Sliding Mode Control of Uncertain Stochastic Hybrid Delay Systems with Average Dwell Time

This paper investigates the problem of sliding mode control (SMC) for uncertain switched stochastic system with time-varying delay. The system under consideration is concerned with the stochastic dynamics and deterministic switching laws. An integral sliding surface is constructed and the stable sliding mode is derived. A sufficient condition for mean-square exponential stability of the sliding mode is developed under a class of switching laws based on the average dwell time method. Variable structure controllers are designed to guarantee the existence of the sliding mode from the initial time. An illustrative example is used to demonstrate the effectiveness of the proposed scheme.     

Modeling,control and experimental investigation of horizontal hydraulic flight motion simulator

The horizontal hydraulic flight motion simulator (HHFMS) is widely applied in the hardware-in-the-loop (HWIL) simulation of the aircraft attitude attributing to high dynamic response and large power density when a heavy load is tested. In order to achieve a high-precision control performance of the HHFMS, some serious mismatched uncertainties consisting of nonlinear friction torque, unbalanced gravity torque, inertia variation and unmodeled dynamics have to be taken into account. In particular, gravity torque, as an asymmetrical load, will degrade the control performance at the starting moment. In this paper, via transforming mismatched uncertainties into matched uncertainties as a unified disturbance, a cascaded model was firstly established, which can not only avoid designing the complex virtual control laws but also help indirectly reduce the asymmetrical effect of gravity torque. Then, a linear extended state observer (LESO) based continuous sliding mode control (SMC) was proposed. LESO is expected to realize a good suppression of disturbance, as well as convenient acquisition of states signals such as velocity and acceleration. In addition to ensuring the control accuracy and the robustness, continuous SMC without sign function also frees from worrying about possible chattering. Moreover, a setting criterion of two parameters that satisfy Hurwitz's Condition in the third-order SMC was also provided. Finally, experimental investigation shows the effectiveness of dynamic modeling and the practicability of the proposed control method.     

Sliding mode control and stability analysis of buck DC-DC converter

This paper is proposed to deal with the voltage regulation of buck DC-DC converter based on sliding mode control (SMC) technology. A buck DC-DC converter with parasitic resistance is inherently a bilinear system possessing inevitable uncertainties, such as variable resistive load and input disturbance. First, the buck DC-DC converter is modified into an uncertain linear model. Then, SMC technology is adopted to suppress the input disturbance and reduce the effects from the load variation. In addition, the continuous conduction mode (CCM) for normal operation can be guaranteed by the design of sliding function. Finally, experimental results are included for demonstration.     

Reliable Sliding-Mode Control for Markovian Jumping Systems Subject to Partial Actuator Degradation

In this work, a novel robust sliding-mode control (SMC) method has been provided for uncertain stochastic Markovian jumping systems subject to actuator degradation, such that the closed-loop system is globally asymptotically stable (with probability one). In the design of switching functions, a set of specified matrices are employed such that the connections among sliding surfaces corresponding to each mode are established. Then, a sliding-mode controller is synthesized to ensure the reachability of the specified switching surface despite actuator degradation and uncertainties. Finally, the simulation results illustrate the proposed method and the effectiveness.     

A Neuro-Sliding-Mode Control With Adaptive Modeling of Uncertainty for Control of Movement in Paralyzed Limbs Using Functional Electrical Stimulation

During the past several years, several strategies have been proposed for control of joint movement in paraplegic subjects using functional electrical stimulation (FES), but developing a control strategy that provides satisfactory tracking performance, to be robust against time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, muscle fatigue, and external disturbances, and to be easy to apply without any re-identification of plant dynamics during different experiment sessions is still an open problem. In this paper, we propose a novel control methodology that is based on synergistic combination of neural networks with sliding-mode control (SMC) for controlling FES. The main advantage of SMC derives from the property of robustness to system uncertainties and external disturbances. However, the main drawback of the standard sliding modes is mostly related to the so-called chattering caused by the high-frequency control switching. To eliminate the chattering, we couple two neural networks with online learning without any offline training into the SMC. A recurrent neural network is used to model the uncertainties and provide an auxiliary equivalent control to keep the uncertainties to low values, and consequently, to use an SMC with lower switching gain. The second neural network consists of a single neuron and is used as an auxiliary controller. The control law will be switched from the SMC to neural control, when the state trajectory of system enters in some boundary layer around the sliding surface. Extensive simulations and experiments on healthy and paraplegic subjects are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed neuroadaptive SMC. The results show that the neuro-SMC provides accurate tracking control with fast convergence for different reference trajectories and could generate control signals to compensate the muscle fatigue and reject the external disturbance.     

