Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

Sliding mode control combined with extended state observer for an ankle exoskeleton driven by electrical motor

A novel sliding mode control combined with extended state observer (ESO) is proposed for an ankle exoskeleton driven by electrical motor. During the process of assisting, it is necessary to design an effective controller for assisting torque of ankle exoskeleton. However, the parameter uncertainty of complex dynamics model and the irregular motion of human ankle may affect the torque control accuracy. For a high control precision of assisting torque when facing the modeling uncertainty, the sliding mode control is employed, but a large switching gain is usually needed in order to suppress the disturbance, which cause the control signal vibrate greatly. ESO can observe and suppress the disturbance and modeling uncertainty, but its tracking performance needs to be improved. Therefore, the proposed complex controller takes the advantages of sliding mode control and extended state observer, which can not only improve torque tracking performance but also overcome the disturbance force caused by the change of human joint angle without increasing chattering of control signal. Experimental studies are carried out to validate the effectiveness of the proposed control. The results show the presented controller have better torque tracking performance and robustness stability, and the proposed controller can reduce the chattering compared with the tradition sliding mode control.     

A supervisory fuzzy neural network controller for slider-crank mechanism

A supervisory fuzzy neural network (FNN) controller is proposed to control a nonlinear slider-crank mechanism in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive coupled with a slider-crank mechanism and a supervisory FNN position controller. The supervisory FNN controller comprises a sliding mode FNN controller and a supervisory controller. The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with on-line learning ability. The supervisory controller is designed to stabilize the system states around a defined bound region. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results are provided to show that the proposed control system is robust with regard to plant parameter variations and external load disturbance.     

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.     

Adaptive Fuzzy Sliding Mode Control Algorithm for a Non-Affine Nonlinear System

This paper concerns the design of robust controller for a nonlinear system that can be represented or approximated in a non-affine form. The control algorithm is based on sliding mode control that incorporates a fuzzy tuning technique, and it superposes equivalent control, switching control, and fuzzy control. An equivalent control law is firstly designed based on a nominal system model that was obtained by using curve fitting techniques under MATLAB. Switching control is then added to guarantee that the state reaches the sliding surface in the presence of parameter and disturbance uncertainties. Also, fuzzy tuning schemes, which can be supported by learning techniques derived from neural networks, are employed to improve control performance and to reduce chattering in the sliding mode. To verify the performance of this controller, an experimental platform of a pneumatically actuated top-guided single-seated control valve, which belongs to a classical complex nonlinear system, was constructed. Also, the experimental results show that high performance and attenuated chatter are achieved and thus verify the validity of the proposed control approach to dynamic systems characterized by severe uncertainties.     

可重构飞行控制系统的滑模自适应控制律设计

当飞行控制系统操纵面发生损伤故障时,结合自适应思想,采用滑模控制方法进行重构飞行控制系统的设计.采用单位向量法设计滑模控制器,这种控制器由线性部分和非线性部分组成.线性部分采用改进的线性二次型最优控制器法进行计算,而非线性部分采用自适应增益来更好地适应故障情况.利用某型飞机的纵向飞行控制系统模型进行仿真,结果表明,带有自适应增益的滑模控制方法不仅适合于正常情况下的飞控系统设计,而且对操纵面损伤故障情况具有较强的适应能力,与固定增益情况相比,具有更好的跟踪效果和重构控制效果.     

自适应模糊滑模控制器设计

针对传统滑模控制的抖振问题,利用线性化反馈技术,将模糊自适应和滑模控制相结合,设计一种新型的模糊滑模控制器。通过模糊推理和基于Lyapunov函数的稳定性分析,获得模糊控制规则的自适应律,构成自适应模糊滑模控制器,有效解决了传统滑模控制中,需要确定参数摄动和外部干扰上确界不确定性问题,倒立摆上的运行结果表明该方法的有效性。     

Online Tracking of Varying Inertia using a SDFT Approach

The mechanical dynamics of modern machines very often depend on the angular position of the driven axis. To obtain optimal control, such applications typically require an advanced control structure such as an adaptive controller. Moreover, the variation in the dynamics like changing inertia, load torque, and viscous friction limits the performance and reduces the energy efficiency. Energy savings can be obtained by using so-called trajectory optimization techniques combined with feedforward control. However, both optimization and adaptive control require the knowledge of the position dependency of the mechanical parameters. In the case of reciprocating mechanisms, for instance, this position dependency is significant. Consequently, the mechanical parameters change rapidly at high operating speed of the machine. This paper thus contributes towards fast and accurate estimation of rapidly varying mechanical parameters. A sliding discrete Fourier transform (SDFT) approach is proposed to track the inertia variation of a reciprocating mechanism online. The feasibility is verified with experiments on an industrial pick and place unit. Both the results on the real machine and its CAD equivalent, modelled in a multibody dynamics software package, are considered. In addition, the developed inertia tracking algorithm is proven to be implementable in standard commercial drive components.     

