Sliding Mode Parameter Research Articles

Vibration control and robustness analysis of tensegrity structures via fuzzy dynamic sliding mode control method

This study addresses the problem of mitigating vibration responses in tensegrity structures subjected to complex dynamic loading conditions. The overall purpose is to develop an effective control method to enhance the stability and performance of these structures. To achieve this, a fuzzy dynamic sliding mode control (FDSMC) method is proposed. The methodology involves deriving the state space expression of the controlled system based on the tensegrity structure's dynamic model, followed by designing a dynamic sliding mode controller using the reaching law. Fuzzy rules are incorporated to adaptively adjust the dynamic sliding mode parameters, accounting for uncertainties in controller parameters, thereby ensuring high efficiency and smooth controller output. A comparative analysis scheme, focusing on identical energy input on actuators, is utilized to evaluate the performance of various active vibration control methods. Two illustrative examples, a spatial double-layer tensegrity beam and a complex tensegrity spiral tower, are investigated in detail. The findings demonstrate that the FDSMC method significantly reduces structural dynamic responses and improves algorithm robustness compared to the conventional linear quadratic regulator (LQR) method, indicating its promising potential for relevant engineering applications.

Robust Nonlinear Control of a Wind Turbine with a Permanent Magnet Synchronous Generator

This paper addresses the design of a robust nonlinear dynamic controller for a wind turbine. The turbine is equipped with a permanent magnet synchronous generator. The control problem involves tracking a suitable reference value for the turbine’s angular velocity, which corresponds to the wind speed. This issue is tackled by compensating for variations in the electrical and mechanical parameters present in the mathematical model. Additionally, the problem is approached under the assumption that wind speed cannot be directly measured, a fact verified in practical scenarios. This situation is particularly relevant for real-world applications, where only nominal parameter values are accessible and accurate wind speed measurement is challenging due to disturbances caused by the turbine or other factors, despite the use of appropriate sensors. To achieve precise tracking of the angular velocity reference, effective compensation of perturbation terms arising from parameter uncertainties and errors in wind estimation becomes crucial. To address this problem, a wind velocity estimator is employed in conjunction with high-order sliding mode parameter estimators, ensuring the turbine’s operation attains a high level of performance.

Variations in Finite-Time Multi-Surface Sliding Mode Control for Multirotor Unmanned Aerial Vehicle Payload Delivery with Pendulum Swinging Effects

Multi-surface sliding mode control addresses the limitations of traditional sliding mode control by employing multiple sliding surfaces to handle uncertainties, disturbances, and nonlinearities. The design process involves developing sliding surfaces, designing switching logic, and deriving control laws for each surface. In this paper, first, a robust finite-time multi-surface sliding mode controller will be presented and its performance analyzed by applying it to a multirotor subjected to a suspended payload, modeled in the form of a single pendulum, itself defined as a spatial (3D) dynamic model. Next, an adaptive finite-time multi-surface sliding mode controller will be derived—adding a variable adaptive parameter to the existing sliding surfaces of the robust finite-time control—and applied to the same system. It will be shown that the adaptive controller, with an adaptive parameter that adjusts itself based on the present value of the multi-surface sliding mode parameter, creates an improved fast finite-time convergence by obtaining an optimal settling time and minimizing undershoot of the multirotor state vector. Empirical verification of the effectiveness of the adaptive control will be carried out by presenting the control performances against a step response. It is also shown that the control may be utilized to approximate external disturbances—represented by the pendulum—and that with the application of control, the vehicle’s motion may be stabilized and the payload swing suppressed. Lyapunov stability theory-based stability proofs for the controllers’ designs are developed, showing the asymptotic stability of the output and uniform boundedness of the errors in the system dynamics. It is verified that the multi-surface sliding mode control can account for system uncertainties—both matched and mismatched—in addition to changes in internal dynamics and disturbances to the system, where the single pendulum payload is representative of the changes in dynamics that may occur to the system. Numerical simulations and characteristics are presented to validate the performance of the controllers.

