scholarly journals Evaluation of the stability enhancement of the conventional sliding mode controller using whale optimization algorithm

2021 ◽  
Vol 21 (2) ◽  
pp. 744
Author(s):  
Aws Mahmood Abdullah ◽  
Ali Mohsin Kaittan ◽  
Mustafa Sabah Taha
Keyword(s):  
Optimization Algorithm ◽  
Sliding Mode ◽  
Optimization Methods ◽  
Whale Optimization Algorithm ◽  
Sliding Mode Controller ◽  
Whale Optimization ◽  
The Stability ◽  
Stability Enhancement ◽  
The Impact ◽  
The Relationship

The proposed work is an attempt to investigate the stability of the nonlinear system by using a whale optimization algorithm as of one of the meta-heuristic optimization methods, and this investigation was conducted on a single inverted pendulum as a study model. The evaluation measures which were used in this article values of gain and sliding surface of the conventional sliding mode controller to illustrate the extent of the system`s stability. Furthermore, control action, the relationship between error and its derivative, desired, and actual position in addition to sliding response graphically showed the feasibility of the proposed solution. The attained results illustrated considerable improvement in the settling time and minimizing the impact of chattering behavior.

A Novel Two-Stage Structural Damage Identification Method Based on Superposition of Modal Flexibility Curvature and Whale Optimization Algorithm

2021 ◽  
pp. 2150169
Author(s):  
Minshui Huang ◽  
Xihao Cheng ◽  
Zhigang Zhu ◽  
Jin Luo ◽  
Jianfeng Gu
Keyword(s):  
Optimization Algorithm ◽  
Damage Identification ◽  
Whale Optimization Algorithm ◽  
Two Stage ◽  
Simply Supported ◽  
Damage Location ◽  
Flexibility Matrix ◽  
Modal Flexibility ◽  
Whale Optimization ◽  
The Impact

A novel two-stage method is proposed to properly identify the location and severity of damage in plate structures. In the first stage, a superposition of modal flexibility curvature (SMFC) is adopted to locate the damage accurately, and the identification index of modal flexibility matrix is improved. The low-order modal parameters are used and a new column matrix is formed based on the modal flexibility matrix before and after the structure is damaged. The difference of modal flexibility matrix is obtained, which is used as a damage identification index. Meanwhile, based on SMFC, a method of weakening the “vicinity effect” is proposed to eliminate the impact of the surrounding elements to the damaged elements when damage identification is carried out for the plate-type structure. In the second stage, the objective function based on the flexibility matrix is constructed, and according to the damage location identified in the first stage, the actual damage severity is determined by the enhanced whale optimization algorithm (EWOA). In addition, the effects of 3% and 10% noise on damage location and severity estimation are also studied. By taking a simply supported beam and a four-side simply supported plate as examples, the results show that the method can accurately estimate the damage location and quantify the damage severity without noise. When considering noise, the increase of noise level will not affect the assessment of damage location, but the error of quantifying damage severity will increase. In addition, damage identification of a steel-concrete composite bridge (I-40 Bridge) under four damage cases is carried out, and the results show that the modified method can evaluate the damage location and quantify 5%–92% of the damage severity.

scholarly journals Estimation of Transmission Line Parameters Using Voltage-Current Measurements and Whale Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3239
Author(s):  
Wael S. Hassanein ◽  
Marwa M. Ahmed ◽  
Mohamed I. Mosaad ◽  
A. Abu-Siada
Keyword(s):  
Transmission Line ◽  
Objective Function ◽  
Real Time ◽  
Optimization Algorithm ◽  
Time Estimation ◽  
Distribution Networks ◽  
Measured Data ◽  
Whale Optimization Algorithm ◽  
Whale Optimization ◽  
The Impact

Real-time estimation of transmission line (TL) parameters is essential for proper management of transmission and distribution networks. These parameters can be used to detect incipient faults within the line and hence avoid any potential consequences. While some attempts can be found in the literature to estimate TL parameters, the presented techniques are either complex or impractical. Moreover, none of the presented techniques published in the literature so far can be implemented in real time. This paper presents a cost-effective technique to estimate TL parameters in real time. The proposed technique employs easily accessible voltage and current data measured at both ends of the line. For simplicity, only one quarter of the measured data is sampled and utilized in a developed objective function that is solved using the whale optimization algorithm (WOA) to estimate the TL parameters. The proposed objective function comprises the sum of square errors of the measured data and the corresponding estimated values. The robustness of the proposed technique is tested on a simple two-bus and the IEEE 14-bus systems. The impact of uncertainties in the measured data including magnitude, phase, and communication delay on the performance of the proposed estimation technique is also investigated. Results reveal the effectiveness of the proposed method that can be implemented in real time to detect any incipient variations in the TL parameters due to abnormal or fault events.

