobu Kobayashi,et al.  Power plant start-up scheduling: a reinforcement learning approach combined with evolutionary computation , 1998, J. Intell. Fuzzy Syst..

[26]  James A. Momoh,et al.  An implementation of a hybrid intelligent tool for distribution system fault diagnosis , 1996 .

[27]  Aniruddha M. Gole,et al.  Fuzzy logic control for HVDC transmission , 1997 .

[28]  Yuan-Yih Hsu,et al.  Fuzzy dynamic programming approach to reactive power/voltage control in a distribution substation , 1997 .

[29]  Girijesh Prasad,et al.  A neural net model-based multivariable long-range predictive control strategy applied in thermal power plant control , 1997 .