Research on Path Tracking and Yaw Stability Coordination Control Strategy for Four-Wheel Independent Drive Electric Trucks

Achieving accurate path tracking and vehicle stability control for four-wheel independent drive electric trucks under complex driving conditions, such as high speed and low adhesion, remains a major challenge in current research. Poor coordination control may cause the vehicle to deviate from its intended path and become unstable. To address this issue, this article proposes a coordinated control strategy consisting of a three-layer control framework. In the upper layer controller design, establish a linear quadratic regulator (LQR) path tracking controller to ensure precise steering control by eliminating steady-state errors through feedforward control. The middle layer controller utilizes the fractional order sliding mode control (FOSMC) yaw moment controller to calculate the additional yaw moment based on the steering angle of the upper input, utilizing the error of yaw rate and sideslip angle as the state variable. To collectively optimize the control system, establish a coordinated optimization objective function and utilize the hybrid genetic-particle swarm optimization algorithm (GA-PSO) to optimize the weight coefficient of LQR and sliding mode parameters of FOSMC, effectively improving the performance of the controller. In the lower layer torque distribution controller, use the quadratic programming method to achieve real-time optimal torque distribution based on tire utilization, which improves vehicle stability control. Through simulations conducted under four different working conditions, the proposed control scheme demonstrates a 15.54% to 23.17% improvement in tracking performance and a 10.83% to 23.88% optimization in vehicle driving stability compared to other control methods. This scheme provides a theoretical reference for path tracking and stability control in four-wheel independent drive electric trucks.

Adaptive Terminal Sliding Mode Speed Regulation for PMSM Under Neural-Network-Based Disturbance Estimation: A Dynamic-Event-Triggered Approach

The speed regulation control issue of the networked permanent magnet synchronous motor system is investigated in this paper by utilizing a nonsingular terminal sliding mode control scheme. In order to remove the demand of the prior knowledge for possible lumped disturbance and parameter uncertainties in the permanent magnet synchronous motor system, an adaptive neural network is introduced into the proposed terminal sliding mode control scheme. Moreover, in order to ease the communication overheads of the networked system, a new dynamic event-triggered mechanism with considering the neural network estimation error is employed to schedule the signal transmission between the speed sensor and the remote sliding mode controller. The Zeno phenomena for the developed dynamic event-triggered mechanism is excluded via explicit analysis. It is further shown that by choosing suitable sliding mode parameters, the proposed control strategy can guarantee the convergence of the sliding variable into a practical sliding region as well as the ultimate boundedness of the speed regulation error. Finally, the feasibility and applicability of the proposed speed regulation strategy are demonstrated by simulation results and a real experiment.

An Enhanced Coupling Adaptive Sliding Mode Control Method for Casting Cranes Based on Radial Spring Damping

During the transference of a ladle by the casting crane, the antiswing control of the ladle is particularly difficult due to liquid sloshing, so we designed a model based on a radial spring damper. During the ladle swings, the centrifugal force causes the spring damper to move radially, thereby generating a Coriolis force that inhibits the sloshing of the liquid. In addition, a sloshing analysis of the liquid in the ladle is carried out, and a double-pendulum casting crane model based on viscous damping and radial spring damper is established. On the basis of this model, the Enhanced Coupled Adaptive Sliding Mode Control (ECASMC) method is proposed. By introducing an enhanced coupling variable and constructing a new coupling deviation signal, we enhance the relationship among state quantities. Then, a new type of sliding surface is designed based on the enhanced coupling deviation signal, and adaptive technology is used to adjust the sliding mode parameters, which enhances the system's robustness for system parameter variations and external disturbances. Using LaSalle's invariance principle and Lyapunov theorem, we prove that the casting crane system is asymptotically stable near the desired equilibrium point. The simulation results verify the effectiveness and superior control performance of the proposed method even in the presence of uncertainties.

A vision-aided fuzzy adaptive sliding mode controller for autonomous landing of a nonlinear model helicopter on a moving marine platform

PurposeA vision-assisted fuzzy adaptive sliding mode controller is presented in this research and implemented on a nonlinear helicopter model, which is about to land on a moving ship. Stabilization of the dynamics and tracking the landing path are required, at the same time. This study aims to take one step closer to fully autonomous landing, which is a growing trend.Design/methodology/approachAn integrated guidance and control is considered for the model helicopter. A fuzzy logic is designed to adaptively choose the best control parameters for the sliding mode controller and solve the challenge of parameter tuning. A self-organizing matrix consisting of fuzzy sliding mode parameters is formed instead of a single parameter with the goal of enhancing controller tracking capability. A simple, precise and fast image recognition system based on OpenCV is used to detect the proper point for descending without getting any special data from the ship and by only using a general “H” sign.FindingsThe problem is simulated under intense disturbances, while the approach and landing performances are acceptable. Controller performance is compared and validated. Simulation results show the robustness, agility, stability and outperformance of the proposed controller.Originality/valueThe novelty of this paper is the designed procedure for using a simple image recognition system in the process of autonomous ship-landing, which does not use any special data sent from the ship. Besides, an improved nonlinear controller is designed for integrated guidance and control in this specific application.

