Integral Sliding Mode Control Scheme Research Articles

Integral sliding mode control for interconnected descriptor systems based on a reduced-order observer

In this paper, a reduced-order observer-based integral sliding mode controller is designed for a class of interconnected descriptor systems. First, the observer matching condition is used to transform the interconnected descriptor system into an interconnected normal system. Based on the canonical form, a reduced-order observer is then designed to estimate the state variables of the interconnected descriptor system. In terms of the measurable output variables and the state variables of the proposed reduced-order observer, a sliding mode control scheme is developed to drive the state trajectories of the system to the sliding surface in a finite time and maintain a sliding motion thereafter. It is shown that at the existence of unknown matched disturbances, the proposed observer-based integral sliding mode control scheme can still ensure the asymptotic stability of the resultant closed-loop system. This is an obvious improvement of the existing observer-based sliding mode control methods in descriptor systems fields. Finally, an example is given to verify the effectiveness of the proposed method.

Adaptive observer‐based integral sliding mode control of a piezoelectric nano‐manipulator

In this study, the authors propose an adaptive observer-based integral sliding mode control scheme to support ultra-precision tracking of a multi-axis piezoelectric nano-manipulator. By introducing a modified Dahl model capable of approximating the hysteresis phenomenon, an adaptive observer is developed to compensate the impact of hysteresis, where an adaptive observer-based integral sliding mode control architecture is further proposed with good robustness against model uncertainties. The gain of the sliding mode controller is adaptively estimated for the purposes of fast convergence, chattering alleviation and controller robustness. Finally, the proposed algorithm is implemented in real time on a PZT-actuated nano-manipulating stage, where good robustness and excellent tracking performance are successfully demonstrated, which outperform representative algorithms in the literature.

Time-varying formation for high-order multi-agent systems with external disturbances by event-triggered integral sliding mode control

This paper investigates the time-varying formation problem for high-order multi-agent systems subject to external disturbances. The interaction topology among agents is assumed to be directed and has a directed spanning tree. A novel event-triggered integral sliding mode control strategy is proposed. It can be proved that, with the designed control law and the event-triggered condition, the desired time-varying formation will be reached. Moreover, the Zeno behavior of triggering time sequences can be avoided. Finally, a simulation example is presented to illustrate the effectiveness of the theoretical results.

Adaptive fault tolerant control of dissimilar redundant actuation system of civil aircraft based on integral sliding mode control strategy

In modern aircraft, the dissimilar redundant actuation system is used to resolve the actuator failure issues due to the common cause, thus increasing the system reliability. This paper proposes an adaptive integral sliding mode fault tolerant control strategy to deal with actuator fault/failure in the dissimilar redundant actuation system of civil aircraft. To cope with the unknown actuator faults, the adaptive integral sliding mode controller is designed where the modulation gain is made adaptive to the fault. To deal with the complete failure of certain actuator, the integral sliding mode control is integrated with control allocation scheme and distribute the control input signals to the redundant actuators. The performance of the proposed scheme is tested on the nonlinear model of dissimilar redundant actuation system, where the effect of external airload is accounted during simulations. The effectiveness of the proposed scheme is validated by comparing the simulations with the existing literature.

Adaptive fuzzy radial basis function neural network integral sliding mode tracking control for heavy vehicle electro-hydraulic power steering systems

Due to parametric uncertainties, unknown nonlinearities, and dynamic external disturbances, it is a challenging and valuable task for heavy vehicle electro-hydraulic power steering systems to realize high-precision tracking control. To cope with this complex nonlinear tracking control problem, the integral sliding mode control is an extremely potential control method, which has strong robustness to model uncertainties and unknown disturbances, and can effectively reduce the steady-state error in tracking control process. However, the inherent chattering phenomenon of integral sliding mode control seriously affects its control performance. In order to suppress the chattering while ensuring robustness, adaptive fuzzy technique is adopted as an effective auxiliary means, which can not only deal with the inherent chattering problem of integral sliding mode control and a priori knowledge of the disturbance upper bound in controller design but also dynamically adjust the parameters in the fuzzy rules. Moreover, the designed adaptive fuzzy–integral sliding mode control scheme still needs the precise mathematical models of the control systems. But it is difficult to obtain the model for heavy vehicle electro-hydraulic power steering systems with highly complex and coupling properties. Therefore, to further improve the method, this paper presents a novel adaptive fuzzy–radial basis function neural network–integral sliding mode control method for the complex systems to achieve timely and accurate steering angle tracking control. In addition to the advantages of adaptive fuzzy–integral sliding mode control, the modified controller no longer requires the precise mathematical models of heavy vehicle electro-hydraulic power steering systems and realizes the continuous adaptive updating of weights. Finally, the effectiveness and superiority of the proposed control scheme is illustrated by comparisons and extensive simulations.

