the paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. some mathematical vector models were obtained for control system multicriterion quality indices with due ...

In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear Bilevel programming (FFLBLP) problems by representing all the parameters as triangular fuzzy numbers. In the proposed method, the given FFLBLP problem is decomposed into three crisp linear programming (CLP) problems with bounded variables constraints, the three CLP problems are solved separately...

The camera stabilizer stabilizes the camera’s line of sight by isolating the camera from the model uncertainties, disturbances of operating environment and system movements. This paper presents a voltage-base optimal adaptive fuzzy sliding mode control for camera stabilizer. In this proposed control method, a voltage-base sliding mode controller is applied. But unfortunately, undesirable ...

In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed. The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optim...

the main purpose of this paper is to propose a new numerical method for solving the optimal control problems based on state parameterization. here, the boundary conditions and the performance index are first converted into an algebraic equation or in other words into an optimization problem. in this case, state variables will be approximated by a new hybrid technique based on new second kind ch...

and Applied Analysis 3 A α , A β are matrices that will be updated adaptively with the following updating laws: ?̇? α (t) = −Q −1 ⋅ z ⋅ ξ T α ⋅ es, ?̇? β (t) = −Q −1 ⋅ z ⋅ ξ T β ⋅ es ⋅ u (t) (12) and finally the control law is described as follows: u (t) = 1 β (t) + β (x) (− [α (t) + ?̂? (x)] + v (t)) . (13) 2.2. Direct Adaptive Fuzzy Controller (DAFC). Control law u(t) in feedback linearization m...

The optimal control of problem is about finding a control law for a given system such that a certain optimality criterion is achieved. Methods of solving the optimal control problems are divided into direct methods and mediated methods (through other equations). In this paper, the PSO- SVM indirect method is used to solve a class of optimal control problems. In this paper, we try to determine t...

In this paper, we consider a time-optimal control problem with uncertainties. Dynamics of controlled object is expressed by crisp linear system of differential equations with fuzzy initial and final states. We introduce a notion of fuzzy optimal time and reduce its calculation to two crisp optimal control problems. We examine the proposed approach on an example.