Showing papers by "Mahdi Aliyari Shoorehdeli published in 2007"
27 Jun 2007
TL;DR: This algorithm is shown to be a better interpretation of continuous PSO into discrete PSO than the older versions and a number of benchmark optimization problems are solved using this concept and quite satisfactory results are obtained.
Abstract: Particle swarm optimization (PSO) as a novel computational intelligence technique, has succeeded in many continuous problems. But in discrete or binary version there are still some difficulties. In this paper a novel binary PSO is proposed. This algorithm proposes a new definition for the velocity vector of binary PSO. It will be shown that this algorithm is a better interpretation of continuous PSO into discrete PSO than the older versions. Also a number of benchmark optimization problems are solved using this concept and quite satisfactory results are obtained.
355 citations
27 Jun 2007
TL;DR: One of the swarm intelligent branches, named particle swarm optimization (PSO) with some modification in it is applied to the training of all parameters of ANFIS structure and is compared with basic PSO and showed quite satisfactory results.
Abstract: This paper introduces a new approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO) with some modification in it to the training of all parameters of ANFIS structure. These modifications are inspired by natural evolutions. Finally the method is applied to the identification of nonlinear dynamical system and is compared with basic PSO and showed quite satisfactory results.
110 citations
27 Jun 2007
TL;DR: Sliding mode control of rotary inverted pendulum is presented and based on this performance two sliding surfaces are designed, then system is controlled by proper definition of a lyapunov function.
Abstract: This paper presents sliding mode control of rotary inverted pendulum. Rotary inverted pendulum is a nonlinear, unstable and non-minimum-phase system. Designing sliding mode controller for such system is difficult in general. Here, first the desired performance is introduced and based on this performance two sliding surfaces are designed, then system is controlled by proper definition of a lyapunov function. The lyapunov function designed puts more emphasis on the control of the inverted pendulum rather than the control of the motor.
28 citations
12 Dec 2007
TL;DR: In this study, a fuzzy system is added to the classical sliding mode controller to adaptively estimate the equivalent signal of the sliding mode controllers and the stability of the controller and the adaptation law is guaranteed.
Abstract: In this study, a fuzzy sliding mode controller for a rotary inverted pendulum is designed. Sliding mode controllers are high performance nonlinear controllers. Not only Sliding mode controller stabilizes the system under control effectively but also it robustly compensates the effect of bounded uncertainties and shows invariance properties in the presence of bounded disturbance. In this study, a fuzzy system is added to the classical sliding mode controller to adaptively estimate the equivalent signal of the sliding mode controller. In addition, using Lyapunov theory the stability of the controller and the adaptation law is guaranteed.
26 citations
24 Sep 2007
TL;DR: This learning algorithm aims to solve main problems of the gradient descent based methods for the optimization of the RFNNs, which are instability, local minima and the problem of generalization of trained network to the test data.
Abstract: In this study, a hybrid learning algorithm for training the recurrent fuzzy neural network (RFNN) is introduced. This learning algorithm aims to solve main problems of the gradient descent (GD) based methods for the optimization of the RFNNs, which are instability, local minima and the problem of generalization of trained network to the test data. PSO as a global optimizer is used to optimize the parameters of the membership functions and the GD algorithm is used to optimize the consequent part's parameters of RFNN. As PSO is a derivative free optimization technique, a simpler method for the train of RFNN is achieved. Also the results are compared to GD algorithm.
17 citations
01 Oct 2007
TL;DR: In the new approaches, the classical method based on Lyapanov function is used, it is demonstrated that this new technique have good control ability performance and can be successfully used to stabilize any chosen operating point of the system.
Abstract: This study addresses new hybrid approaches for velocity control of an electro hydraulic servosystem (EHSS) in presence of flow nonlinearities and internal friction. In our new approaches, we combined classical method based-on sliding mode control and fuzzy RBF networks. The control by using adaptive networks need plant's Jacobean, but here this problem solved by sliding surface. It is demonstrated that this new technique have good ability control performance. It is shown that this technique can be successfully used to stabilize any chosen operating point of the system. All derived results are validated by computer simulation of a nonlinear mathematical model of the system. The controllers which introduced have big range for control the system.
8 citations
29 Aug 2007
TL;DR: A new combination of nonlinear backstepping scheme with on-line fuzzy system is presented for the rotary inverted pendulum system to achieve better performance in nonlinear controller.
Abstract: In this study a new combination of nonlinear backstepping scheme with on-line fuzzy system is presented for the rotary inverted pendulum system to achieve better performance in nonlinear controller. The inverted pendulum, a popular mechatronic application, exists in many different forms. The common thread among these systems is their goal: to balance a link on end using feedback control. The purpose of this study is to design a stabilizing controller that balances the inverted pendulum in the upright position.
1 citations
15 Dec 2007
TL;DR: A new combination of nonlinear backstepping scheme with fuzzy system is presented for controlling a rotary inverted pendulum system to achieve better performance in nonlinear controller approach.
Abstract: In this study a new combination of nonlinear backstepping scheme with fuzzy system is presented for controlling a rotary inverted pendulum system to achieve better performance in nonlinear controller approach. This study uses two different fuzzy systems: off-line and on-line to consider different concept. The purpose of this study is to design a stabilizing controller that balances the inverted pendulum in the up-right position.