Disturbance observer–based adaptive integral sliding mode control for the hybrid automobile electro-coating conveying mechanism

This article seeks to achieve high tracking performance of the hybrid automobile electro-coating conveying mechanism with disturbances and uncertainties. An integral sliding mode control scheme is first presented to eliminate the reaching phase in sliding mode control. Then, an adaptive integral sliding mode controller is designed without knowing the disturbance information. Finally, a composite strategy, referred to as nonlinear disturbance observer (NDO)-based adaptive integral sliding model control, is put forward to further reduce the switching gain. By compensating the lumped disturbances via a NDO, the switching gain is only required to be higher than upper bound of the disturbance estimation error which is much smaller than actual disturbance. The results of both numerical simulations and experiments show that the proposed approach has good control performance especially in reducing the switching gain and alleviating the chattering problem.

Fuzzy Reduced-Order Compensator-Based Stabilization for Interconnected Descriptor Systems via Integral Sliding Modes

This paper investigates the integral sliding mode control problem of T–S fuzzy interconnected descriptor system based on a reduced-order compensator. A canonical equivalent form for T–S fuzzy interconnected descriptor system is first introduced to facilitate the reduced-order compensator design. In terms of the measurable output variables of the T–S fuzzy interconnected descriptor system and the state variables of the proposed reduced-order compensator, an integral sliding mode control scheme is then developed for the T–S fuzzy interconnected descriptor system. The sliding motion is defined in the augmented space formed by the state variables of the original T–S fuzzy interconnected descriptor system and the resulting error system. It is shown that the designing parameters in the switching function can be simultaneously solved and the original T–S fuzzy interconnected descriptor system has no requirement to be relative degree one. Since the estimate error is bounded by an auxiliary dynamical system, when ideal sliding mode occurs, the resulting closed-loop system is asymptotically stable rather than uniformly ultimately bounded. Finally, a double-inverted pendulum system and a ball and beam system are numerically simulated to demonstrate the effectiveness and merits of the method proposed.

Event-triggered Finite-time Consensus with Fully Continuous Communication Free for Second-order Multi-agent Systems

This study deals with finite-time consensus problems of second-order multi-agent systems with intrinsic nonlinear dynamics and external bounded disturbances. First, instead of the time-triggered control algorithm, the event-triggered control algorithm is developed by using integral sliding mode control strategy. Then, a triggering function is explicitly constructed to generate event sequences, and the triggering function is fully continuous communication free. Rigorous proof is given by using Lyapunov stability theory and finite-time stability theory. Several conditions are derived to guarantee the finite-time consensus and exclude Zeno behavior. Finally, a simulation of single-link robotic arms is given to verify the effectiveness of the results.

Robust integral sliding mode control strategy under designed switching rules for uncertain switched linear systems via multiple Lyapunov functions

This paper puts forward a switching rule stabilization design of the robust integral sliding mode control for uncertain switched systems. A kind of common robust integral sliding mode (CRISM) is firstly designed and the system matrices of subsystems under the sliding mode comprise a robust stable matrix set. The stability of the switched system (SS) under the sliding mode is then analyzed by multiple Lyapunov functions (MLF) method. Based on the presented design of CRISM, a sliding mode controller is devised so that the sliding mode can be reached. Finally, the correctness of the proposed method is verified through results of numerical and application simulations.

Novel integral sliding mode control for small-scale unmanned helicopters

Integral sliding mode (ISM) control which consists of a nominal control and a sliding-mode motion control, provides a nice framework for high tracking performance and good disturbance reduction. Our work develops ISM to attenuate the adverse effect of mismatched perturbations. By properly choosing sliding-manifold surface, the elimination of disturbances on control outputs enables to be achieved. Additionally, the chattering of sliding-mode control part is attenuated based on second-order sliding mode idea. Then, the proposed novel ISM control scheme is applied to address trajectory tracking problem for helicopters under perturbations. Approximated input-output linearization is implemented, such that the obtained linearized model is suitable for applying the proposed ism control. The stability of the closed-loop system for helicopter and its convergence to zeros of tracking errors are demonstrated by Lyapunov theory analysis. Several comparison simulations illustrate the effectiveness and superiority of the proposed methods.