Torque ripple attenuation of PMSM using improved robust two-degree-of-freedom controller via extended sliding mode parameter observer

Torque ripple caused by flux harmonics, nonlinearity of inverter and current measurements decreases the accuracy of the servo control system, which limits the application of permanent magnet synchronous motor (PMSM) with high precision requirement. To reduce torque ripple, this paper proposes an improved robust two-degree-of-freedom controller (IR-2DOFC) based on an extended sliding-mode parameter observer (ESMPO) for a PMSM. The IR-2DOFC is constructed around the 2DOFC with iterative learning control (ILC) and a series-connecting structure, which not only suppresses unmodeled disturbances and periodic components, but also attenuates the negative impact of ILC on the dynamic response. Meanwhile, to improve the robust stability of the IR-2DOFC, ESMPO identifies the mechanical parameters so that they can be employed to further establish the IR-2DOFC parameters. Additionally, the observed disturbances can be regarded as a feed-forward compensation component to the IR-2DOFC, which enhances the disturbance-rejection performance. Simulations and experiments show that the IR-2DOFC with ESMPO has an improved dynamic response performance, which exhibits better robustness with respect to internal and external load disturbances and harmonics torque compared with proportional–integral (PI) and PI-ILC controllers.

Robust iterative learning control design based on iterative integral sliding mode for nonlinear systems with unrepeatable disturbance

For the repetitive tracking control tasks, the unrepeatable disturbance is an obstruction to learning control schemes. This paper discussed the robust iterative learning control (RILC) design based on the sliding mode control (SMC) technique for a class of nonlinear systems with unrepeatable disturbances. In order to make the tracking error converge to zero in the iteration domain under the sliding mode and eliminate the reaching phase of the SMC, an iterative integral sliding mode (IISM) surface design was proposed. The IISM leads to linear tracking error dynamics in the iteration domain, which guarantees the convergence if the sliding mode parameters meet the given condition. After that, the iterative learning control (ILC) based on the IISM was designed, which drove the sliding mode variable of the closed-loop system to reach the origin with iterations from the initial time instant, despite the effect of the unrepeatable disturbances. The robustness to the unrepeatable disturbance and the fast convergence were achieved. Finally, the proposed IISM method was applied to a one-link robotic manipulator, and the simulation results validated the performance of the proposed control design.

Robust Finite-Time Control Algorithm Based on Dynamic Sliding Mode for Satellite Attitude Maneuver

Robust finite-time control algorithms for satellite attitude maneuvers are proposed in this paper. The standard sliding mode is modified, hence the inherent robustness could be maintained, and this fixed sliding mode is modified to dynamic, therefore the finite-time stability could be achieved. First, the finite -time sliding mode based on attitude quaternion is proposed and the loose finite-time stability is achieved by enlarging the sliding mode parameter. In order to get the strict finite-time stability, a sliding mode based on the Euler axis is then given. The fixed norm property of the Euler axis is used, and a sliding mode parameter without singularity issue is achieved. System performance near the equilibrium point is largely improved by the proposed sliding modes. The singularity issue of finite-time control is solved by the property of rotation around a fixed axis. System finite-time stability and robustness are analyzed by the Lyapunov method. The superiority of proposed controllers and system robustness to some typical perturbations such as disturbance torque, model uncertainty and actuator error are demonstrated by simulation results.

Finite-Time Controller for Flexible Satellite Attitude Fast and Large-Angle Maneuver

In order to deal with the fast, large-angle attitude maneuver with flexible appendages, a finite-time attitude controller is proposed in this paper. The finite-time sliding mode is constructed by implementing the dynamic sliding mode method; the sliding mode parameter is constructed to be time-varying; hence, the system could have a better convergence rate. The updated law of the sliding mode parameter is designed, and the performance of the standard sliding mode is largely improved; meanwhile, the inherent robustness could be maintained. In order to ensure the system’s state could converge along the proposed sliding mode, a finite-time controller is designed, and an auxiliary term is designed to deal with the torque caused by flexible vibration; hence, the vibration caused by flexible appendages could be suppressed. System stability is analyzed by the Lyapunov method, and the superiority of the proposed controller is demonstrated by numerical simulation.

