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The paper presents issues related to the application of filtered integral sliding mode control to a two-mass drive system. A classical control structure has been presented and its design procedure is shown in detail. The properties of the classical structure, in which the chattering phenomenon seems to be a big drawback, have been summarized. In order to eliminate this phenomenon, an output low- -pass filter has been proposed and the performance of this system has been tested. In order to improve its characteristics, an adaptive low-pass filter has been proposed. The bandwidth of the filter was changed on-line by the fuzzy system according to the current state of the plant. During the steady-states, the bandwidth is low to eliminate chattering effect, and during transients higher in order to ensure the fast dynamics of the plant.

This paper proposes an improved double power reaching law integral SMC algorithm to overcome the chattering, large overshoot, slow response. This improved algorithm has two advantages. Firstly, the designed control law can reach the approaching equilibrium point quickly when it is away from or close to the sliding surface. The chattering and response speed problems can be resolved. Secondly, the proposed algorithm has a good anti-jamming performance, and can maintain a good dynamic quality under the condition of the uncertain external disturbance. Finally, the proposed algorithm is applied to the open-loop unstable magnetic suspension system. Theoretical analysis and Matlab simulation results show that the improved algorithm has better control performances than the traditional SMC and the power reaching law integral SMC algorithm, such as less chattering, smaller overshoots, and faster response speed.

An adaptive integral sliding mode control (AISMC) method with payload sway reduction is presented for 4-DOF tower cranes in this paper. The designed controller consists of three parts: The integral sliding mode control is used to provide the robust behavior; the adaptive control is utilized to present the adaptive performance; the swing-damping term is added to suppress and eliminate the payload swing angles. Different from existing sliding mode control methods presenting with chattering phenomenon, the proposed AISMC method is essentially continuous and chattering free. Moreover, the accurate values of the system parameters including the payload mass, the trolley mass, the cable length, the moment of inertia of the jib, the friction-related coefficients are not required for the designed controller due to the adaptive control. Lyapunov-based analysis and LaSalle’s invariance principle are employed to support the theoretical derivations without linearizing the nonlinear dynamics. Experimental results are illustrated to show the superior control performance of the designed controller.

In this paper, a robust tracking control problem for underactuated underwater vehicles in horizontal motion is investigated. The presented control scheme that performs the trajectory tracking task is a combination of the backstepping technique and the integral sliding mode control method using the inertial quasi velocities (IQVs) resulting from the inertia matrix decomposition. Unlike many known solutions, the proposed approach allows not only trajectory tracking, but also, due to the fact that IQV includes dynamic and geometric model parameters, allows us to obtain additional information about changes in vehicle behavior during movement. In this way, some insight into its dynamics is obtained. Moreover, the control strategy takes into account model inaccuracies and external disturbances, which makes it more useful from a technical point of view. Another advantage of this work is to indicate problems occurring during the implementation of trajectory tracking in algorithms with a dynamics model containing a diagonal inertia matrix, i.e., without inertial couplings. The theoretical results are illustrated by simulation tests conducted on two models of underwater vehicles with three degrees of freedom (DOF).

This paper investigates the problem of attitude tracking control with predefined-time convergence for rigid spacecraft under external disturbances and inertia uncertainties. Firstly, the proposed nominal controller is designed to achieve attitude tracking control of the rigid spacecraft in the absence of disturbances and inertia uncertainties, and the convergence of the spacecraft attitude errors can be selected in advance. Then, the integral sliding mode combined with barrier function-based adaptive laws is proposed to reject the disturbances and inertia uncertainties, and at the same time, a barrier function-based adaptive method can also ensure the solutions of the rigid spacecraft system belonging to a stipulated vicinity of the intended variables starting from the initial moment and the uncertainties’ upper bound is not overestimated. Finally, a numerical simulation is provided to illustrate the efficiency of the proposed control protocol.

The sliding-mode control (SMC) has been used successfully to stabilize nonlinear systems, yet a side effect of SMC is chattering, an undesired phenomenon. Researchers have then introduced the so-called integral-type approach to diminish chattering. Additional studies have shown that SMC with the so-called barrier function can drive the system state to a region close to the origin. The main contribution of this paper is to join both setups in the context of SMC, i.e., integral term and barrier function. We show that SMC with both integral term and barrier function can be used to track any given trajectory while ensuring both stability and chattering-free performance. The potential of this novel control for applications is illustrated through real-time experiments performed on a magnetic levitation system.

Permanent magnet synchronous motors are highly coupled, multivariable, and nonlinear, and sliding mode control has gradually gained traction in motor control systems due to its robustness. However, conventional sliding mode control suffers from issues such as severe chattering and insufficient convergence speed. To address these limitations, we propose an integral sliding mode control strategy, enhanced by an improved power exponential reaching law (IPERL). This strategy integrates an IPERL based on state error and an integral sliding mode surface, enabling the system to respond rapidly to changes in operating conditions while effectively mitigating oscillatory behavior. The proposed control strategy is validated through simulations, demonstrating its superior performance compared to traditional methods in terms of both stability and convergence speed.

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies.

This paper focuses on controlling and optimizing a hybrid renewable energy system. The complex interactions and intermittent nature of renewable sources pose challenges to grid stability, necessitating sophisticated control strategies. The system includes a photovoltaic generator and a wind energy conversion system with a permanent magnet synchronous generator. Two key innovations are presented: i) connecting the photovoltaic generator to the grid in hybridization with the wind turbine without using a DC/DC converter, simplifying the structure, reducing losses, and ensuring grid stability and reliability; and ii) designing multi-objective controllers using the maximum power point tracking method based solely on electrical parameters, leading to fewer sensors and higher reliability compared to previous methods that required additional measurements like wind speed and irradiance. To address these challenges, a multiloop nonlinear controller is proposed, employing integral sliding mode and backstepping design techniques based on an accurate nonlinear system model. The stability of the multiloop control system is ensured using a suitable Lyapunov function.

This article considers the application of a robust control technique for vehicle steer-by-wire (VSbW) system subjected to variations in parameters based on adaptive integral sliding mode control (AISMC). The AISMC has been designed to control the VSbW system to cope with the uncertainties in system parameters. The proposed adaptive control scheme provides the solution for perturbation boundedness, as there is no need to have a prior knowledge of perturbation bound in the uncertainty. In addition, the proposed adaptive control design can avoid overestimation of sliding gain under unknown prior knowledge of perturbations. Moreover, the inclusion of integral sliding mode control (ISMC) leads to elimination of the reaching phase in trajectory solution of controlled system. Computer simulations have been used to verify the effectiveness of proposed AISMC to show the superiority of the proposed control technique; in this regard, a comparison between AISMC and other control methods from the literature were conducted. The numerical simulation based on MATLAB programming software showed that the designed AISMC has better tracking performance and accuracy as compared to ISMC and other control schemes in terms of robustness characteristics.