Adaptive Sliding Mode Fault-Tolerant Control for a Class of Uncertain Systems With Probabilistic Random Delays

This paper investigates the robust control problem of uncertain nonlinear systems subject to actuator faults via the integral sliding mode control (ISMC) scheme. The actuator failures contain the cases of an outage, loss of effectiveness, and stuck fault, which are frequently encountered in practical applications. Furthermore, in this paper, the time-varying delay considered obeys the probability distribution within certain intervals. By fully considering the information of the probabilistic random delay, new sufficient conditions are given to ensure the asymptotical stability of the controlled system with prescribed $H_\infty $ performance. Moreover, a new control law is proposed to compensate for the effects induced by the actuator faults, and an adaptive mechanism is adapted to estimate the unknown terms. In a word, the proposed ISMC scheme ensures the asymptotical stability with guaranteed $H_\infty $ performance of the closed-loop system and forces that the state trajectories are attracted to the pre-designed sliding surface. Finally, a practical example of the rocket fairing structural acoustic model is used to clarify the validly of the presented control method.

Implementation of model-free motion control for active suspension systems

Abstract This paper focuses on the implementation of motion control for active suspension systems using a novel scheme of model-free finite-time tracking control method. The proposed strategy facilitates the realization since the system plant modeling is not needed. Correspondingly, the suspension vertical dynamics including external disturbances are estimated by the time-delay estimation, and its estimated error is compensated by the integral sliding mode control scheme. Theoretical analysis proves that the sliding mode and desired system dynamics can achieve a finite time convergence performance with continuous control law. In active suspension control, the continuous control law contributes to preventing the unexpected chattering in practical implementation. The advantage of the presented control algorithm is verified via comparative investigation, especially the comparison of the existing extended state observer-based feedback control scheme, which requires a high-gain observer to realize the desired dynamics. Comparative experimental studies are presented to confirm the effectiveness and superiority of the proposed control strategy over the traditional methods.

Adaptive fuzzy integral sliding mode control of blood glucose level in patients with type 1 diabetes: In silico studies

Currently, artificial pancreas is an alternative treatment instead of insulin therapy for patients with type 1 diabetes mellitus. Closed-loop control of blood glucose level (BGL) is one of the difficult tasks in biomedical engineering field due to nonlinear time-varying dynamics of insulin-glucose relation that is combined with time delays and model uncertainties. In this paper, we propose a novel adaptive fuzzy integral sliding mode control scheme for BGL regulation. System dynamics is identified online using fuzzy logic systems. The presented method is evaluated in silico studies by nine different virtual patients in three different groups for two continuous days. Simulation results demonstrate effective performance of the proposed control scheme of BGL regulation in presence of simultaneous meal and physical exercise disturbances. Comparison of the proposed control method with proportional–integral–derivative (PID) control and model predictive control (MPC) shows a superiority of the adaptive fuzzy integral sliding mode control with regard to two conventional methods of BGL regulation (PID and MPC) and sliding mode control.

$$H_\infty $$ H ∞ tracking adaptive fuzzy integral sliding mode control for a train of self-balancing vehicles

A series of self-balancing vehicles is stabilized and controlled in this research work. The system is composed of several Segway $$\frac{{\mathrm{TM}}}{}$$ type platforms interconnected through flexible links. The system is inherently highly nonlinear and underactuated which makes the tracking task very challenging. In this paper, $$H_\infty $$ tracking adaptive fuzzy integral sliding mode control scheme is proposed for n-self-balancing interconnected vehicles system where uncertainties and disturbances are included. First, a nonlinear dynamic model with uncertainties for the train system with n-vehicles is derived using the Lagrangian method assuming the vehicles moving in tandem on a inclined path. Then, the dynamics of the train system with n-vehicles is formulated as an error dynamics according to a specified reference signal. A fuzzy technique with an on-line estimation scheme is developed to approximate the dynamics of the train system with n-vehicles. The advantage of employing an adaptive fuzzy system is the use of linear analytical results instead of estimating nonlinear uncertain functions in dynamics with an online update law. Using the concept of parallel distributed compensation, the adaptive fuzzy scheme combined with the integral sliding mode control scheme is synthesized to address the system uncertainties and the external disturbances such that $$H_\infty $$ tracking performance is achieved. Simulation results for 2-self-balancing interconnected vehicles system are presented to show the effectiveness and performance of the proposed control scheme.

