Designing an optimal fuzzy sliding mode control for a two-link robot

Taran, Babak; Pirmohammadi, A. A.

doi:10.1007/s40430-019-2073-4

Cited by 12 publications

(3 citation statements)

References 10 publications

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“…Secondly a mechanism of control knowledge base is very primary to develop for using the input and output linguistic parameter's description. Four different methods have been suggested for achieving this [41][42][43][44][45]: self-organization, modeling of operator's control operation, expert's experience and knowledge, and modeling a process. From the methods discussed above, the third one is the most widely used method.…”

Section: Control Knowledge Basementioning

confidence: 99%

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

et al. 2021

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Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature.

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Section: Control Knowledge Basementioning

confidence: 99%

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

et al. 2021

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“…However, if the constant k is increased, then the convergence rate is accelerated, but the chattering in the sliding mode stage is strengthened; if the constant ε is reduced, then the chattering in the sliding mode stage is weakened, but the convergence rate in the motion stage is slow. e general index approach rate is usually a compromise method to determine the constant but does not efficiently solves this problem [26]. e improved power exponential approach rate is selected to overcome the shortcomings of the exponential approach rate [27]:…”

Section: Design Of the Fuzzy Sliding Mode Controllermentioning

confidence: 99%

Fuzzy Sliding Mode Control of a VAV Air-Conditioning Terminal Temperature System

Niu

Yang

et al. 2020

Complexity

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A varied air volume (VAV) air-conditioning system comprises diverse input and/or output disturbances, which are commonly nonlinear, with large lag and uncertainty. Based on the traditional control methods, testing the controlling parameters of a VAV air-conditioning system is challenging. Sliding mode control could improve the robustness of the system due to the adaptive capacity of disturbance rejection. Moreover, the fuzzy algorithm could be employed to determine the stability of a sliding control system by adjusting the parameters in the approach rate, reducing the switching frequency, and weakening chatter. Fuzzy sliding mode control is investigated in this paper to improve the performance of a VAV air-conditioning system. Simulation results verify that the sliding mode control is suitable for a VAV air-conditioning system to achieve good adaptability and robustness considering the influence of multiple external variable disturbances. In addition, the chattering of the system is improved after the introduction of fuzzy control.

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“…In their model, the masses of the links are considered to be uncertain parameters. 27 By combining SMC with an optimal strategy based on SDRE, optimality properties can also be added. To this end, for an attitude-tracking spacecraft, Pukdeboon designed a controller that combined SMC with control Lyapunov function utilizing the state estimation method of SDRE to find state variables.…”

Section: Introductionmentioning

confidence: 99%

Designing an optimal control strategy for a mobile manipulator and its application by considering the effect of uncertainties and wheel slipping

Korayem

Ghobadi

Dehkordi

2021

Optim Control Appl Methods

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This article seeks to develop the dynamic model of a mobile robot for controlling purposes while the effects of uncertainties and longitudinal and lateral slip are assumed. The rise in the number of state variables and considering the effects of nonlinear parameters due to slip modeling can complicate the control procedure of wheeled mobile manipulators. In addition, the existence of uncertainties as well as holonomic and nonholonomic constraints would increase this complexity even more. On the one side, as wheels are considered to slip, unwanted movements due to slippage affect the movement of the manipulator and the manipulator may not be able to track the desired path. On the other side, the movement of weighted links of the manipulator constantly changes the normal forces of the wheels. As traction forces are dependent on these normal forces, the path tracked by the platform would be affected. Given these conditions, employing a robust control methodology and developing an optimal algorithm to reduce the effects of uncertainties and wheels slip seems mandatory. To this aim, a sliding mode control (SMC) strategy is formulated in this study. Furthermore, the suggested algorithm is optimized using a state-dependent Riccati equation to reduce the consumed torque and increase the accuracy of the system. Simulations are conducted, and the presented algorithm is also checked with the experimental setup of a Scout robot. Simulation results show that the optimal sliding mode control (OSMC) successfully decreases sudden jumps due to slippage in the system. In addition, the consumed power of wheels and arm for SMC decreases from 9.15 and 1.02 N⋅m to, respectively, 1.46 and 0.54 N⋅m for OSMC.

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Designing an optimal fuzzy sliding mode control for a two-link robot

Cited by 12 publications

References 10 publications

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

Fuzzy Sliding Mode Control of a VAV Air-Conditioning Terminal Temperature System

Designing an optimal control strategy for a mobile manipulator and its application by considering the effect of uncertainties and wheel slipping

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