基于观测器的滑模制导律

为考虑拦截导弹控制回路动态,所设计的滑模制导律在实际应用中往往涉及到不可量测的反馈状态变量和不确定性的内部参数等问题。采用自适应控制和观测方法,给出了一种基于观测器的自适应滑模制导律,观测器主要用于实现对系统状态,如视线角速度的高阶导数和有界不确定项,如相对运动速度的高阶导数等的在线估计,从而满足实际情形下的可执行性要求。制导律推导中考虑到了拦截导弹具有一阶机动动态的情形,且该方法也可以推广到具有高阶机动动态下的设计。非线性系统仿真表明,相比于传统的比例导引和滑模制导律,该制导律在足够的机动性能下,不仅可以实现对机动目标的碰撞拦截,且具有较强的机动性能和拦截性能优势,同时仿真结果也表明了所设计的观测器的有效性。     

Neural-Network-Based Terminal Sliding-Mode Control of Robotic Manipulators Including Actuator Dynamics

A neural-network-based terminal sliding-mode control (SMC) scheme is proposed for robotic manipulators including actuator dynamics. The proposed terminal SMC (TSMC) alleviates some main drawbacks (such as contradiction between control efforts in the transient and tracking errors in the steady state) in the linear SMC while maintains its robustness to the uncertainties. Moreover, an indirect method is developed to avoid the singularity problem in the initial TSMC. In the proposed control scheme, a radial basis function neural network (NN) is adopted to approximate the nonlinear dynamics of the robotic manipulator. Meanwhile, a robust control term is added to suppress the modeling error and estimate the error of the NN. Finite time convergence and stability of the closed loop system can be guaranteed by Lyapunov theory. Finally, the proposed control scheme is applied to a robotic manipulator. Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.      

Congestion Control for DiffServ Network Using Second-Order Sliding Mode Control

In this paper, a nonlinear fluid flow model is used to analyze and control DiffServ Network. The controller design is based on the integrated dynamic congestion control strategy and a leader–follower control scheme. With respect to standard sliding mode control (SMC), the second-order sliding mode technique shows the same properties of robustness to uncertainties of model and considerable simplification of model used in the design. Apart from the robustness feature, the proposed second-order SMC laws have the advantage of being continuous, thus eliminating the chattering effect and being more acceptable in application. The performance of the control scheme is verified by the simulation results.      

Neural network based-time optimal sliding mode control for an autonomous underwater robot

This paper presents a robot control system using sliding mode control (SMC) as a core controller. The SMC switches according to the Pontryagin’s time optimal control principle, in which the solution is obtained by using neural network approach. The control system is implemented on Chalawan, a six-degree-of-freedom autonomous underwater robot developed at Mechatronics Laboratory, AIT. The control system can be applied to underwater robots, which have similar kind of architecture. Performance of the proposed controller is compared with various classical SMCs and conventional linear control system. The comparison detail results such as controller performance and error phase portrait are presented and analyzed. Such comparisons ensure the implementation success and prove it as a real time-optimal controller. The results also show the controller’s effective capabilities in plant nonlinearity and parameters uncertainties.     