Distributed Event‐Triggered Consensus for Multiple Underactuated Systems Under Markovian Switching Topologies

AbstractThis paper presents a distributed consensus algorithm that employs event‐triggered communication for multiple underactuated systems under Markovian switching topologies. Instead of the general stochastic topology, the graph of the entire system is governed by a set of Markov chains to the edges, which can recover the general Markovian switching topologies in line with the practical communication network. By utilizing integral sliding mode control strategy, rigorous analysis of the asymptotic convergence results has been performed through graph theory and Lyapunov stability theory. An event‐triggered communication law is provided for each agent and Zeno behavior of triggering time sequences is excluded. It will yield to the very first application of the multiple underactuated systems, in which the system states could be enforced to track the leader. Finally, the illustrative simulations on six underactuated two‐link manipulators are given to demonstrate the effectiveness of theoretical results.

Design of a fractional-order adaptive integral sliding mode controller for the trajectory tracking control of robot manipulators

In this study, trajectory tracking control of six–degrees of freedom robotic manipulator has been performed using the proposed fractional-order adaptive integral sliding mode control scheme. The proposed method is first composed by fractional-order and adaptive integral sliding mode control to achieve the finite-time convergence, chattering-free control inputs, better tracking performance and robustness for the robotic manipulator. Furthermore, an adaptive method has been utilized to evaluate and compensate the uncertain and unknown dynamics of the system without relying on the prior knowledge of the upper bounds. To illustrate the efficiency of the proposed fractional-order adaptive integral sliding mode control method, the real-time experimental studies have been performed for the six–degrees of freedom industrial robot manipulator. The experimental outcomes strongly verified that the proposed controller gives quite well trajectory tracking response and faster convergence compared with the classical integral sliding mode control under the external payload.

Differential Steering Based Yaw Stabilization Using ISMC for Independently Actuated Electric Vehicles

Differential drive assistance steering (DDAS) is an emerging assisted steering mechanism in in-wheel-motor driven (IWMD) electric vehicles, yielded by the differential moment of the front tires in the steering system. DDAS can steer the front wheels when there is no steering power from the steering motor, and thus can be used as a redundant steering mechanism. To realize the yaw control when the active front steering entirely breaks down and guarantee the transient control performance therein, this paper proposes an integral sliding mode control (ISMC) approach for IWMD electric vehicles steered by DDAS. Two contributions are made in this paper: 1) An improved disturbance observer based ISMC strategy is designed to cope with the unknown mismatched disturbances, and the composite nonlinear feedback technique is employed to design the nominal part of the controller to restrain overshoots and remove steady-state errors considering the tire force saturations; 2) An adaptive super-twisting control approach is proposed to deal with the disturbances with unknown boundaries using a continuous controller while eliminating the chattering effect. The system stability and robustness are proved via Lyapunov approach. CarSim-Simulink simulation has verified the effectiveness of the proposed control approach in the case of the steering fault.

Repetitive Control based on Integral Sliding Mode Control of Matched Uncertain Systems

This paper proposed an integral sliding mode control scheme based on repetitive control for uncertain repetitive processes with the presence of matched uncertainties, external disturbances and norm-bounded nonlinearities. A new method based on the combination of repetitive control and sliding mode approach is studied in order to use the robustness sensibility property of the sliding mode control to matched uncertainties and disturbances and to cancel gradually tracking error for periodic processes. A sufficient condition of the existence of sliding mode is studied based on basic repetitive control and a sliding mode controller is synthesized through linear matrix inequalities, which guarantees the stability along the periods of the controlled closed-loop process and the reachability of the sliding surface is ensured. Then, an adaptive integral sliding mode controller is synthesized to improve performances of the proposed control scheme. The effectiveness of the proposed controlled design schemes is proved by the use of a third order uncertain mechanical system and the simulation results using the new approaches give good performances.

Extended state observer–based intelligent double integral sliding mode control of electronic throttle valve

Motivated by achieving precise positioning of the throttle plate, an extended state observer–based intelligent double integral sliding mode control strategy is proposed for the electronic throttle control system. Specifically, an extended state observer is first designed to observe the opening angle change of the electronic throttle and compensate unexpected external disturbance. On this basis, an intelligent double integral sliding mode controller for electronic throttle valve is presented based on Lyapunov stability theory and sliding mode control theory, which includes stability analysis and parameter adaptation design. Finally, extensive simulations are conducted to demonstrate the superior performance of the proposed method.

Robust Stabilization of T-S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes.

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.