scholarly journals An Improved Nonlinear Grey Bernoulli Model Based on the Whale Optimization Algorithm and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jianming Jiang ◽  
Ting Feng ◽  
Caixia Liu
Keyword(s):  
Optimization Algorithm ◽  
Structural Parameters ◽  
Optimization Methods ◽  
Whale Optimization Algorithm ◽  
Bernoulli Model ◽  
Proposed Model ◽  
Whale Optimization ◽  
Inherent Error ◽  
Applicable Range ◽  
The Difference

In order to improve the prediction performance of the existing nonlinear grey Bernoulli model and extend its applicable range, an improved nonlinear grey Bernoulli model is presented by using a grey modeling technique and optimization methods. First, the traditional whitening equation of nonlinear grey Bernoulli model is transformed into its linear formulae. Second, improved structural parameters of the model are proposed to eliminate the inherent error caused by the leap jumping from the differential equation to the difference one. As a result, an improved nonlinear grey Bernoulli model is obtained. Finally, the structural parameters of the model are calculated by the whale optimization algorithm. The numerical results of several examples show that the presented model’s prediction accuracy is higher than that of the existing models, and the proposed model is more suitable for these practical cases.

scholarly journals Grey Wolf and Weighted Whale Algorithm Optimized IT2 Fuzzy Sliding Mode Backstepping Control with Fractional-Order Command Filter for a Nonlinear Dynamic System

2021 ◽  
Vol 11 (2) ◽  
pp. 489
Author(s):  
Seongik Han
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Sliding Mode ◽  
Fuzzy Logic System ◽  
Backstepping Control ◽  
Whale Optimization Algorithm ◽  
Grey Wolf ◽  
Whale Optimization ◽  
Logic System

In this study, a fractional-order sliding mode backstepping control method was proposed, which involved the use of a fractional-order command filter, an interval type-2 fuzzy logic system approximation method, and a grey wolf and weighted whale optimization algorithm for multi-input multi-output nonlinear dynamic systems. For designing the stabilizing controls of the backstepping control, a novel fractional-order sliding mode surface was suggested. Further, the transformed errors that occurred during the recursive design steps were easily compensated by the controllers constructed using a new fractional-order command filter. Thus, the differentiation issue of the virtual control in the conventional backstepping control design could be bypassed with a simpler controller structure. Subsequently, the unknown plant dynamics were approximated by an interval type-2 fuzzy logic system. The uncertainties, such as the approximation error and the external disturbance, were compensated by the fractional-order sliding mode control that was added in the backstepping controller. Furthermore, the controller parameters and the fuzzy logic system were optimized via a grey wolf and weighted whale optimization algorithm to obtain a faster tuning process and an improved control performance. Simulation results demonstrated that the fractional-order sliding mode backstepping control scheme provides enhanced control performance over the conventional backstepping control system. Thus, in this paper, a fractional-order sliding mode surface and fractional-order backstepping control are studied, which provide more rapid convergence and enhanced robustness. Furthermore, a hybrid grey wolf and weighted whale optimization algorithm are proposed to provide an improved learning performance than those of conventional grey wolf optimization and weighted whale optimization methods.

scholarly journals An Improved Whale Optimization Algorithm with Random Evolution and Special Reinforcement Dual-Operation Strategy Collaboration

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 238
Author(s):  
Qibing Jin ◽  
Zhonghua Xu ◽  
Wu Cai
Keyword(s):  
Optimization Algorithm ◽  
Whale Optimization Algorithm ◽  
Evolutionary Strategies ◽  
Hammerstein Model ◽  
Local Optimum ◽  
Operation Strategy ◽  
Whale Optimization ◽  
Adaptive Weight ◽  
The Stability ◽  
Step Factor

In view of the slow convergence speed, difficulty of escaping from the local optimum, and difficulty maintaining the stability associated with the basic whale optimization algorithm (WOA), an improved WOA algorithm (REWOA) is proposed based on dual-operation strategy collaboration. Firstly, different evolutionary strategies are integrated into different dimensions of the algorithm structure to improve the convergence accuracy and the randomization operation of the random Gaussian distribution is used to increase the diversity of the population. Secondly, special reinforcements are made to the process involving whales searching for prey to enhance their exclusive exploration or exploitation capabilities, and a new skip step factor is proposed to enhance the optimizer’s ability to escape the local optimum. Finally, an adaptive weight factor is added to improve the stability of the algorithm and maintain a balance between exploration and exploitation. The effectiveness and feasibility of the proposed REWOA are verified with the benchmark functions and different experiments related to the identification of the Hammerstein model.

