Stochastic Linear Quadratic Regulators with Indefinite Control Weight Costs
SIAM Journal on Control and Optimization
Toward the Formal Foundation of Ant Programming
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
Neural-network-based optimal fuzzy controller design for nonlinear systems
Fuzzy Sets and Systems
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Switching control of an R/C hovercraft: stabilization and smoothswitching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stable and optimal fuzzy control of linear systems
IEEE Transactions on Fuzzy Systems
Optimal fuzzy controller design: local concept approach
IEEE Transactions on Fuzzy Systems
Optimal fuzzy controller design in continuous fuzzy system: global concept approach
IEEE Transactions on Fuzzy Systems
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In this paper, optimal control for stochastic linear singular Takagi-Sugeno (T-S) fuzzy system with quadratic performance is obtained using ant colony programming (ACP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using ACP approach. The solution of this novel method is compared with the traditional Runge Kutta (RK) method. An illustrative numerical example is presented for the proposed method.