Development of a self-tuning fuzzy logic controller for intelligent control of elevator systems

Jamaludin, Jafferi; Rahim, N.A.; Hew, W.P.

doi:10.1016/j.engappai.2009.04.006

Cited by 35 publications

(15 citation statements)

References 19 publications

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“…Recently, type-2 fuzzy sets have been successfully applied on different applications as type-2 fuzzy neural network [43], image processing [44], embedding intelligent agents [45], pattern recognition [46,47], mobile robots control [48], and fuzzy controller designs [49,50].…”

Section: Introductionmentioning

confidence: 99%

Synchronization of two different chaotic systems using novel adaptive interval type-2 fuzzy sliding mode control

et al. 2011

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In this paper, we use sliding mode control integrated with an interval type-2 fuzzy system for synchronization of two different chaotic systems in presence of system unmodeling and external disturbances. To reduce the chattering and improve the robustness of reaching phase of the Sliding Mode Control (SMC), an interval fuzzy type-2 logic controller is used. In addition, an adaptive interval type-2 fuzzy inference approximator is proposed (as equivalent control part of SMC) to approximate the unknown parts of the uncertain chaotic system. Using type-2 fuzzy systems makes more effective synchronization results in presence of system uncertainty and disturbances in comparison with type-1 fuzzy approximators. The stability analysis for the proposed control scheme is provided, and simulation results compare the performance of interval type-2 fuzzy and type-1 fuzzy con-M. Roopaei ( ) · trollers to verify the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Synchronization of two different chaotic systems using novel adaptive interval type-2 fuzzy sliding mode control

et al. 2011

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“…Simultaneously, a new fuzzy gains auto-tuning strategy is used to guarantee the smoothness of control law and good dynamic and static performance of the control system. Many literatures have proposed the concept of fuzzy gain auto-tuning [3][4][5], but they focused mainly on adaptation of the control system to the changing conditions. To achieve high steady precision and fast dynamic response with no overshoot, FC parameters are designed and regulated according to the output.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy sliding mode control of the A-axis with high torque and high power

Zhao

2015

Fifth Asia International Symposium on Mechatronics (AISM 2015)

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For the influence of nonlinear backlash and friction on positioning precision of the A-axis in 5-axis machine tools, the fuzzy controller (FC) with gain auto-tuning and fuzzy sliding mode controller (FSMC) with gains auto-tuning are proposed. For the former, the control law mutation caused by gain switching in traditional fuzzy control is eliminated by introducing the gain auto-tuning based on the continuous exponential function of the error. For the latter, chattering phenomenon in traditional SMC is eliminated by employing the FC to approximate the nonlinear function item in the equivalent control law. Experimental results show that both the two control algorithms can achieve higher steady state precision and faster dynamic response with zero overshoot.

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“…As the elevator group control system is a complex nonlinear dynamic discrete system, the waiting time, taking time for an elevator, energy loss and other factors as the control objectives, the control system are all very large. In order to shorten people's waiting time, take the time for an elevator, to reduce energy loss, the shortest waiting time, shortest distance, genetic algorithms, fuzzy control, a variety of elevator group control scheduling method [2,3], but now some elevator control technology there are still shortcomings and deficiencies. The advanced technology used in elevator group control system to further improve the operating efficiency of the existing elevator system to meet passengers' demand, further research is still required.…”

Section: Introductionmentioning

confidence: 99%

A novel elevator group control scheduling algorithm based on pseudo differential feedback

2012

2012 IEEE International Conference on Automation and Logistics

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For the non-determinacy of transportation characteristics of the elevator group control scheduling process, an elevator group control system model is established, which including the shortest waiting time, the shortest by ladder time and the least energy consumption. Along with a scheduling strategy of elevator group control based on pseudo differential feedback (PDF) control which can content the requirement of an adaptable elevator group control performance is presented. The algorithm will be improved to achieve better dispatching result and simulation experiment effect finally. The simulation results show that this method compared with other algorithms in elevator group control scheduling performance and traffic model's adaptability has greatly improved.Index Terms -non-determinacy; pseudo differential feedback; elevator group control strategy.

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Development of a self-tuning fuzzy logic controller for intelligent control of elevator systems

Cited by 35 publications

References 19 publications

Synchronization of two different chaotic systems using novel adaptive interval type-2 fuzzy sliding mode control

Synchronization of two different chaotic systems using novel adaptive interval type-2 fuzzy sliding mode control

Fuzzy sliding mode control of the A-axis with high torque and high power

A novel elevator group control scheduling algorithm based on pseudo differential feedback

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