Nonlinear robust adaptive control for bidirectional stabilization system of all-electric tank with unknown actuator backlash compensation and disturbance estimation

Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.

Adaptive inverse control of air supply flow for proton exchange membrane fuel cell systems

To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.

Adaptive inverse control of random vibration based on the filtered-X LMS algorithm

Random vibration control is aimed at reproducing the power spectral density （PSD） at specified control points. The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequency response functions （FRFs）, which lengthens the control loop time in the equalization process. Likewise, the feedback control algorithm has a very slow convergence rate due to the small value of the feedback gain parameter to ensure stability of the system. To overcome these limitations, an adaptive inverse control of random vibrations based on the filtered-X least mean-square （LMS） algorithm is proposed. Furthermore, according to the description and iteration characteristics of random vibration tests in the frequency domain, the frequency domain LMS algorithm is adopted to refine the inverse characteristics of the FRF instead of the traditional time domain LMS algorithm. This inverse characteristic, which is called the impedance function of the system under control, is used to update the drive PSD directly. The test results indicated that in addition to successfully avoiding the instability problem that occurs during the iteration process, the adaptive control strategy minimizes the amount of time needed to obtain a short control loop and achieve equalization.

Adaptive Pseudo Inverse Control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)scheme.The"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is included.The main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is achieved.Analysis of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

Improved filtered-ε adaptive inverse control and its application on nonlinear ship maneuvering

The drawbacks of common nonlinear Filtered-ε adaptive inverse control （AIC） method, such as the unreliability due to the change of delay time and the faultiness existing in its disturbance control loop, are discussed. Based on it, the diagram of AIC is amended to accommodate with the characteristic of nonlinear object with time delay. The corresponding Filtered-ε adaptive algorithm based on RTRL is presented to identify the parameters and design the controller. The simulation results on a nonlinear ship model of ＂The R.O.V Zeefakker＂ show that compared with the previous scheme and adaptive PID control, the improved method not only keeps the same dynamic response performance, but also owns higher robustness and disturbance rejection ability, and it is suitable for the control of nonlinear objects which have higher requirement to the maneuverability under complex disturbance environment.

Robust adaptive precision motion control of tank horizontal stabilizer based on unknown actuator backlash compensation

Backlash nonlinearity inevitably exists in the actuator of tank horizontal stabilizer and has adverse effect on the system control performance,however,how to effectively eliminate its effect remains a pending issue.To solve this problem,a robust adaptive precision motion controller is presented in this paper to address uncertainties and unknown actuator backlash of tank horizontal actuator.The controller handles the modeling uncertainties including parameter uncertainties and unmodeled disturbances by integrating adaptive feedforward compensation and continuous nonlinear robust law.Based on the backstepping method,a smooth backlash inverse model is constructed by combining the adaptive idea.Meanwhile,the unknown backlash parameters of the system can be approximated through the parameter adaptation,and the impact of the actuator backlash nonlinearity is effectively compensated via the inverse operation,which can availably improve the tracking performance.Moreover,the adaptive law can update the disturbance ranges of tank horizontal stabilizer online in real time,which enhances the feasibility in practical engineering applications.Furthermore,the stability analysis based on Lyapunov function shows that with the existence of unmodeled disturbances and unknown actuator backlash,the designed controller guarantees excellent asymptotic output tracking performance.Extensive comparative results verify the effectiveness of the proposed control strategy.

Adaptive fuzzy nonlinear inversion-based control for uncertain chaotic systems

This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.

NONLINEAR DYNAMIC INVERSION CONTROL WITH ADAPTIVE COMPENSATION FOR FLIGHT CONTROL SYSTEM

A type of nonlinear dynamic inversion control with adaptive compensation is proposed in order to overcome its over sensitivity to parameter uncertainty and disturbance for flight control system using nonlinear dynamic inversion. This control strategy is different from the general strategy of a nonlinear adaptive control by taking into consideration both parameter uncertainty and external disturbance, the two major uncertain forms in flight control. Finally, an analysis of the stabilily of this control structure is given.

Position Control of Flexible Joint Carts Using Adaptive Generalized Dynamics Inversion

This paper presents the design and implementation of Adaptive Generalized Dynamic Inversion(AGDI)to track the position of a Linear Flexible Joint Cart(LFJC)system along with vibration suppression of the flexible joint.The proposed AGDI control law will be comprised of two control elements.The baseline(continuous)control law is based on principle of conventional GDI approach and is established by prescribing the constraint dynamics of controlled state variables that reflect the control objectives.The control law is realized by inverting the prescribed dynamics using dynamically scaledMoore-Penrose generalized inversion.To boost the robust attributes against system nonlinearities,parametric uncertainties and external perturbations,a discontinuous control law will be augmented which is based on the concept of sliding mode principle.In discontinuous control law,the sliding mode gain is made adaptive in order to achieve improved tracking performance and chattering reduction.The closed-loop stability of resultant control law is established by introducing a positive define Lyapunov candidate function such that semi-global asymptotic attitude tracking of LFJC system is guaranteed.Rigorous computer simulations followed by experimental investigation will be performed on Quanser’s LFJC system to authenticate the feasibility of proposed control approach for its application to real world problems.

