A predictive sliding mode control for quadrotor’s trackingtrajectory subject to wind gusts and uncertainties

<p>The robust reaching law based sliding mode control is used for chattering suppression, minimization of steady state error and reaching speed kept minimized. With fine tuning of parameters of robust reaching law, the sliding mode reaches the equilibrium point at the earliest. The stability of the proposed reaching law is analyzed. In one hand, they guarantee the system reach the sliding face rapidly and stay on it, in another way they decline the chattering effectively, even unmatched certainties and disturbances. Such that the system response can better realize the unification of rapidity. <br />A proposed reaching law ia analyzed mathematically and applied to SMC DC-DC buck converter to lessen the chattering, because switching devices are existing in the model, it reduces effectively in the switching losses in the switching devices of the dc-dc converter. In turn effectiveness of the efficiency increases. MATLAB/Simulink results give significant decline of chattering and switching losses in the buck converter.</p>

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“…A new RL, called robust reaching law, is described in this section. The proposed RRL is described in vector format as (1).…”

Section: Method: Mathematical Analysis Of Robust Reaching Law (Rrl)mentioning

confidence: 99%

“…Sliding mode control (SMC) is a nonlinear control system design technique that is robust to parameter variations and matched uncertainties [1]- [8]. It evolved from variable structure control (VSC) and is established in the field of nonlinear control [1], [2], [9]- [13]. In [14]- [16] provide more information on sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode control technique of step down converter using reaching law

Ningappa

Basavarajan²,

Katappa³

et al. 2023

IJAPE

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“…In the sequel, the optimal partial objective function of ( 6) from stage 𝑁 − 𝑟 to stage 𝑁, where 𝑟 = 1, 2, ⋯ , 𝑁, is given by (7),…”

Section: Ananalytical Solutionmentioning

confidence: 99%

“…Receding horizon control (RHC) has become the standard control technique for constrained dynamical systems [1]- [7]. RHC involves an open-loop finite horizon optimal control problem at each sampling instant where an objective function has to be optimized at each sample time.…”

Section: Introductionmentioning

confidence: 99%

Infinite horizon fuzzy optimal control: optimality does not imply asymptotic stability

Teniou

Belarbi²

2023

IJECE

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In this paper, novel stability result for discrete-time infinite horizon optimal control using fuzzy objective functions is presented. For this class of control, the fuzzy goals and the fuzzy constraints introduced in the fuzzy objective function handle the constraints placed on both the state and the control vectors. We analyze the asymptotic stability of the equilibrium for the infinite horizon fuzzy optimal control law using the minimum aggregation operator. We show that the infinite horizon control with the minimum aggregation operator does not guarantee the asymptotic stability of the equilibrium in general. This is done by deriving an analytical solution of the control law for a simple linear system using a fuzzy dynamic programming approach. An example that shows the novel asymptotic stability result of the equilibrium for discrete-time infinite horizon optimal control with fuzzy objective function problem is given.

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“…Du et al [18] investigated SMC for nonlinear discrete networked cascade control systems. Meradi et al [19] introduced a MPSMC strategy for a quadrotor unmanned aerial vehicle system. The simulation results demonstrate the robustness of the SMC controller against disturbances and the lower control effort of MPC.…”

Section: -Introductionmentioning

confidence: 99%

Model Predictive Sliding Mode Control of Direct Current Motors

Eghbal,

Seyedeh-Solmaz

2024

Preprint

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In this paper, a cascade controller is designed for controlling the speed of a direct current motor, which includes a combination of a model predictive controller and a sliding mode controller. The main goal is to precisely control the speed and angle of the motor shaft by adjusting the input voltage, taking into account the voltage limitations. We design a model predictive sliding mode controller in such a way that in the inner loop, the model predictive controller controls the voltage to follow the reference current, and in the outer loop, the sliding mode controller generates the reference current to follow the desired speed. The sliding mode controller, with its resistance to external disturbances, reduces their effects and the uncertainties of modeling. By extracting the reference current based on the speed tracking error and the presence of uncertainty, the optimal terminal voltage of the motor is predicted in the inner loop, leading to the tracking of the desired rotational speed by the motor. This paper also proves the stability of the system in the presence of the motor terminal input voltage constraint, and the simulation results confirm the effectiveness of the proposed controller in dealing with uncertainty and external disturbances.

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A predictive sliding mode control for quadrotor’s trackingtrajectory subject to wind gusts and uncertainties

Cited by 5 publications

References 24 publications

Sliding mode control technique of step down converter using reaching law

Sliding mode control technique of step down converter using reaching law

Infinite horizon fuzzy optimal control: optimality does not imply asymptotic stability

Model Predictive Sliding Mode Control of Direct Current Motors

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