scholarly journals Controller design for underwater robotic vehicle based on improved whale optimization algorithm

2021 ◽  
Vol 10 (2) ◽  
pp. 609-618
Author(s):  
Mustafa Wassef Hasan ◽  
Nizar Hadi Abbas
Keyword(s):  
Motion Control ◽  
Optimization Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Vertical Motion ◽  
Whale Optimization Algorithm ◽  
Linear Quadratic ◽  
Specific Detail ◽  
Fixed Dimension ◽  
Whale Optimization ◽  
The Impact

This paper presents the impact of introducing a two-controller on the linearized autonomous underwater vehicle (AUV) for vertical motion control. These controllers are presented to overcome the sensor noise of the AUV control model that effect on the tolerance and stability of the depth motion control. Linear quadratic Gaussian (LQG) controller is cascaded with AUV model to adapt the tolerance and the stability of the system and compared with FOPID established by the improved whale optimization algorithm (IWOA) to identify which controlling method can make the system more harmonize and tolerable. The developed algorithm is based on improving the original WOA by reshaping a specific detail on WOA to earn a warranty that the new IWOA will have values for the update position lower than the identified lower-bound (LB), and upper-bound (UB). Furthermore, the algorithm is examined by a set of test functions that include (unimodal, multimodal and fixed dimension multimodal functions). The privileges of applying IWOA are reducing the executing time and obtaining the semi-optimal objective function as compared with the original WOA algorithm and other popular swarm-intelligence optimization algorithms.

scholarly journals Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm

2022 ◽  
Vol 12 (1) ◽  
pp. 293
Author(s):  
Randa Jalaa Yahya ◽  
Nizar Hadi Abbas
Keyword(s):  
Optimization Algorithm ◽  
Sliding Mode ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Grey Wolf Optimizer ◽  
Sliding Mode Controller ◽  
Grey Wolf ◽  
Integral Sliding Mode ◽  
Whale Optimization ◽  
Nature Inspired Algorithm

A newly hybrid nature-inspired algorithm called HSSGWOA is presented with the combination of the salp swarm algorithm (SSA) and grey wolf optimizer (GWO). The major idea is to combine the salp swarm algorithm's exploitation ability with the grey wolf optimizer's exploration ability to generate both variants' strength. The proposed algorithm uses to tune the parameters of the integral sliding mode controller (ISMC) that design to improve the dynamic performance of the two-link flexible joint manipulator. The efficiency and the capability of the proposed hybrid algorithm are evaluated based on the selected test functions. It is clear that when compared to other algorithms like SSA, GWO, differential evolution (DE), gravitational search algorithm (GSA), particles swarm optimization (PSO), and whale optimization algorithm (WOA). The ISMC parameters were tuned using the SSA, which was then compared to the HSSGWOA algorithm. The simulation results show the capabilities of the proposed algorithm, which gives an enhancement percentage of 57.46% compared to the standard algorithm for one of the links, and 55.86% for the other.

scholarly journals Anti-Disturbance Fault-Tolerant Sliding Mode Control for Systems with Unknown Faults and Disturbances

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1487
Author(s):  
Xiaoli Zhang ◽  
Zhengyu Zhu ◽  
Yang Yi
Keyword(s):  
Control Algorithm ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Actuator Faults ◽  
Controlled System ◽  
Simulation Results ◽  
The Stability ◽  
Mismatched Disturbances ◽  
The Impact

In this paper, a novel control algorithm with the capacity of fault tolerance and anti-disturbance is discussed for the systems subjected to actuator faults and mismatched disturbances. The fault diagnosis observer (FDO) and the disturbance observer (DO) are successively designed to estimate the dynamics of unknown faults and disturbances. Furthermore, with the help of the observed information, a sliding surface and the corresponding sliding mode controller are proposed to compensate the actuator faults and eliminate the impact of mismatched disturbances simultaneously. Meanwhile, the convex optimization algorithm is discussed to guarantee the stability of the controlled system. The favorable anti-disturbance and fault-tolerant results can also be proved. Finally, the validity of the algorithm is certified by the simulation results for typical unmanned aerial vehicles (UAV) systems.

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