Adaptive incremental sliding mode control for a robot manipulator

An adaptive incremental sliding mode control (AISMC) scheme for a robot manipulator is presented in this paper. Firstly, an incremental backstepping (IBS) controller is designed using time-delay estimation (TDE) to reduce dependence on the mathematical model. After substituting IBS controller into the nonlinear system, a linear system w.r.t. tracking errors is obtained while TDE error is the disturbance. Then, the AISMC scheme, including a nominal controller and an SMC, is developed for the resulted linear system to improve control performance. According to the equivalent control method, the SMC in the AISMC scheme is to handle TDE error. To receive optimal control performance at the sliding manifold, an LQR controller is selected as the nominal controller. The SMC is designed based on positive semi-definite barrier function (PSDBF) since it prevents switching gains from being over/under-estimated, and two practical problems are addressed in this paper: A new PSDBF is designed and conservative (large) setting bounds affecting tracking precision and/or system stability are avoided; An improved PSDBF based SMC is developed where the PSDBF and an adaptive parameter are used simultaneously to regulate switching gains, and the system is still stable when sliding variable occasionally exceeds the predefined vicinity. Moreover, finite-time convergence property of the sliding variable is strictly analyzed. Finally, real-time experiments are conducted to verify the effectiveness of the proposed control method.     

A new controller for boost dc–dc converters based on a novel sliding surface

ABSTRACT

In this paper, two control schemes for boost converters affected by uncertainties in input voltage and load are proposed. The boost converter dynamics is redefined in terms of new state variables to facilitate the use of a disturbance observer that can estimate matched and unmatched disturbances. A sliding surface, which is new in the context of boost converters, is proposed to enable tracking and regulation of output voltage without requiring measurement of input voltage and load current. The stability of the overall system including the disturbance observer, the sliding variable and the output is proved. The performance of the schemes is assessed for regulation of output voltage and tracking of reference voltage by simulation as well as experimentation in which various types of uncertainties and various types of reference voltages are considered.     

Analysis and Experimental Study of Proportional-Integral Sliding Mode Control for DC／DC Converter

DC/DC converter using the proportional-integral (PI) sliding mode control (SMC)scheme is investigated, including the selection of the switching surface, the proof of the reaching condition and the existence condition of sliding motion. The sliding regime and the local stability are given. The implementation of the PI SMC is simpler than other SMC schemes and the steady-state error is eliminated. A prototype based on Buck converter is built up. The experimental results show that the dynamic performance and robustness to the parameter variations and external disturbances are improved.     

Robust tracking control of mechatronic arms

A robust tracking control scheme based on variable structure systems (VSS) theory is presented to cope with the uncertainties and parameter variations in mechatronic arm dynamics. A modification of VSS is used to remove its restrictions with regard to chattering and required control efforts. By blending VSS with a self-organizing controller (SOC), a sliding mode self-organizing controller (SLIMSOC)scheme has been developed. In this scheme, both control actions and performance evaluation are executed using the distance from the desired sliding surface and rate of approach to it. Comparisons are drawn and it is shown that the inherent robustness properties of variable structure systems are retained while the undesirable chatter motion of the sliding mode is eliminated. The results are illustrated by applications of SLIMSOC on a direct drive SCARA type of robot.     

Robust decoupled control of direct field-oriented induction motor drive

This paper focuses on the development of a decoupling mechanism and a speed control scheme based on total sliding-mode control (TSMC) theory for a direct rotor field-oriented (DRFO) induction motor (IM). First, a robust decoupling mechanism including an adaptive flux observer and a sliding-mode current estimator is investigated to decouple the complicated flux and torque dynamics of an IM. The acquired flux angle is utilized for the DRFO object such that the dynamic behavior of the IM is like that of a separately excited dc motor. However, the control performance of the IM is still influenced seriously by the system uncertainties including electrical and mechanical parameter variation, external load disturbance, nonideal field-oriented transient responses, and unmodeled dynamics in practical applications. In order to enhance the robustness of the DRFO IM drive for high-performance applications, a TSMC scheme is constructed without the reaching phase in conventional sliding-mode control (CSMC). The control strategy is derived in the sense of Lyapunov stability theorem such that the stable tracking performance can be ensured under the occurrence of system uncertainties. In addition, numerical simulations as well as experimental results are provided to validate the effectiveness of the developed methodologies in comparison with a model reference adaptive system flux observer and a CSMC system.     