An adaptive fuzzy sliding‐mode control for regenerative braking system of electric vehicles

SummaryThis article proposes a novel fuzzy sliding‐mode control scheme under an adaptive control strategy for energy management mechanism in electric vehicles that are subject to a regenerative braking system. The effectiveness of the fuzzy logic controller is to adjust the sliding mode parameters according to the slip ratio tracking error between the optimal slip ratio and the actual slip ratio. Specifically, the proposed torque distribution strategy can integrate the best battery condition and energy recovery efficiency under the practical constraints through this control method by fixing the pneumatic braking torque and motor torque. Finally, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.

Adaptive-triggered asynchronous control for stochastic jumping systems under sliding mode

This paper investigates the problem of event-triggered asynchronous control for discrete-time stochastic jumping systems. A novel adaptive event-triggered (AET) strategy is proposed to save network resources, and two asynchronous control approaches are presented. First, an asynchronous feedback control method on adaptive triggered mechanism is proposed, and the mean-square exponentially stable of the closed-loop system is analysed. Second, the reduced-order model for discrete-time stochastic system is established to deal with the actuator faults. Furthermore, combining with the AET scheme, an asynchronous sliding-mode surface is designed such that the discrete-time reduced-order sliding-mode dynamics is yielded. Third, the stability analysis for the sliding-mode dynamics is discussed and the sliding-mode parameters are solved. Moreover, in order to compensate the actuator faults, an asynchronous sliding-mode controller is synthesised, and the reachability of the sliding-mode surface is analysed. Finally, two examples are given to demonstrate the potential of the developed scheme.

Stabilizing terminal constraint-free nonlinear MPC via sliding mode-based terminal cost

It is well-known that terminal state constraints play an instrumental role in ensuring the feasibility and stability of the nonlinear model predictive control (MPC). Yet, they inherently and largely limit the size of the feasible region and restrict the use of MPC to practical applications. In this paper, a terminal cost characterized by an implicit sliding mode control (SMC) law is proposed for developing a stabilizing constrained MPC scheme. This SMC law developed for the linearized model helps compensate the model mismatch between the linearization and the original nonlinear system model. Thanks to it, the proposed MPC strategy can stabilize the constrained nonlinear system of which the corresponding linearization around the equilibrium is non-stabilizable. Moreover, by appropriately tuning the sliding mode parameters, the conventional terminal constraints and large prediction horizon typically used in the literature are no longer required. We establish the conditions of ensuring the recursive feasibility and asymptotic stability of the closed-loop system. Finally, numerical comparison results on two examples of dynamic systems are reported to demonstrate the effectiveness of the developed strategy.

Reduced-order-asynchronous-based control for nonlinear jump networked systems with attacks

With the widespread application of communication networks in industrial control systems, cyber-attacks bring a huge threat to the networked control system. In this paper, the issue of secure control of nonlinear jump networked systems with false data inject (FDI) attacks is investigated. In order to against the malicious attacks, a reduced-order-asynchronous sliding-mode control (SMC) strategy is proposed. Firstly, in order to damp the effect of nonlinear term and FDI attacks, an asynchronous sliding-mode function is designed, and the resultant sliding-mode dynamics is generated by using the reduced-order method. Then, the stability conditions for the reduced-order sliding-mode dynamics are given, and the sliding-mode parameters are solved by linear matrix inequality technology. Furthermore, the sliding-mode controllers are designed under the situation of the parameters is known or unknown, respectively, and the reachability of the sliding-mode motion is certificated. Finally, two examples are implemented to illustrate the potential of the presented control strategy.

Dynamic Sliding Mode Controller with Variable Structure for Fast Satellite Attitude Maneuver

In order to deal with the low convergence rate of the standard sliding mode in satellite attitude control, a novel variable structure sliding mode is constructed in this paper by designing the update law of the sliding mode parameter. By implementing this method, the advantage such as simple structure and strong robustness of the standard sliding mode are maintained and the system convergence rate is largely improved. The fixed sliding mode parameter is modified, and the update law is designed. When the system state is away from the sliding mode surface, the parameter is fixed, and when the system state approaches the sliding mode surface, the parameter begins to update. The constraint on control torque and angular velocity is taken into consideration, and the constraint on control parameters is given to ensure that the system state do not exceed its upper bound. System stability is proved by the Lyapunov stability theorem, and the superiority of the proposed controller is demonstrated by numerical simulation.