APPLICATION OF NEURAL NETWORK INVERSE CONTROL SYSTEM IN TURBO DECODING

Adaptive inverse control system can improve the performance of turbo decoding,and modeling turbo decoder is one of the most important technologies. A neural network model for the inverse model of turbo decoding is proposed in this paper. Compared with linear filter with its revi-sion,the general relationship between the input and output of the inverse model of turbo decoding system can be established exactly by Nonlinear Auto-Regressive eXogeneous input (NARX) filter. Combined with linear inverse system,it has simpler structure and costs less computation,thus can satisfy the demand of real-time turbo decoding. Simulation results show that neural network in-verse control system can improve the performance of turbo decoding further than other linear con-trol system.

ADAPTIVE FLIGHT CONTROL SYSTEM OF ARMED HELICOPTER USING WAVELET NEURAL NETWORK METHOD

A discussion is devoted to the design of an adaptive flight control system of the armed helicopter using wavelet neural network method. Firstly, the control loop of the attitude angle is designed with a dynamic inversion scheme in a quick loop and a slow loop. respectively. Then, in order to compensate the error caused by dynamic inversion, the adaptive flight control system of the armed helicopter using wavelet neural network method is put forward, so the BP wavelet neural network and the Lyapunov stable wavelet neural network are used to design the helicopter flight control system. Finally, the typical maneuver flight is simulated to demonstrate its validity and effectiveness. Result proves that the wavelet neural network has an engineering practical value and the effect of WNN is good.

Adaptive Control for a Class of Systems with Output Deadzone Nonlinearity

This paper presents a continuous-time adaptive control scheme for systems with uncertain non-symmetrical deadzone nonlinearity located at the output of a plant. An adaptive inverse function is developed and used in conjunction with a robust adaptive controller to reduce the effect of deadzone nonlinearity. The deadzone inverse function is also implemented in continuous time, and an adaptive update law is designed to estimate the deadzone parameters. The adaptive output deadzone inverse controller is smoothly differentiable and is combined with a robust adaptive nonlinear controller to ensure robustness and boundedness of all the states of the system as well as the output signal. The mismatch between the ideal deadzone inverse function and our proposed implantation is treated as a disturbance that can be upper bounded by a polynomial in the system states. The overall stability of the closed-loop system is proven by using Lyapunov method, and simulations confirm the efficacy of the control methodology.

Robust Adaptive Control of PVTOL System via Minimum Projection Method

＂Dynamic extension＂ is commonly used for stabilization of the planar vertical take off and landing （PVTOL） system. Most controllers designed by the method are based on ＂dynamic＂ control Lyapunov functions （CLFs）. We design a C^∞ differentiable ＂static＂ CLF for the PVTOL system by dynamic extension and minimum projection method. Then we propose an inverse optimal controller based on the static CLF that attains a gain margin. We design an adaptive control input and show the robustness of the controller by computer simulation.

电液振动台加速度时域波形自适应控制策略

针对电液振动台加速度时域波形复现精度低的问题,提出了一种基于内环前馈逆补偿和外环非线性滤波的在线自适应控制策略。首先,构建了电液振动台伺服驱动机构模型,采用三状态控制策略获得了初步加速度控制性能;其次,基于多新息遗忘梯度算法辨识了三状态控制下系统参数化模型,利用零幅值跟踪技术构建了内环前馈逆补偿策略,拓展了系统频宽,降低了相位滞后误差;然后,引入了外环非线性Volterra自适应滤波算法,抑制了电液振动台模型参数偏差、非线性动态特性和不确定性扰动的影响;最后,在搭建的水平单轴电液振动台上开展了时域波形复现对比实验。结果表明,提出的自适应控制策略与传统策略相比具有更优越的加速度时域波形复现精度。

Start-up current adaptive control for sensorless high-speed brushless DC motors based on inverse system method and internal mode controller

The start-up current control of the high-speed brushless DC（HS-BLDC） motor is a challenging research topic. To effectively control the start-up current of the sensorless HS-BLDC motor, an adaptive control method is proposed based on the adaptive neural network（ANN）inverse system and the two degrees of freedom（2-DOF） internal model controller（IMC）. The HS-BLDC motor is identified by the online least squares support vector machine（OLS-SVM） algorithm to regulate the ANN inverse controller parameters in real time. A pseudo linear system is developed by introducing the constructed real-time inverse system into the original HS-BLDC motor system. Based on the characteristics of the pseudo linear system, an extra closed-loop feedback control strategy based on the 2-DOF IMC is proposed to improve the transient response performance and enhance the stability of the control system. The simulation and experimental results show that the proposed control method is effective and perfect start-up current tracking performance is achieved.

