Sliding Mode Control for a Nonlinear Aeroelastic System through Backstepping

In this paper, a chatter free sliding mode control (SMC) strategy for chaos control is introduced to the nonlinear uncertain chaotic systems in the presence of unknown bounded uncertainties and external disturbances. The sliding mode surface with differential operators is proposed to divert the discontinuous gian function swith term into only one control input, and the control input is smooth and differentiable with respect to time. Based on the Lyapunov stability theory, SMC stability analysis is performed and a theorem serving as designing a chatter free sliding mode control input is also introduced. Finally, numerical simulations are presented to verify the usefulness of the proposed control strategy.

Chattering-free higher order sliding mode controller with a high-gain observer for the load following of a pressurized water reactor

[Abstract] This paper presents the design of a higher-order sliding mode controller for finite-time stabilization of a multi-input multi-output nonlinear aeroelastic system with uncertain dynamics using leadingand trailing-edge control surfaces. The model describes the plunge and pitch dynamics of a prototypical wing section. It is assumed that the system parameters are not known precisely and external disturbance inputs are present in the model. The uncontrolled model exhibits limit cycle oscillations. The objective is to control the state vector of the system to the origin. A robust control law is designed for the finite-time trajectory control of the plunge and pitch angle trajectory. The control law includes a nominal finite-time stabilizing control signal designed for the system without uncertainties, and a discontinuous control signal for nullifying the effect of uncertain functions in the model. For the nominal control law design, the notion of geometric homogeneity is utilized and the discontinuous part of the controller is derived based on a second-order sliding mode control scheme. In the closed-loop system including the nominal and discontinuous control signals, finite-time control of the complete state vector associated with the plunge-pitch motion of the system to the origin is accomplished. Simulation results are presented which show the suppression of the limit cycle oscillations, despite parameter uncertainties and triangular, exponential, sinusoidal and random gust loads.

Three-phase voltage PWM rectifier is a multivariable, strong coupling, nonlinear multi-input and multi-output system. In the design of rectifier control systems, with PI control it is difficult to achieve the ideal control effect, the dynamic performance is poor, and the parameter computation is complex. Moreover, the traditional sliding mode control voltage outer loop suffers from the problem of chattering, which is difficult to solve. Responding to the above issues, a new type of variable speed reaching law is proposed, which is applied to the voltage outer loop sliding mode control, while the feedback linearization principle is introduced to the current inner loop, and a new type of double closed-loop sliding mode control system is obtained by applying the two theories to the design of the sliding mode controller. A simulation model is established in MATLAB/Simulink to compare the PI control, the SMC control and the V-SMC control strategy proposed in this paper (voltage outer loop V-SMC current inner loop FLC-SMC control), and the simulation results show that the rectifier under the new dual-closed-loop sliding mode control strategy has the advantages of good dynamic performance, strong robustness and strong anti-interference ability. At the same time, compared with the traditional sliding mode control strategy, the vibration suppression effect under the proposed control strategy is obvious. Finally, a 10 kW rectifier control system is built on a semi-physical hardware-in-the-loop experimental platform to further verify the correctness and superiority of the proposed control strategy.

In this paper, because a adaptive fuzzy control is incorporated into the sliding mode control (SMC) to adaptively regulate the adaptive law of SMC, an adaptive fuzzy sliding mode controller (AFSMC) for brushless doubly fed machine (BDFM) adjustable speed system is presented. The proposed controller for BDFM eliminates the average chattering encountered by most SMC schemes, and employs the robustness and excellent static and dynamic performances of SMC. Simulation results show that the proposed control strategy is of the feasibility, correctness and effectiveness.

In this chapter an adaptive sliding mode controller for the Furuta pendulum is proposed. The Furuta pendulum is a class of underactuated mechanical systems commonly used in many control systems laboratories due to its complex stabilization which allows the analysis and design of different nonlinear and multivariable controllers that are useful in some fields such as aerospace and robotics. Sliding mode control has been extensively used in the control of mechanical systems as an alternative to other nonlinear control strategies such as backstepping, passivity based control etc. The design and implementation of an adaptive sliding mode controller for this kind of system is explained in this chapter, along with other sliding mode controller variations such as second order sliding mode (SOSMC) and PD plus sliding mode control (PD \(+\) SMC) in order to compare their performance under different system conditions. These control techniques are developed using the Lyapunov stability theorem and the variable structure design procedure to obtain asymptotically stable system trajectories. In this chapter the adaptive sliding mode consist of a sliding mode control law with an adaptive gain that makes the controller more flexible and reliable than other sliding mode control (SMC) algorithms and nonlinear control strategies. The adaptive sliding mode control (ASMC) of the Furuta pendulum, and the other SMC strategies shown in this chapter, are derived according to the Furuta’s pendulum dynamic equations making the sliding variables, position errors and velocity errors reach the zero value in a specified reaching time. The main reason of deriving two well known sliding mode control strategy apart from the proposed control strategy of this chapter (adaptive sliding mode control) is for comparison purposes and to evince the advantages and disadvantages of adaptive sliding mode control over other sliding mode control strategies for the stabilization of the Furuta pendulum. A chattering analysis of the three SMC variations is done, to examine the response of the system, and to test the performance of the ASMC in comparison with the other control strategies explained in this chapter.

