Spatial modeling, identification and adaptive second order sliding mode control of a micro air vehicle

Castañeda, Herman; Gordillo, José Luís

doi:10.1109/icuas.2017.7991320

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Here, the estimation of the sliding parameter is not required, and thus it diminishes the amount of sensors essential for the execution control. The second-order sliding mode control (SoSMC) incorporates the foremost consequences of standard sliding modes, and thus it can be further nominated to eradicate the chattering effect, thus contributing piecewise control (Castañeda & Gordillo, 2017; Naik & Mehta, 2017; Zhifu, Yang, Chaopeng, & Jun, 2016). This approach also provides enhanced accurateness with respect to the delays in switching.…”

Section: Introductionmentioning

confidence: 99%

A novel adaptive second-order sliding mode controller for autonomous underwater vehicles

Roy

Ghoshal

2019

Adaptive Behavior

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Navigating, directing, and controlling autonomous underwater vehicles (AUVs) are demanding and considered complicated compared to the autonomous surface-level performance. In such vehicles, the motion can be controlled depending on the estimation of indefinite hydrodynamic forces and the disturbances that occurs in this vehicle in the underwater background. In this article, Gray Wolf optimization (GWO) is performed along with the second-order sliding mode control (GW-SoSMC) approach for controlling the yaw angle in AUV. The main purpose of the article is to reduce the error that occurs in the system between the controlled signal and desired signal corresponding to yaw angle. Using this proposed model, both the occurrence of chattering and the controlling performance of AUV system can be diminished. Moreover, the proposed model is compared with the existing approaches like, FireFly-SoSMC (FF-SoSMC), Genetic Algorithm-SoSMC (GA-SoSMC), Gray Wolf-SMC (GW-SMC), Group search optimization-SoSMC (GSO-SoSMC) and Artificial Bee Colony-SoSMC (ABC-SoSMC). From the simulation results, it shows that the performance of the implemented technique in terms of steady-state response, error analysis, yaw angle analysis, and controller response is enhanced while comparing with the existing approaches.

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Section: Introductionmentioning

confidence: 99%

A novel adaptive second-order sliding mode controller for autonomous underwater vehicles

Roy

Ghoshal

2019

Adaptive Behavior

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“…It does not need the derivative of the sliding parameter to be observed or calculated and thus minimizes the number of sensors needed for implementation control. Second-order SMC includes the major significance of standard sliding modes, and it can be further adopted to eliminate chattering effect, thus offering piecewise control (Castañeda and Gordillo, 2017;Listwan and Pie nkowski, 2017;Liu et al, 2017;Ravi and Monica, 2018;Shareef and Srinivasa Rao, 2018;Zeng et al, 2019). The technique also offers better accuracy regarding the delays in switching.…”

Section: Introductionmentioning

confidence: 99%

Advanced heavy water reactor control with the aid of adaptive second-order sliding mode controller

Roy

Ghoshal

2019

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Purpose Advanced heavy water reactor (AHWR) is a pressure tube type of heavy water reactor. It eliminates high-pressure heavy water coolant resulting in a reduction of heavy water leakage losses and eliminating heavy water recovery system. It recovers the heat generated in the moderator for feed water heating. However, it requires a satisfactory technological response to develop an effective controller that attains the challenges of the very high-level safety system. Hence, they require application-specific improvement for better controlling performance. Design/methodology/approach The purpose of this study intends to propose a system for controlling state vectors v1 and v2and in AHWR using Grey Wolf second-order sliding mode control (GW-SoSMC) technique. The main aim of the paper is to minimize the errors between the predicted and desired azimuthal angles of the system. With this proposed method, it is possible to mitigate both the chattering phenomenon and controlling performance of AHWR system. It implements a SoSMC controller based on GWO algorithm for the purpose of controlling the state vectors in the AHWR system. It aims to accomplish a controller for improving the performance of the AHWR system. Findings Through the performance analysis, the efficiency of the proposed GW-SoSMC technique was verified by comparing it with various conventional algorithms, such as GW-SMC, FF-SoSMC, ABC-SoSMC, GS-SoSMC and GA-SoSMC. From the analysis, it was obtained that the implemented GW-SoSMC technique was 65.3 per cent superior to GW-SMC, 65.32 per cent superior to both FF-SoSMC and 65 per cent superior to ABC-SoSMC, 65.8 per cent superior to the GS-SoSMC and 58 per cent superior to the GA-SoSMC methods. Thus, the effectiveness of the proposed method in controlling the state vectors in AHWR was obtained. Originality/value This paper presents a technique for controlling the state vectors in the AHWR system using GWO algorithm. This is the first work that uses GWO-based optimization for controlling state vectors in the AHWR system.

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Spatial Modeling and Robust Flight Control Based on Adaptive Sliding Mode Approach for a Quadrotor MAV

Castañeda

Gordillo

2018

J Intell Robot Syst

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Spatial modeling, identification and adaptive second order sliding mode control of a micro air vehicle

Cited by 4 publications

References 19 publications

A novel adaptive second-order sliding mode controller for autonomous underwater vehicles

A novel adaptive second-order sliding mode controller for autonomous underwater vehicles

Advanced heavy water reactor control with the aid of adaptive second-order sliding mode controller

Spatial Modeling and Robust Flight Control Based on Adaptive Sliding Mode Approach for a Quadrotor MAV

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