Sliding Mode Control for Networked Interval Type-2 Fuzzy Systems via Random Multiaccess Protocols

In this paper, a magnetorheological (MR) mount with fuzzy sliding mode controller (FSMC) is studied for vibration suppression when the system is subject to base excitations. In recent years, magnetorheological fluids are becoming a popular material in the field of the semi-active control. However, the dynamic equation of an MR mount is highly nonlinear and it is difficult to identify. FSMC provides a simple method to achieve vibration attenuation of the nonlinear system with uncertain disturbances. This method is capable of handling the chattering problem of sliding mode control effectively and the fuzzy control rules are obtained by using the Lyapunov stability theory. The numerical simulations using one-dimension and two-dimension FSMC show effectiveness of the proposed controller for vibration suppression. Further, the well-known skyhook control scheme and an adaptive sliding mode controller are also included in the simulation for comparison with the proposed FSMC..

This work investigates the security sliding mode control problem of uncertain discrete‐time systems under an unreliable network, in which denial of service and deception attacks may randomly occur in each sensor‐to‐controller channel. Two 2‐valued variables are introduced to model the available state signals for the controller side under random attacks. Meanwhile, by means of mapping rule, independent Markov chains are reformulated into a new Markov chain. And then, a hybrid‐attack‐probability dependent sliding function is constructed, and a desirable sliding mode controller is designed by adopting compensation strategy and available state signals. Moreover, sufficient conditions are derived, under which the closed‐loop system achieve stochastic stability along a quasi sliding mode. Moreover, a cone complementarity linearization (CCL)‐based iterative solving algorithm is proposed. Finally, simulation results are provided to verify the proposed security control approach.

To eliminate the effect of the uncertain disturbances and improve the control accuracy of spacecraft Attitude Control System, a nonlinear control algorithm named nonsingular terminal sliding-mode feedback controller is proposed in this work, which is mainly made up of nonsingular terminal sliding-mode controller and sliding-mode feedback controller. In the first place, nonsingular terminal sliding-mode controller is designed, which guarantees global asymptotic convergence of the attitude in the presence of the uncertain perturbations from the space. Despite that, it is the influence of the uncertain disturbances that hinder the control accuracy. Then, in order to promote the control accuracy, the sliding-mode feedback controller based on the principle of minimum sliding-mode error is proposed, which is used to compensate the control errors of the nonsingular terminal sliding-mode controller caused by the uncertainties. Hence, the determination principle of the weighting matrix in sliding-mode feedback controller is discussed, and the algorithm structure of the sliding-mode feedback controller is also analyzed, which provides the theoretical basis for the sliding-mode feedback controller. By contrast, an adaptive fuzzy algorithm is designed and introduced into the nonsingular terminal sliding-mode controller to improve the control accuracy, which named the nonsingular terminal fuzzy sliding-mode controller. Last but not the least, several numerical examples are presented to demonstrate the efficacy of the proposed nonsingular terminal sliding-mode feedback controller. Simulation results confirm that the control accuracy of the nonsingular terminal sliding-mode feedback controller is higher than the nonsingular terminal sliding-mode controller and the same as nonsingular terminal fuzzy sliding-mode controller. Not only is the calculation of the nonsingular terminal fuzzy sliding-mode feedback controller smaller than nonsingular terminal fuzzy sliding-mode controller, the adjusted parameters are also fewer than nonsingular terminal fuzzy sliding-mode controller obviously. The numerical results clearly indicate that the proposed nonsingular terminal sliding-mode feedback controller based on the principle of minimum sliding-mode error can compensate control errors accurately and quickly; therefore, it can reduce the effect of the uncertainties from the space indirectly.

The implementation of the sliding mode control (SMC) for load frequency control of power networks becomes difficult due to the chattering phenomenon of high-frequency switching. This chattering problem in SMC is extremely dangerous for actuators used in power systems. In this paper, a continuous control strategy by combining a second-order mode and integral siding surface is proposed as a possible solution to this problem. The proposed second-order integral sliding mode control (SOISMC) law not only rejects chattering phenomenon in control input, but also guarantees the robustness of the multi-area power network, which has an effect on parametric uncertainties such as the load variations and the matched or mismatched parameter uncertainties. Moreover, the reporting of the simulation indicates that the proposed controller upholds the quality requirement by controlling with operating conditions in the larger range, rejects disturbance, reduces the transient response of frequency, eliminates the overshoot problem, and can better address load uncertainties compared to several previous control methods. The simulation results also show that the proposed SOISMC can be used for practical multi-area power network to lessen high parameter uncertainties and load disturbances.

Robotic manipulator is a multi-input multi-output (MIMO), highly nonlinear and coupled system. Controlling this system always has been a challenging task for control engineers. In this paper, sliding mode control (SMC) technique utilizing Proportional and Derivative (PD) surface with different reaching laws has been applied on a two-link planar rigid robotic manipulator. Performance of PD sliding surface has been investigated with three different control laws namely, constant rate, exponential and power rate reaching law. Stability of the studied controller configurations have been demonstrated using Lyapunov theory. One of the major problems in SMC, “chattering” is reduced by introducing boundary layer in the controller. Genetic Algorithm optimization technique is used for tuning of parameters of SMC and boundary layer in all the cases for minimum Integral Absolute Error and chattering. Simulation results revealed that all the investigated laws performed equally for set-point tracking and the constant rate reaching law outperforms the other two laws for noise suppression. Also, all three reaching control laws of SMC offered significantly enhanced trajectory tracking and chattering performance as compared to recent literature.

