Advanced and Optimization Based Sliding Mode Control: Theory and Applications

Ferrara, Antonella; Incremona, Gian Paolo; Cucuzzella, Michele

doi:10.1137/1.9781611975840

Cited by 58 publications

(60 citation statements)

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“…These parameters are accountable for reaching the sliding surface and reducing the chattering problem. It is observed that several researchers have used the metaheuristic algorithm to determine the values of K D and δ [20]. Nelder and Mead searching algorithm is utilized by [8,15] to achieve the K D and δ values.…”

Section: The Proposed Sliding Mode Controller Designmentioning

confidence: 99%

Sliding mode controller design for second-order unstable processes with dead-time

Siddiqui

Anwar

Laskar

2020

Journal of Electrical Engineering

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A new approach is proposed to design the sliding mode (SM) controller for the unstable second-order plus dead-time (SOPDT) processes. The sliding mode control consists of two control laws ie continuous control law and discontinuous control law. The continuous control law parameters have been derived in terms of unstable SOPDT process parameters using the root locus technique. On the other hand, the parameters of discontinuous control law are tuned by optimizing a performance index using a recently developed metaheuristic search algorithm, namely the grasshopper optimization technique. The performance index is framed to achieve a good trade-off between performance and control efforts. Finally, simulations are conducted to validate the effectiveness of the proposed approach over the other existing techniques. It is observed that the proposed approach is able to deliver better disturbance rejection, minimal control efforts and good setpoint tracking.

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Section: The Proposed Sliding Mode Controller Designmentioning

confidence: 99%

Sliding mode controller design for second-order unstable processes with dead-time

Siddiqui

Anwar

Laskar

2020

Journal of Electrical Engineering

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“…After the introduction of a saturation function, the controller will no longer be a classic sliding mode controller. According to References [41,42], the sat function implies a pseudo sliding mode in fact.…”

Section: W(t)mentioning

confidence: 99%

Energy-Efficient Speed Profile Optimization and Sliding Mode Speed Tracking for Metros

et al. 2020

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Nowadays, most metro vehicles are equipped with an automatic train operation (ATO) system, and the speed control method, combining cruise speed planning and proportional-integral-derivative (PID) control, is widely used. The automation is achieved, and the energy-efficient can be improved. This paper presents an improved artificial bee colony algorithm for speed profile optimization with coast mode and an adaptive terminal sliding mode method for speed tracking. Specifically, a multi-objective optimization model is established, which considers energy consumption, comfortableness, and punctuality. Then, a novel artificial bee colony algorithm named regional reinforcement artificial bee colony (RR-ABC) is designed, to search the optimal speed profile with coast mode, in which some improvements are made to speed up convergence and to avoid local optimal solutions. For speed-tracking control, the adaptive terminal sliding mode controller (ATSMC) is used to improve the speed error, robustness, and energy saving. In addition, a disturbance observer (DOB) is designed to improve the anti-interference ability of the system and further improve the robustness and anti-disturbance, which are also conducive to speed error and energy saving. Finally, the line and train data of the Qingdao Metro Line 6 are used for simulation, which proves the effectiveness of the study. Specific to the energy saving rate, and compared with normal algorithms, RR-ABC with coast mode is approximately 9.55%, and ATSMC+DOB is 7.58%.

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“…When a sliding mode control approach is adopted, the controlled system state regulation is obtained through the finite time stabilization of a particular system output called "sliding variable". In case of uncertain nonlinear systems of relativedegree-2, a possible solution to the finite time regulation problem is offered by higher-order sliding mode control [6]. This kind of control has the capability of steering to zero in finite time not only the sliding variable, but also its time derivatives up to a certain order, so that the control signal actually fed into the plant is continuous [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

Predefined-Time Output Stabilization With Second Order Sliding Mode Generation

Ferrara

Incremona

2021

IEEE Trans. Automat. Contr.

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In this paper a novel second order sliding mode control strategy is proposed for relative-degree-2 nonlinear uncertain SISO systems. To design the strategy, it is studied the phase portrait of the second order system in normal form associated with the formulated sliding mode control problem. A sliding surface switching between arcs of parabolas is conceived to ensure the convergence in a predefined time to the desired second order sliding mode. Lyapunov-based analysis and the reformulation of LaSalle-Yoshizawa results for nonsmooth systems are used to prove the uniform finite-time stability of the equilibrium consisting in the second order sliding mode enforcement. This in turns allows to prove the asymptotic convergence of the original plant state to the origin in spite of the uncertainties.

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Advanced and Optimization Based Sliding Mode Control: Theory and Applications

Cited by 58 publications

References 0 publications

Sliding mode controller design for second-order unstable processes with dead-time

Sliding mode controller design for second-order unstable processes with dead-time

Energy-Efficient Speed Profile Optimization and Sliding Mode Speed Tracking for Metros

Predefined-Time Output Stabilization With Second Order Sliding Mode Generation

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