A nonlinear output feedback control method is presented, which achieves asymptotic limit cycle oscillation (LCO) regulation in an aircraft wing section using synthetic jet actuators. To eliminate the standard requirement that LCO pitching and plunging rates are available for feedback, a finite-time sliding mode observer is utilized to estimate the rates using only measurements of LCO displacements. To achieve the result, a detailed mathematical model of the LCO dynamics is utilized, which includes nonlinear stiffness effects, unmodeled external disturbances, and dynamic model uncertainty, in addition to the parametric actuator uncertainty. A rigorous analysis is used to prove finite-time convergence of the estimation error, and a Lyapunov-based stability analysis is used to prove asymptotic regulation control of the LCO. Numerical simulation results are also provided which show the performance of the proposed sliding mode observer-based control design in comparison with our recently developed bank of filters-based output feedback LCO control method.

Robust internal model control of servo motor based on sliding mode control approach

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

To improve the performance of the magnetorheological (MR) semi-active suspension system, a fractional-order sliding mode control (FOSMC) strategy is proposed to address the nonlinear problems caused by the external disturbances and changes in parameters of system. Firstly, The MR damper designed by the research team is applied to the vehicle’s MR semi-active suspension, and a one-fourth semi-active suspension dynamic model is established. Mechanical performance tests of the MR damper are conducted through tensile experiments, confirming its satisfactory mechanical characteristics and suitability for meeting the output damping force requirements of the vehicle’s semi-active suspension. To accurately convert the computed control force into the MR damper’s control current, an adaptive neuro-fuzzy inference system (ANFIS) inverse model of the MR damper is constructed. Comparative data analysis demonstrates the inverse model’s high accuracy and its ability to effectively meet the controller’s requirements. The proposed FOSMC strategy effectively reduces the chattering phenomenon associated with sliding mode control, leading to improved vibration-damping performance of the suspension. Subsequently, a simulation model and experimental platform are utilized to evaluate the performance of the proposed controller. Experimental results indicate that the FOSMC-controlled suspension outperforms the passive suspension, achieving significant reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 27.4%, 7.3%, and 17.39%, respectively. Similarly, the semi-active suspension controlled by sliding mode control (SMC) also shows improvements compared to the passive suspension, with reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 20.9%, 4.3%, and 5.2%, respectively. In summary, the FOSMC-controlled MR semi-active suspension exhibits superior damping performance compared to both the passive suspension and the SMC-controlled semi-active suspension, demonstrating the effectiveness of the proposed FOSMC controller.

Terminal sliding mode control for coordinated motion of a space rigid manipulator with external disturbance

ABSTRACTIn this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.

In this paper, we present a simulation study of a wind system with a doubly fed induction machine driven by a variable pitch wind turbine. The objective of the work is to design a control algorithm based on the sliding mode control strategy allowing the control of both active and reactive power independently. The main goal achieved by the control strategy is to control the amount of active and reactive power produced by the doubly fed induction generator and injected in the main grid according to the power references derived from turbine's mechanical power and the grid operator. The simulation results have shown good performances concerning the tracking of the references both in transient and steady state. A comparative study between the proposed control strategy and the well known vector control strategy has been carried out and has shown the superiority of sliding mode control to track the given references.

A self-organizing fuzzy controller to augment a sliding-mode control (SOFSMC) scheme for a class of nonlinear systems is proposed. The motivation behind this scheme is to combine the best features of self-organizing fuzzy control and sliding-mode control to achieve rapid and accurate tracking control of a class of nonlinear systems. The chatter encountered by most sliding-mode control schemes is greatly alleviated without sacrificing invariant properties. A stability analysis is presented; the design guidelines and the class of applicable systems are clearly identified. To verify the scheme, the authors performed experiments on its implementation in a magnetic levitation system. The results show that both alleviation of chatter and robust performance are achieved; the advantages of the scheme are indicated in comparison with the conventional sliding-mode design. >

Echo-state network based adaptive fuzzy sliding-mode consensus control scheme for nonlinear multi-agent systems with external disturbances.