Showing papers by "Mahdi Aliyari Shoorehdeli published in 2016"
TL;DR: The modified algorithm based on stability analysis is compared with the standard GSA, PSO, RGA, and two methods of improved GSA in terms of average, median, and standard deviation of best-so-far solutions and results demonstrate the validity and feasibility of the proposed modified GSA.
35 citations
TL;DR: Investigation on empirical accomplishments shows that the goal-oriented definition of Time–Variant Artificial Potential Fields is able to resolve the motion-planning problem in planetary applications.
Abstract: SUMMARY In this paper, a novel scheme is presented to conquer the motion-planning problem for autonomous space robots. Minimizing the consumed energy of atomic batteries within the daily planetary missions of robot on the planet is taken into account, i.e., utilization of the generated solar power by its embedded photocells leads to saving energy of batteries for night missions. Aforementioned objective could be acquired by appropriate interaction of motion planning paradigm with shadows of obstacles. Modeling of the shadow with the proposed artificial potential field leads to generalize the concept of potential fields not only for static and dynamic obstacles but also for being confronted with the intrinsic time-variant phenomena such as shadows. With due attention to the noticeable computational complexity of the introduced strategy, fuzzy techniques are applied to optimize the sampling times effectively. To accomplish this objective, a smart control scheme based on the fuzzy logic is mounted to the primitive version of algorithm. Regarding the need to identify some structural parameters of obstacles, PIONEER TM mobile robot is designed as a test bed for the verification of simulated results. Investigation on empirical accomplishments shows that the goal-oriented definition of Time‐Variant Artificial Potential Fields is able to resolve the motion-planning problem in planetary applications.
14 citations
01 Oct 2016
TL;DR: In this article, a simple analytic linear filter design based on a probabilistic model of the system was proposed for the deposition fault detection of a V94.2 gas turbine with 162.1 MW and 50 Hz nominal power and frequency respectively.
Abstract: Filtering is an effective method of alarm management family that can reduce false and missed alarm rates significantly. Simple and effective techniques of fault diagnosis methods are popular in industry. So, deriving a simple analytic filter design approach is important. This study proposes a simple analytic linear filter design based on a probabilistic model of the system. At last, the effectiveness of the proposed method is showed in the deposition fault detection of a V94.2 gas turbine with 162.1 MW and 50 Hz as the nominal power and frequency respectively. It is built by MAPNA group (originally built by SIEMENS) and set up in Shiraz power plant, Shiraz city of Iran.
7 citations
10 May 2016
TL;DR: A transparent neural network structure for identification of dynamic terms by introducing a gray-box identifier is proposed for a data-driven identification of robot dynamics and results indicate the applicability of the proposed method.
Abstract: In this paper, a novel architecture in multilayer per-ceptron (MLP) neural network with flexible activation function and adaptive learning rate is presented for a data-driven identification of robot dynamics. It is assumed that the measurement of robot end-effector position, velocity and acceleration are available corrupted by Gaussian noise. Since some general property of robot dynamics are included in the proposed structure as well as optimization indices, this structure is envisaged having good performance in confronting with uncertainty in measurements. The main contribution of this paper is to propose a transparent neural network structure for identification of dynamic terms by introducing a gray-box identifier. Simulation results on 2-DOF serial manipulator reveal the accuracy of the method. Finally, experimental results on a laboratory-scaled twin rotor CE 150 helicopter indicate the applicability of the proposed method.
5 citations
TL;DR: Full probability distribution of parameters of ARX model is obtained for on-line problems by means of Bayesian approach and Markov chain Monte Carlo method (MCMC), which provides the ability to be applied on time-varying ARX models as well.
1 citations
05 Dec 2016
TL;DR: In this article, two modified feedback error learning (FEL) methods are suggested and their effectiveness are validated by experimental tracking data and the experimental results show that the proposed algorithms are able to give good performance regardless of any uncertainties.
Abstract: In this study, a new adaptive controller is proposed for position control of pneumatic systems. Difficulties associated with the mathematical model of the system in addition to the instability caused by Pulse Width Modulation (PWM) in the learning-based controllers using gradient descent, motivate the development of a new approach for PWM pneumatics. In this study, two modified Feedback Error Learning (FEL) methods are suggested and the their effectiveness are validated by experimental tracking data. The first one is a combination of PD (ProportionalâDerivative) and RBF (Radial Basis Function) and in the second one RBF is replaced by ANFIS (Adaptive Neuro-Fuzzy Inference System). The robustness to varying mass is also examined. The experimental results show that the proposed algorithms, especially with ANFIS, are able to give good performance regardless of any uncertainties.