Fractional order sliding-mode control based on parameters auto-tuning for velocity control of permanent magnet synchronous motor

Zhang, Bitao; Pi, Yiming; Luo, Ying

doi:10.1016/j.isatra.2012.04.006

Cited by 214 publications

(126 citation statements)

References 16 publications

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“…These controllers not only deal with the uncertainties in ABS, but also track the desired slip faster than conventional integer-order SMC (IOSMC). Additionally, FOSMC has been employed for speed control of permanent magnet synchronous motors, 19,20 for vibration suppression of uncertain structures, 21 for control design of uncertain nonlinear systems, 22,23 for control of fractional-order chaotic systems, 24,25 and so on and achieved better control capacities. To date, most of the research on FOSMC has focused on the fractional-order switching manifold, these FOSMC strategies improve the control capacities of conventional IOSMC by employing fractional-order switching manifold, but they cannot achieve optimal control performance without additional measures.…”

Section: 6mentioning

confidence: 99%

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Fractional-order sliding mode control for a class of uncertain nonlinear systems based on LQR

Zhang

Cao

Tang

2017

International Journal of Advanced Robotic Systems

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This article presents a new fractional-order sliding mode control (FOSMC) strategy based on a linear-quadratic regulator (LQR) for a class of uncertain nonlinear systems. First, input/output feedback linearization is used to linearize the nonlinear system and decouple tracking error dynamics. Second, LQR is designed to ensure that the tracking error dynamics converges to the equilibrium point as soon as possible. Based on LQR, a novel fractional-order sliding surface is introduced. Subsequently, the FOSMC is designed to reject system uncertainties and reduce the magnitude of control chattering. Then, the global stability of the closed-loop control system is analytically proved using Lyapunov stability theory. Finally, a typical single-input single-output system and a typical multi-input multi-output system are simulated to illustrate the effectiveness and advantages of the proposed control strategy. The results of the simulation indicate that the proposed control strategy exhibits excellent performance and robustness with system uncertainties. Compared to conventional integer-order sliding mode control, the high-frequency chattering of the control input is drastically depressed.

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Section: 6mentioning

confidence: 99%

“…Considering the tacking error dynamics of system (13), if it is controlled with the fractional sliding mode controlling law described by v i ¼ v n þ v s , where v n and v i are defined by (17) and (23), respectively, then the tracking error trajectory will converge to the proposed sliding surface (20) in finite time.…”

Section: Lyapunov Stability Analysismentioning

confidence: 99%

Fractional-order sliding mode control for a class of uncertain nonlinear systems based on LQR

Zhang

Cao

Tang

2017

International Journal of Advanced Robotic Systems

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“…The approach which uses the FOPID sliding surface was also studied in [17,18]. A FOSMC based on a fractional order PD (FOPD) sliding surface was studied in [19,20] and a Fractional Order Terminal Sliding Mode Control (FOTSMC) was proposed in [21].…”

Section: Introductionmentioning

confidence: 99%

Sliding-Mode Controller Based on Fractional Order Calculus for a Class of Nonlinear Systems

Bouarroudj¹,

Boukhetala²,

Boudjema³

2016

IJECE

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This paper presents a new approach of fractional order sliding mode controllers (FOSMC) for a class of nonlinear systems which have a single input and two outputs (SITO). Firstly, two fractional order sliding surfaces S1 and S2 were proposed with an intermediate variable z transferred from S2 to S1 in order to hierarchy the two sliding surfaces. Secondly, a control law was determined in order to control the two outputs. A sliding control stability condition was obtained by using the properties of the fractional order calculus. Finally, the effectiveness and robustness of the proposed approach were demonstrated by comparing its performance with the one of the conventional sliding mode controller (SMC), which is based on integer order derivatives. Simulation results were provided for the case of controlling an inverted pendulum system.Copyright c 2016 Institute of Advanced Engineering and Science.All rights reserved.Corresponding Author: Noureddine Bouarroudj LCP, Ecole Nationale Polytechnique, 10 av. Hassen Badi, BP. 182, El-Harrach, Alger, Algeria Email: autonour@gmail.com INTRODUCTIONSliding mode control has largely proved its effectiveness in numerous applications, see, e.g., the studies by Utkin [1] and Slotine [2]. The first step of the SMC design is to select a sliding surface that models the desired closedloop performance in state variable space. In the second step, equivalent and hitting control laws are designed such that the system state trajectories are forced towards the sliding surface and slide along it to the desired attitude.An advantage of these methods of control (SMC) is their robustness to parameters variation and bounded external disturbances. The robustness is attributed to the discontinuous term in the control input. However, this discontinuous term also causes an undesirable effect called chattering. Sometimes this discontinuous control action can even cause instability of the system. This effect can be alleviated by, for example, introducing a sat function and taking off the sgn function in the hitting control law of the SMC.In the last years, the control of single-input-two output non-linear dynamical systems has risen some interest in the control research community; in general, the controller (input) is done for the trajectory tracking of the two outputs. PID controllers were applied in [3] to the stabilization and tracking control of three types of inverted pendulum. A PID+LQR method was given in [4], in which the LQR was added negatively to the PID in order to have a resultant optimal control. A fuzzy controller with estimation of scaling factors was studied in [5]. An intelligent control system based on an interval type-2 fuzzy PD controller was studied in [6]. The SMC design for this kind of systems is a very challenging task. Such developed controllers include the decoupled SMC shown in [7], a Fuzzy Sliding Mode Control (FSMC) that was tuned using ant colony optimization [8], [9] and a decoupled SM with a fuzzy-neural network controller [10] where the fuzzy-neural network w...

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“…In fact, many systems can be described by fractional differential equations, for example, dielectric polarization, electrode-electrolyte polarization, electromagnetic waves, visco-elastic systems, quantitative finance, bioengineering, diffusion wave and nuclear magnetic resonance [5,10,13,14,19,30,31,32].…”

Section: Introductionmentioning

confidence: 99%

Synchronization of fractional-order chaotic systems with multiple delays by a new approach

Hu¹,

Wei²,

Zhao³

2016

Kybernetika

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Fractional order sliding-mode control based on parameters auto-tuning for velocity control of permanent magnet synchronous motor

Cited by 214 publications

References 16 publications

Fractional-order sliding mode control for a class of uncertain nonlinear systems based on LQR

Fractional-order sliding mode control for a class of uncertain nonlinear systems based on LQR

Sliding-Mode Controller Based on Fractional Order Calculus for a Class of Nonlinear Systems

Synchronization of fractional-order chaotic systems with multiple delays by a new approach

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