Event-triggered type-2 fuzzy-based sliding mode control for steer-by-wire systems

This paper proposes an event-triggered higher-order sliding mode control for steer-by-wire (SbW) systems subject to limited communication resources and uncertain nonlinearity. First, an interval type-2 fuzzy logic system (IT2 FLS) is adopted to approximate the uncertain nonlinearities. A fuzzy-based state observer is developed to estimate unavailable states of the extended SbW system. Then, to save communication resources and eliminate chattering, an event-triggered higher-order sliding mode control is proposed for the SbW system. The key advantage is that the proposed control scheme can offset the observation error and the event-triggering error. After that, the practical finite-time stability of the closed-loop SbW system is proved in the framework of the Lyapunov theory. Finally, numerical simulations and vehicle experiments are given to evaluate the effectiveness and superiority of the proposed scheme.     

Design of output feedback sliding mode controller for SEPIC converter for robustness

ABSTRACT

This paper presents an output feedback sliding mode control (SMC) of a SEPIC converter whose utilisation areas include MPPT and PFC in industrial applications. Owing to their discrete nature, DC-DC converters represent challenges in modelling therefore special linearisation techniques are required. In this study, state space averaging method, which is one of those linearisation methods, is employed in the modelling phase of the design process. Since SEPIC has non-minimum phase and non-linear characteristics, conventional linear control algorithms offer unsatisfactory performance in the face of disturbances, thereby requiring more advanced control strategies. Recently, SMC technique has gained popularity due to whose robust nature against parameter variations, modelling uncertainties and disturbances. Output Feedback Discrete Sliding Mode Control (ODSMC) is a SMC control algorithm that requires only output to be measured instead of full state vector, thereby eliminating the observer design process. To validate the superiority of the non-linear controller in the case of supply voltage and load current variations with sensor noise, results of numerical simulations that are carried are also given.     

A second order sliding mode strategy for fault detection and fault-tolerant-control of a MEMS optical switch

Optical switches are widely used in telecommunication industry due to their many desirable characteristics. In this paper, robust fault detection and fault-tolerant-control (FTC) system for an uncertain nonlinear MEMS optical switch are presented. The design strategy is based on the second order sliding mode approach. A robust second order nonlinear sliding mode observer capable of filtering unwanted high frequencies due to unmodeled dynamics is used to generate quantities called the the residuals. The residuals are then used for the purpose of fault detection and alarm generation. Once an alarm is registered, a fault tolerant control strategy is employed. Two different fault-tolerant control strategies for the unhealthy system are considered. The first strategy is based on conventional sliding mode, while the second is based on a second order sliding mode theory. Robustness and convergence of the proposed schemes are proved using the second method of Lyapunov and the super-twisting algorithm. A comparative study is then performed to demonstrate the superior capability of second order sliding mode control strategy in fault accommodation. Finally, the effectiveness of the proposed strategy for detection of faults, and subsequent control of the MEMS optical switch is illustrated through simulation studies.     

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.     

A fault-tolerant strategy based on SMC for current-controlled converters

The sliding mode control (SMC) is used to control variable structure systems such as power electronics converters. This paper presents a fault-tolerant strategy based on the SMC for current-controlled AC–DC converters. The proposed SMC is based on three sliding surfaces for the three legs of the AC–DC converter. Two sliding surfaces are assigned to control the phase currents since the input three-phase currents are balanced. Hence, the third sliding surface is considered as an extra degree of freedom which is utilised to control the neutral voltage. This action is utilised to enhance the performance of the converter during open-switch faults. The proposed fault-tolerant strategy is based on allocating the sliding surface of the faulty leg to control the neutral voltage. Consequently, the current waveform is improved. The behaviour of the current-controlled converter during different types of open-switch faults is analysed. Double switch faults include three cases: two upper switch fault; upper and lower switch fault at different legs; and two switches of the same leg. The dynamic performance of the proposed system is evaluated during healthy and open-switch fault operations. Simulation results exhibit the various merits of the proposed SMC-based fault-tolerant strategy.