A nonlinear programming approach for the sliding mode control design

The sliding mode control problem is investigated with the frequency domain approach. The authors show that the sliding mode control can be transformed into a Lure problem. With this formulation, it is shown that the conventional sliding mode control with a nonlinear sign function can only guarantee to make the overall system stable but not asymptotically stable. The authors also consider a practical situation where the sign nonlinearity may contain a hysteresis loop. For this situation, they show that even if the hysteresis loop is very small, there still exists a limit cycle. However, chattering phenomenon caused by the limit cycle behavior can be eliminated by a certain class of nonlinearities.

As mobile welding robot are widely applied into industry and the weld quality are highlighted, the more flexible control strategy for welding robot are needed, but these control systems are often hard to control by traditional method, so a nonlinear sliding mode control method based on variable structure control was presented for mobile robot control was designed. Sliding mode control (SMC) is a special nonlinear control method which have quick response, insensitive to parameters variation and disturbance, online identification for plants are not needed, its very suitable for nonlinear system control, but in reality usage, the chattering reduction and elimination is key problem in SMC. In this paper, the kinematics models of mobile welding robot was established, the switching function was designed and the stability was analyzed by Lyapnouv theorem, also the sliding mode controller was designed with uniform reaching law, by simulation we can get the methods that presented in this paper is effective and can applied into linear or nonlinear control system.

Co-design of scheduling protocol and fuzzy sliding mode controller under communication constraints

An effective method, adaptive fuzzy sliding-mode (SM) PI Control to design full-bridge inverter is proposed in this paper. For practical applications, sliding mode control (SMC) with chattering phenomenon is a large hindrance. The modified model of the PI controller is built by the plant extension scheme, in order to relieve the chattering. Also, the fuzzy logic is applied to find the appropriate parameter values of the PI controller, and can adapt to plant parameter variations and external load disturbances. The proposed method has been realized for the actual full-bridge inverters controlled by DSP and CPLD. Simulation and experimental results of the closed-loop system show that the proposed method yields system performance improvement, such as low total harmonic distortion (THD), fast dynamic response, reduced steady-state error, and reduced chattering.

The helicopter can play an important role in military and civil applications owing to its super maneuvering ability, which is closely related to its control system. To improve control performance, this study presents an adaptive sliding mode control strategy merging an adaptive neural network for a nonlinear two‐degrees‐of‐freedom (2‐DOF) helicopter system. By setting up the Lyapunov function, the asymptotic stability of the closed‐loop system is guaranteed, the astringency of the neural network weight renewal course is pledged, and the asymptotic attitude adjustment and trajectory tracking for the desired set point are realized. The availability of the adaptive radial basis function sliding mode control is finally verified via the simulation and real implementation on a nonlinear 2‐DOF helicopter platform.

In this study, the design of Sliding Mode Control (SMC) has been carried out based on a second order reference model with a specified transfer function. The primary objective of this study is to determine the SMC controller parameters according to the desired time response in the output signal. The aim is to determine the optimal control gains that minimize the difference between the reference and plant outputs in a systematic way. By minimizing the error between the reference model and the SMC controlled system model, the optimal SMC parameters, specifically the sliding surface slope ( λ ) and the switching function coefficient ( K ), are obtained. Integral performance criteria were used to minimize the error. Both the reference system and the system controlled by the SMC have second-order transfer functions. While the natural frequency ( ω n ) in the reference model system remains constant, the damping ratio ( ζ ) was varied between 0.5 and 1. For each ζ value in the reference system, the optimal SMC parameters ( λ and K ) were obtained by using the Fmincon optimization algorithm to minimize the error between the two systems based on the selected integral performance criteria. By applying the obtained SMC parameters to the controlled system, unit step responses were obtained in the output of the controlled system. T optimization process was performed based on the transfer functions of two different known systems, and the variation of the optimal SMC parameters according to the damping ratio of the reference model was presented in tables and graphs. The simulation results confirm that the proposed method significantly improves the accuracy and robustness of tracking compared to conventional SMC tuning approaches. These results demonstrate the effectiveness of the proposed method for designing reliable and efficient controllers for second-order dynamic systems. The success of the reference model-based second-order system controlled by the SMC method is clearly demonstrated by the generated graphs and tables. This study introduces a new optimization-based SMC design approach by establishing an explicit analytical relationship between the damping ratio and the controller parameters. In the proposed method uses regression, which avoids the need for iterative tuning and repeated calibration.

This paper deals with the problem of robust Sliding Mode Control (SMC) of uncertain nonlinear dynamic systems. The uncertainties being norm bounded in both state and input matrices as well as norm bounded nonlinearity. Sufficient conditions using Linear Matrix Inequalities (LMIs) are derived to guarantee the existence of linear sliding surface and the quadratic stability of the reduced-order equivalent dynamic system restricted to the sliding surface. Thus, one can design a continuous nonlinear control strategy ensuring a sliding motion despite the presence of uncertainties. We analysis and applies the designed controller to a flexible joint robotic system, in which the simulations results are validate its effectiveness and good performance.

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

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.