The problem of designing controls for a linear dynamic system under input disturbance is considered. The input disturbance is bounded but the bound information is either deterministic or fuzzy. The control design is purely deterministic. However, the resulting system performance is interpreted differently, depending on the bound information. It may be deterministic or fuzzy (i.e. with a spectru...

optimal allocation of water resources is an essential service in agriculture that must be considered by farmers. one of the most significant factors in optimal allocation of water resources in agriculture is to define optimal farm cropping pattern. in this study, in order to determine optimal cropping pattern and water resources allocation in central district of mashhad city (toos village), the...

Dealing with a LQR controller surface subject to power and torque constraints, is an issue of nonlinear problem that is difficult to implement. This paper employs a fuzzy controller surface to replace the LQR surface subject to power and torque constraints by using class stacking, least square and Sugenotype fuzzy inference mode. Through this type of transformation, called “Optimal fuzzy contro...

in this paper we present a method for solving fuzzy linear systemsby two crisp linear systems. also necessary and sufficient conditions for existenceof solution are given. some numerical examples illustrate the efficiencyof the method.

To find an optimal path for robots in an environment that is only partially known and continuously changing is a difficult problem. This paper presents a new method for generating a collision-free near-optimal path for an autonomous mobile robot in a dynamic environment containing moving and static obstacles using neural network and fuzzy logic with genetic algorithm. The mobile robot selects a...

In this paper, optimal control for linear singular fuzzy system is obtained using Simulink. To obtain the optimal control, the solution of MRDE is computed using Simulink approach. The Simulink solution is equivalent or very close to the exact solution of the problem. An illustrative numerical example is presented for the proposed method.

in this project guidance and control of underwater robot, including three engines and propeller attached to it, by fuzzy control has been investigated. fuzzy control is done based on human experience and requiered laws. the robot can also be controlled and guided by the user. this robot may be used in sea or swimming pool environment for finding goal point and locate in desired direction. in ad...

Model-based reinforcement learning methods are known to be highly efficient with respect to the number of trials required for learning optimal policies. In this article, a novel fuzzy model-based reinforcement learning approach, fuzzy prioritized sweeping (F-PS), is presented. The approach is capable of learning strategies for Markov decision problems with continuous state and action spaces. Th...

It is known that neuro-fuzzy system is easily stuck in local minimum. To improve these drawbacks, a two-stage algorithm combining the advantages of neuro-fuzzy and genetic algorithms (GA) is integrated in system identification. Genetic algorithms are general purposed optimization algorithms with adaptive reproduction, crossover, and mutation operators that provide a method to search optimal par...

A three-step method for function approximation with a fuzzy system is proposed. First, the membership functions and an initial rule representation are learned; second, the rules are compressed as much as possible using information theory; and nally, a computational network is constructed to compute the function value. This system is applied to two control examples: learning the truck and traile...