Design and analysis of a plug-in robust compensator: an application to indirect-field-oriented-control induction machine drives

It is well known that the system performance for an indirect-field-oriented-control induction motor drive degrades under the variation of rotor resistance and in the presence of external load torque. In this paper, a plug-in robust compensator for speed and position control enhancement of an indirect-field-oriented-control induction machine drive is developed. In the case where a controller for the induction machine already exists or is in operation with satisfactory nominal tracking performance, this plug-in compensator, designed using the H/sub /spl infin// loop-shaping techniques, can be plugged into the existing controller without affecting the already satisfactory nominal tracking performance of the existing closed-loop system but with the capability to improve the system performance under plant parameter variations and in the presence of external disturbances. Simulation and experimental results are given to validate the proposed plug-in robust compensator.     

Integral sliding mode control with a disturbance observer for next-generation servo track writing

In this paper, we propose a new control scheme that provides position and velocity profile tracking control for next-generation servo track writing (STW). Whereas conventional servo track writers require controllers that perform fast positioning control with fast track seeking and regulation, spiral servo track writers require accurate position and velocity profile tracking control to achieve high quality servo patterns on the media disk. Because STW timing eventually renders geometrically accurate servo patterns, both position and velocity error signals should be regulated within small bounds in a constant velocity region. Regulation via an integral sliding mode controller (SMC) is known to provide good tracking performance; however, use of a high switching gain is inappropriate for an actuator with resonance modes. In this paper, we therefore apply integral sliding mode control with a disturbance observer to STW. The relationship between eigenvalues and control gains is mathematically analyzed to improve dynamic tracking response. To verify the utility of the proposed position and velocity profile tracking control, we perform a comparative study between the proposed and conventional control methods and experimentally validate the performance of the proposed method.     

最优滑模飞行控制系统的设计与仿真

针对机动飞机按时标分离原则可分为快慢两个子系统而形成两环控制结构的特点，提出了最优滑模飞控系统的设计。外环控制器的设计采用基于依赖状态的Riccati方程最优控制器，用以产生最优滑模面，以保证整个飞控系统具有一定的性能鲁棒。内环控制器设计时采用滑动模控制以减小飞控系统对参数变化、模型误差、外部干扰敏感，具有一定的稳定鲁棒性。最后对机动飞机作大机动仿真，仿真结果表明该飞控系统是有效的。     

Indirect sliding mode control based on gray-box identification method for pneumatic artificial muscle

We present an indirect robust nonlinear controller for position-tracking control of a pneumatic artificial muscle (PAMs) testing system. The system modeling is reviewed, for which the existence of uncertain, unknown, and nonlinear terms in the internal dynamics is presented. From the obtained results, an online identification method is proposed for estimation of the internal functions with learning rules designed via a Lyapunov derivative function. A robust nonlinear controller is then designed based on the approximated functions to satisfy the control objective under the sliding mode technique. Appropriate selection of the smooth robust gain and the sliding surface ensures convergence of the tracking error to a desired level of performance. Stability of the closed-loop system is proven through another Lyapunov function. The proposed approach is verified and compared with a conventional proportional–integral–differential (PID) controller, adaptive recurrent neural network (ARNN) controller, and robust nonlinear controller in a real-time system with three different kinds of trajectories and loading. From the comparative experimental results, the effectiveness of the proposed method is confirmed with respect to transient response, steady-state behavior, and loading effect.     

Passivity-based fractional-order integral sliding-mode control design for uncertain fractional-order nonlinear systems

This paper concerns with the problem of designing a passivity-based fractional-order (FO) integral sliding mode controller for uncertain FO nonlinear systems. Utilizing the FO calculus, it is showed that the state trajectories of the closed-loop system reach the FO switching manifold in finite time. The control law ensures the asymptotical stability on the sliding surface. A parameter adjustment scheme for FO integral sliding surface is proposed by using the linear matrix inequality (LMI) approach. The proposed controller can be applied to different systems such as chaotic systems. Finally, simulation results are provided to show the effectiveness of the proposed method controlling chaos in FO Chua circuit and FO Van-der-Pol oscillator.     