Adaptive Tracking Control of an Electronic Throttle Valve Based on Recursive Terminal Sliding Mode

This paper proposes an adaptive tracking control scheme for an electronic throttle valve (ETV) based on recursive terminal sliding mode (RTSM) control strategy in the presence of parametric uncertainties and lumped disturbance. The developed RTSM dynamical structure for the controller is composed of a fast nonsingular terminal sliding surface and a recursive integral terminal sliding function, such that not only is the reaching phase eliminated, but also a sequential finite-time zero-convergence of both the recursive sliding surfaces and position tracking error are guaranteed. Due to the difficulty in ensuring a satisfactory tracking performance with respective to a broad range of operation conditions in practice, an adaptive mechanism is further developed to estimate both the lumped uncertainty bound and the sliding mode parameters, such that no prior knowledge of the system is required in the controller leading to the effective improvement of the flexibility and simplicity of sliding mode-based ETV control systems. Comparative experiments are conducted to verify that the proposed control enjoys a fast finite-time convergence and superior robustness with respect to uncertainties and disturbances.

Current Sensor Fault-Tolerant Control Strategy for Encoderless PMSM Drives Based on Single Sliding Mode Observer

In encoderless field-oriented-controlled permanent magnet synchronous motor (PMSM) drives, current sensors may malfunction in harsh working environments. A current sensor fault-tolerant control (FTC) strategy with a single sliding mode observer (SMO) is proposed in this article, which can achieve both phase current error construction and rotor position estimation. This strategy can simplify the system structure and reduce the FTC algorithm complexity. By utilizing the current error construction module, the estimated current error can be obtained from the healthy current sensor. The parameter design of the construction module is investigated to improve the performance. The stability and the convergence rate of the observer can be ensured by selecting appropriate sliding mode parameters. As the proposed current error construction module is independent of motor parameters and the SMO is also less affected by the motor parameter variation, the proposed FTC strategy owns satisfactory robustness. Finally, the effectiveness of the proposed scheme is verified by experiments on a 2.2-kW PMSM drive platform.

Quadrotor UAV Control for Transportation of Cable Suspended Payload

Abstract Payload transportation with UAV’s (Unmanned Aerial Vehicles) has become a topic of interest in research with possibilities for a wide range of applications such as transporting emergency equipment to otherwise inaccessible areas. In general, the problem of transporting cable suspended loads lies in the under actuation, which causes oscillations during horizontal transport of the payload. Excessive oscillations increase both the time required to accurately position the payload and may be detrimental to the objects in the workspace or the payload itself. In this article, we present a method to control a quadrotor with a cable suspended payload. While the quadrotor itself is a nonlinear system, the problem of payload transportation with a quadrotor adds additional complexities due to both input coupling and additional under actuation of the system. For simplicity, we fix the quadrotor to a planar motion, giving it a total of 4 degrees of freedom. The quadrotor with the cable suspended payload is modelled using the Euler-Lagrange equations of motion and then partitioned into translation and attitude dynamics. The design methodology is based on simplifying the system by using a variable transformation to decouple the inputs, after which sliding mode control is used for the translational and pendulum dynamics while a feedback linearizing controller is used for the rotational dynamics of the quadrotor. The sliding mode parameters are chosen so stability is guaranteed within a certain region of attraction. Lastly, the results of the numerical simulations created in MATLAB/Simulink are presented to verify the effectiveness of the proposed control strategy.

Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

This paper reports on the optimal speed control problem in permanent magnet synchronous motor (PMSM) systems. To improve the speed control performance of a PMSM system, a model predictive control (MPC) method is incorporated into the control design of the speed loop. The control performance of the conventional MPC for PMSM systems is destroyed because of system disturbances such as parameter mismatches and external disturbances. To implement the MPC method in practical applications and to improve its robustness, a compensated scheme with an extended sliding mode observer (ESMO) is proposed in this paper. Firstly, for observing if and when the system model is mismatched, the ESMO is regarded as an extended sliding mode parameter observer (ESMPO) to identify the main mechanical parameters. The accurately obtained mechanical parameters are then updated into the MPC model. In addition, to overcome the influence of external load disturbances on the system, the observer is regarded as an extended sliding mode disturbance observer (ESMDO) to observe the unknown disturbances and provide a feed-forward compensation item based on the estimated disturbances to the model predictive speed controller. The simulation and experimental results show that the proposed ESMO can accurately observe the mechanical parameters of the system. Moreover, the optimized MPC improves the dynamic response behavior and exhibits a satisfactory disturbance rejection performance.