A new impedance and robust adaptive inverse control approach for a teleoperation system with varying time delay

This paper presents a new robust adaptive inverse control approach for a force-reflecting teleoperation system with varying time delay. First,an impedance control is designed for the master robot. Second,an adaptive inverse control is proposed for the slave robot. Finally,the slave side controller is modified such that the robust stability and performance are achieved. In addition,robust stability analysis has been performed and optimal behavior is ensured by using standard characteristic polynomials. It is shown that despite of presence of randomly-varying time delay,the proposed control algorithm compensates the position drifts efficiently. Demonstrable simulation studies confirm the effectiveness of the proposed control system and its advantages over the existing sliding mode control strategies.

H_∞ Inverse Optimal Adaptive Fault-Tolerant Attitude Control for Flexible Spacecraft with Input Saturation

An adaptive inverse optimal attitude controller for flexible spacecraft with fault-free actuator is designed based on adaptive control Lyapunov function and inverse optimal methodology subjected to unknown parameter uncertainties,external disturbances and input saturation.The partial loss of actuator effectiveness and the additive faults are considered simultaneously to deal with actuator faults,and the prior knowledge of bounds on the effectiveness factors of the actuators is assumed to be unknown.A fault-tolerant control version is designed to handle the system with actuator fault by introducing a parameter update law to estimate the lower bound of the partial loss of actuator effectiveness faults.The proposed fault-tolerant attitude controller ensures robustness and stabilization,and it achieves H_∞ optimality with respect to a family of cost functionals.The usefulness of the proposed algorithms is assessed and compared with the conventional approaches through numerical simulations.

带恒功率负载多电平Buck变换器逆解耦自适应滑模控制

针对带恒功率负载(CPL)多电平Buck变换器的强耦合问题及负阻抗特性引起的不稳定问题,提出一种逆解耦自适应滑模控制策略。建立带CPL多电平Buck变换器的非线性数学模型,基于逆系统方法证明系统的可逆性,并推导逆系统表达式,将模型线性化解耦为多个伪线性子系统,抵消负阻抗特性的影响。通过选取线性滑模面和指数趋近律以减弱滑模抖振,并将自适应机制引入到滑模控制中,进而为线性子系统分别设计自适应滑模控制器,进一步提高系统控制性能。基于李雅普诺夫理论对控制系统的稳定性和鲁棒性进行验证。与现有控制方法进行比较,仿真结果表明,所提控制策略具有更强的鲁棒性和优越性。最后,搭建原理样机进行实验对比,实验结果验证了所提控制策略的正确性和有效性。

快速反射镜自适应反演PID复合控制系统设计

为了提高复合轴系统的光束跟踪性能,必须考虑不可测扰动对快速反射镜系统的影响。针对可测量扰动,设计了自适应反演前馈控制算法,并由此得到启发,设计了用于抑制不可测量扰动的自适应反演PID(proportional-integral-derivative)控制系统,用自适应算法提高系统稳态精度以及对不同扰动的适应性,用PID控制器修正系统的误差信号改善系统动态性能。仿真结果表明,相较于PID控制算法,自适应反演PID复合控制系统的误差均方差值下降了34.76%,相较于自适应控制算法,自适应反演PID控制系统的误差均方差值下降了13.3%,自适应反演PID复合控制系统的稳态精度相比经典PID控制和自适应反演控制系统均得到了明显的提升,采用复合算法时上升时间相较自适应算法减少了48.9%,超调量相较经典PID算法减少了80.5%,系统动态性能得到较大改善。

基于非线性干扰观测器的磁悬浮球系统自适应反演滑模控制

为解决磁悬浮球系统易受模型内部参数变化和外界干扰的问题,提出了基于非线性干扰观测器的自适应反演滑模控制算法(NDO-ABSMC)。首先,建立磁悬浮球系统状态空间模型,然后设计非线性干扰观测器(NDOB),用来观测系统受到的外部干扰,经证明,该观测器对扰动的观测误差可以在有限时间内收敛。其次,为克服系统不确定性,设计了基于非线性干扰观测器的自适应反演滑模控制器;最后,对所提出的(NDO-ABSMC)进行了仿真验证。结果表明:与反演滑模控制算法(BSMC)相比,基于非线性干扰观测器的自适应反演滑模控制对扰动有明显的抑制作用,轨迹跟踪效果显著,优化了磁悬浮球系统的控制效果,增强了系统的鲁棒性。