Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
Nonlinear control systems: an introduction (2nd ed.)
Nonlinear control systems: an introduction (2nd ed.)
A universal construction of Artstein's theorem on nonlinear stabilization
Systems & Control Letters
Numerical methods for stochastic control problems in continuous time
Numerical methods for stochastic control problems in continuous time
Industrial applications of model based predictive control
Automatica (Journal of IFAC) - IFAC-IEEE special issue on meeting the challenge of computer science in the industrial applications of control
Sufficient conditions on general fuzzy systems as function approximators
Automatica (Journal of IFAC)
A course in fuzzy systems and control
A course in fuzzy systems and control
Automatica (Journal of IFAC)
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Adaptive Optimal Control: The Thinking Man's G.P.C.
Adaptive Optimal Control: The Thinking Man's G.P.C.
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Dynamic Programming
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
Controller synthesis of fuzzy dynamic systems based on piecewise Lyapunov functions
IEEE Transactions on Fuzzy Systems
Comment on "Discrete-time optimal fuzzy controller design: global concept approach"
IEEE Transactions on Fuzzy Systems
A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Automatica (Journal of IFAC)
Optimal regulator for the inverted pendulum via Euler-Lagrange backward integration
Automatica (Journal of IFAC)
Robust hybrid predictive control of nonlinear systems
Automatica (Journal of IFAC)
Hypergraph partitioning for the parallel computing of fuzzy differential equations
Fuzzy Sets and Systems
| Hi-index | 0.00 |
The optimal control of fuzzy systems with constraints is still an open problem. Our focus concerns the optimal control problem of fuzzy systems derived from receding horizon control (RHC) schemes. We consider methods to numerically compute the value function for general fuzzy systems. The numerical method that is developed using the finite difference with sigmoidal transformation is a stable and convergent algorithm for the Hamilton-Jacobi-Bellman (HJB) equation. An optimization procedure is developed to increase the calculation accuracy with less computation time. A parallel-processing method is employed in the optimization procedure. The optimization results are applied to the controller design of general fuzzy dynamic systems. Employing the principle of conventional RHC schemes, RHC-form controllers are designed for some classes of fuzzy dynamic systems. The basic ideas are as follows. First, the value function is calculated by numerical methods. Then, the value function is used as controller-design parameters to redesign RHC controllers for fuzzy systems, which is motivated by the inverse Lyapunov function design method. It is proven that the closed-loop system is asymptotically stable. An engineering implementation of the controller redesign scheme is discussed. Meanwhile, the parallel-processing framework that can improve the closed-loop performance is also introduced.