Sliding mode control of double input buck buck–boost fused converter

Abstract

This paper develops a hysteresis band‐based multivariable sliding mode control (SMC) for the double input buck buck–boost fused converter. The considered converter is operated at a controlled output voltage, while supplied from two different levels of input voltages from two different sources. The proposed control is to ensure the faster time of responses during the variation in the dual references, the output voltage, and low‐voltage source current, simultaneously. The controller is developed by considering these two controlled variables, which are directly dependent on each other. This multivariable SMC is shown to perform successfully to maintain the controlled variables at their desired values despite the variation in the input voltage sources and also during perturbation in the load impedance. The stability analysis for the closed‐loop system is established with the Lyapunov method, which confirms that both of the controlled variables reach the desired stable band at the steady state. The control is implemented in the simulation environment for different operating conditions. A laboratory prototype is developed to implement the multivariable SMC. The experimental results successfully validate their simulated counterparts.

A generalized reaching‐law‐based discrete‐time integral sliding‐mode controller with matched/mismatched disturbance attenuation

“…To demonstrate the performance of the proposed generalized RL-based controller ( 14) on SISO systems with mismatched disturbance, a MAGLEV system [29] is used, whose dynamical equation is identified as 9) is calculated by placing the poles at P = [0.84, 0.85, 0.86], F is calculated by using (37). Other parameters in the proposed generalized RL-based controller are set as follows: FIGURE 6 Simulation results for a SISO system with mismatched disturbances and system uncertainties q 0 = 0.6, 𝜂 0 = 0.06, 𝜑 = 2, and 𝛼 = 1. The pure EC-based controller (11) in this paper and the available controllers in Abidi et al [20], Du et al [29], and Ma et al [34], whose parameters are shown in Table 1, are employed for comparison.…”

“…Sliding-mode control (SMC) has been widely studied in academic and industrial communities [1][2][3][4][5][6][7], due to its simplicity and robustness to the matched uncertainties of uncertain dynamic systems [8]. The procedure of SMC design mainly involves constructing a sliding surface and organizing the sliding-mode controller (SMCer).…”

A novel fixed‐time sliding mode control for nonlinear manipulator systems based on adaptive disturbance observer

“…However, since the robotic manipulator is a system with nonlinear and complex perturbations, the actual control is susceptible to modeling errors, friction, and external disturbances, which all increase the difficulty of control. In response to the problems of nonlinear systems, scholars have developed different control methods to improve them, such as neural network control [3,4], fuzzy control methods [5][6][7][8][9], backstepping control methods [10][11][12], and sliding mode control (SMC) methods [13][14][15][16][17][18].…”

Model‐free prescribed performance fast nonsingular terminal sliding mode control with practical finite‐time stability of uncertain robot manipulators

“…Generally, motion control of robot manipulators is still a difficult task because of modeling uncertainties, nonlinearities and external disturbances in system. In order to meet the requirements of high performance tracking control, lots of advanced control methods have been proposed and applied to robot manipulators, such as adaptive control [4,5], sliding mode control [6][7][8][9], time delay control [10] and model predictive control [11], etc.…”