Speed control of electrical vehicles: a time‐varying proportional–integral controller‐based type‐2 fuzzy logic

Khooban, Mohammad Hassan; Niknam, Taher; Shasadeghi, Mokhtar

doi:10.1049/iet-smt.2015.0033

Cited by 56 publications

(30 citation statements)

References 21 publications

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“…Thus, based on Lemma 1 we can conclude that ( ) → 0 is asymptotically stable in the sense of Lyapunov process. From (13) and (20)- (21), it can infer that the active force to control the MRD-based railway suspension can be separated into two parts as in (22), in which the main part, ( ), comes from the Ad-op-SMC as in (23), while the second part, ( ), is the supplement active force estimated by the NUO given in (24).…”

Section: Design Of the Nuomentioning

confidence: 99%

“…The role of the NUO is to estimate = ( ), meaninĝin (13). In [9], based on the theory of nonlinear dynamic inversion control presented in [17], S. D. Nguyen and Q. H. Nguyen have presented the NUO for estimating the impact of lumped disturbance aspects.…”

Section: Design Of the Nuomentioning

confidence: 99%

“…Focusing on this, various studies have been carried out. For example, applying the sliding mode technique [1][2][3][4][5], interpolating control rules of fuzzy logic [6][7][8][9][10][11][12][13], or building observers to compensate for the influence of UAD has obtained positive results [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…Regarding these applications, both the type 1 fuzzy logic system (T-1FLS) and the type 2 fuzzy logic system (T-2FLS) can all be utilized. However, reality shows that, in case of having to cope with difficulties related to UAD or noise, T-2FLS has significant advantages compared with the other [7,12,13,[23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Robust Vibration Control of a Magnetorheological Damper Based Railway Suspension Using a Novel Adaptive Type 2 Fuzzy Sliding Mode Controller

Nguyen

Jung

Choi

2017

Shock and Vibration

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This work proposes a novel adaptive type 2 fuzzy sliding controller (AT2FC) for vibration control of magnetorheological damper-(MRD-) based railway suspensions subjected to uncertainty and disturbance (UAD). The AT2FC is constituted of four main parts. The first one is a sliding mode controller (SMC) for specifying the main damping force supporting the suspension. This controller is designed via Lyapunov stability theory. The second one is an interpolation model based on an interval type 2 fuzzy logic system for determination of optimal parameters of the SMC. The third one is a nonlinear UAD observer to compensate for external disturbances. The fourth one is an inverse MRD model (T2F-I-MRD) for specifying the input current. In the operating process, an adaptively optimal structure deriving from the SMC is created (called the Ad-op-SMC) to adapt to the real status. Working as an actuator, the input current for MRD is then determined by the T2F-I-MRD to generate the required damping force which is estimated by the Ad-op-SMC and the nonlinear observer. It is shown that the obtained survey results reflect the AT2FC's excellent vibration control performance compared with the other controllers.

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Section: Design Of the Nuomentioning

confidence: 99%

Section: Design Of the Nuomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Robust Vibration Control of a Magnetorheological Damper Based Railway Suspension Using a Novel Adaptive Type 2 Fuzzy Sliding Mode Controller

Nguyen

Jung

Choi

2017

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…A novel nonlinear model predictive controller (MPC) based on Takagi-Sugeno fuzzy model, has been proposed for electric vehicle applications [12].The merits of the approach are highlighted by comparing the results of the proposed approach with those of the conventional MPC controller and the optimal fuzzy PI controller. A similar approach based on time varying PI controller based Type 2 FL for speed control of electric vehicle was proposed in [13], in order to get an optimal performance and reduced computation complexity. An intelligent robust PI adaptive control strategy for speed control of Electric vehicles is reported in the literature [14].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Self Tuned Fuzzy PID controller for speed control of Brushless DC Motor

2016

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Original scientific paperThe objective of the proposed work is to investigate the performance of hybrid self tuned fuzzy proportional integral derivative (STFPID) controller for brushless DC (BLDC) motor drive. The proposed hybrid STFPID controller includes a proportional integral derivative (PID) controller at steady state, a PID type self tuned fuzzy logic (FL) controller (STFLC) at transient state thereby combining the merits of both the controllers. The switching function incorporated in the controller ensures desired control response at various operating conditions by appropriately switching between PID and STFPID based on speed error. A detailed simulation study and performance comparison with other control approaches is performed to highlight the merits of the proposed work. The simulation results indicate that the proposed controller is robust with fast tracking capability and less steady state error. The experimental results are provided to validate the simulation study.Key words: BLDC motor drive, speed control, self tuned fuzzy logic controller, Hybrid controller, PID controller.Hibridni samopodešavajući neizraziti PID regulator za upravljanje brzinom bezkolektorskog istosmjernog motora.Cilj ovog rada je istražiti performance hibridnog samopodešavajućeg regulatora za bezkolektorski istosmjerni motor. Predloženi hibridni samopodešavajući neizraziti regulator uključuje PID regulator u stacionarnom stanju i samopodešavajući neizraziti PID regulator (STFLC) za vrijeme trajanja prijelazne pojave kombinirajući prednosti oba regulatora. Funkcija prekapčanja regulatora omogućava upravljanje u različitim uvjetima odgovarajućim odabirom izme u PID i samopodešavajućeg neizrazitog PID regulatora na temelju brzine pogreške. Provedena je detaljna simulacijska analiza i usporedba performansi s ostalim metodama upravljanja kako bi se istaknule prednosti predloženog rada. Iz simulacijskih rezultata je vidljivo je robusno svojstvo predloženenog regulatora te smanjena pogreška u stacionarnom stanju. Sustav pravljanja testiran je i eksperimentalno kao potvrda simulacijskih rezultata.

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A Novel Robust Constraint Force Servo Control for Under‐actuated Manipulator Systems: Fuzzy and Optimal

Dong

Han

Chen

et al. 2017

Asian Journal of Control

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We consider the control design for under‐actuated manipulator systems. The task is to drive the system to be close to a prescribed constraint. The system contains uncertainty. It is bounded where the bounding information is prescribed by a fuzzy set (e.g., the bound is close to 1). The initial condition is also prescribed by a fuzzy set. A class of robust control is proposed, which guarantees a deterministic performance. On top of that, the choice of a control design parameter is cast into a fuzzy‐theoretic setting. A performance index, consisting of accumulated fuzzy‐based system performance and control cost, is proposed. The optimal control design parameters, which minimize the performance index, can be obtained by solving two algebraic quartic (fourth‐order) equations. As a result, the control design problem, which addresses both fuzzy and optimal characteristics, is completely solved.

show abstract

Speed control of electrical vehicles: a time‐varying proportional–integral controller‐based type‐2 fuzzy logic

Cited by 56 publications

References 21 publications

A Robust Vibration Control of a Magnetorheological Damper Based Railway Suspension Using a Novel Adaptive Type 2 Fuzzy Sliding Mode Controller

A Robust Vibration Control of a Magnetorheological Damper Based Railway Suspension Using a Novel Adaptive Type 2 Fuzzy Sliding Mode Controller

Hybrid Self Tuned Fuzzy PID controller for speed control of Brushless DC Motor

A Novel Robust Constraint Force Servo Control for Under‐actuated Manipulator Systems: Fuzzy and Optimal

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