具有噪声扰动的统一混沌系统的同步控制

研究了一类具有噪声扰动的统一混沌系统的同步控制问题。基于滑模变结构控制理论,提出了利用不确定性观测器估计扰动噪声,用噪声的观测值来设计控制器的新方法,而且适当选取观测器反馈增益可以使观测误差充分的小,从而可得到几乎没有受到扰动时的控制效果。和常规滑模变结构控制方法相比,所设计的控制器既能有效地抑制抖振,又能降低控制器参数设计的保守性。最后,基于Matlab 6.5软件对Lorenz混沌系统进行分析和数值模拟,验证了该滑模控制方法在混沌同步中的优良性能。     

IBVS based on adaptive sliding mode control for a quadrotor target tracking under perturbations

This paper presents the design of a visual control formulated on an adaptive sliding mode controller for a quadrotor executing a target tracking task subject to disturbances. An image projection of the target from a virtual camera approach, and an image-based visual servoing technique are considered to obtain a singularity-free set of image features to control the position and yaw of the rotorcraft. While, an adaptive sliding mode strategy improves the robustness against bounded external perturbations and uncertainties and provides adaptivity to the visual servoing scheme. Furthermore, an analysis based on Lyapunov theory provides sufficient conditions that guarantee the stability of the closed-loop system. A comparison of the proposed adaptive visual servoing against two recent visual servoing strategies is provided, showing superiority in simulation results. Finally, experimental tests of a Parrot AR.Drone 2.0 tracking a static and moving target further demonstrates the advantages and performance.     

Adaptive robust fast control for induction motors

A new induction motor position controller that exhibits fast response and robustness is proposed. The control strategy is based on the well-known linear quadratic regulator design principle. By adaptively adjusting a penalty parameter, it is shown that the control strategy enables the induction motor system to exhibit fast convergence. Meanwhile, since the sliding mode will occur in the transient process, the fast control inherits the robustness in matched uncertainties of the sliding-mode control. In addition, to alleviate the chattering effect of the switching control signal, a low-pass filter is used to smooth the control and its design is integrated with the switching control design. The performance of the proposed control strategy is verified by experimental results     

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.     

Indirect Sliding Mode Control of Power Converters Via Double Integral Sliding Surface

The steady-state regulation error in power converters that use the conventional hysteresis-modulation-based sliding mode controller can be suppressed through the incorporation of an additional integral term of the state variables into the controller. However, it is found that with the indirect type of sliding mode controller (derived based on the equivalent control approach), the same approach of integral sliding mode control is ineffective in alleviating the converter's steady-state error. Moreover, the error increases as the converter's switching frequency decreases. This paper presents an in-depth study of the phenomenon and offers a solution to the problem. Specifically, it is proposed that an additional double-integral term of the controlled variables to be adopted for constructing the sliding surface of indirect sliding mode controllers. Simulation and experimental results are provided for verification.     

A newly robust controller design for the position control ofpermanent-magnet synchronous motor

A robust controller which is designed by employing variable-structure control and linear-quadratic method is presented for a permanent-magnet synchronous motor (PMSM) position control system. It is to achieve accurate control performance in the presence of plant parameter variation and load disturbance. In addition, it possesses the design flexibility of the conventional state feedback control. It is applied to the position control of a PMSM. Simulation and experimental results show that the proposed approach gives a better position response and is robust to parameter variations and load disturbance     

航空发动机模糊滑模变结构控制研究

针对航空发动机是一个具有时变不确定性的非线性系统,结合模糊控制和滑模变结构控制的特点,提出了一种基于模糊滑模变结构控制的航空发动机控制方法.采用线性滑模面和指数趋近律设计变结构控制器,应用模糊逻辑系统自适应调节切换增益,避免了传统滑模变结构控制系统在到达阶段对不确定性的敏感性,消除了滑模控制中的抖振.通过数字仿真,结果表明所设计的模糊滑模变结构控制器对系统的参数摄动和外部干扰具有不变性,使被控系统在整个控制阶段都具有较强的鲁棒性.