Spatial curvilinear path following control of underactuated AUV with multiple uncertainties

This paper investigates the problem of spatial curvilinear path following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties. Firstly, in order to design the appropriate controller, path following error dynamics model is constructed in a moving Serret–Frenet frame, and the five degrees of freedom (DOFs) dynamic model with multiple uncertainties is established. Secondly, the proposed control law is separated into kinematic controller and dynamic controller via back-stepping technique. In the case of kinematic controller, to overcome the drawback of dependence on the accurate vehicle model that are present in a number of path following control strategies described in the literature, the unknown side-slip angular velocity and attack angular velocity are treated as uncertainties. Whereas in the case of dynamic controller, the model parameters perturbations, unknown external environmental disturbances and the nonlinear hydrodynamic damping terms are treated as lumped uncertainties. Both kinematic and dynamic uncertainties are estimated and compensated by designed reduced-order linear extended state observes (LESOs). Thirdly, feedback linearization (FL) based control law is implemented for the control model using the estimates generated by reduced-order LESOs. For handling the problem of computational complexity inherent in the conventional back-stepping method, nonlinear tracking differentiators (NTDs) are applied to construct derivatives of the virtual control commands. Finally, the closed loop stability for the overall system is established. Simulation and comparative analysis demonstrate that the proposed controller exhibits enhanced performance in the presence of internal parameter variations, external unknown disturbances, unmodeled nonlinear damping terms, and measurement noises.     

Robust tracking control of triaxial angular velocity sensors using adaptive sliding mode approach

This paper presents a robust tracking control strategy using an adaptive sliding mode approach for MEMS triaxial angular sensor device that is able to detect rotation in three orthogonal axes, using a single vibrating mass. An adaptive sliding mode controller with proportional and integral sliding surface is developed and the stability of the closed-loop system can be guaranteed with the proposed adaptive sliding mode control strategy. The proposed adaptive sliding mode controller updates estimates of all stiffness errors, damping, and input rotation parameters in real time, removing the need for any offline calibration stages. To enable all unknown parameter estimates to converge to their true values, the necessary model trajectory is shown to be a three-dimensional Lissajous pattern. The numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive sliding mode control scheme.     

A modified model reference adaptive control with application to MEMS gyroscope

Micro electro-mechanical systems (MEMS) are increasingly being used in measurement and control problems due to their small size, low cost, and low power consumption. The vibrating gyroscope is a MEMS device that will have a significant impact on stability control systems in the transportation industry. This paper investigates the application of a modified model reference adaptive control for MEMS gyroscope. Using this adaptive control algorithm, an estimation of the angular velocity and the damping and stiffness coefficients in real time is easily computable. Changing the conventional model reference input makes it feasible to utilize a low pass filter to remove unwanted oscillations caused by high adaptation gain. This new adaptive control technique enables quick compensation for large changes in the system dynamics, providing consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances. The asymptotic stability of the mentioned adaptive controller is guaranteed using the Lyapunov direct method. Numerical simulation is presented to verify the effectiveness of the proposed control scheme.     

非完整移动机器人的自适应全局轨迹跟踪控制

针对含有未知参数的移动机器人运动学模型,利用自适应反演控制技术,讨论了两后轮角速度为控制输入的非完整移动机器人轨迹跟踪问题,构造了具有全局渐近稳定性的自适应轨迹跟踪控制器,该方法将系统分解为低阶子系统来处理,利用中间虚拟控制量和部分Lyapunov函数简化了控制器的设计并具有直观的稳定性分析。仿真结果验证了所设计控制器的有效性和正确性。     

Control design for the SISO system with the unknown order and the unknown relative degree

For the uncertain system whose order, relative degree and parameters are unknown in the control design, new research is still in need on the parameter tuning and close-loop stability. During the last 10 years, much progress is made in the application and theory research of the active disturbance rejection control (ADRC) for the uncertain system. In this study, the necessary and sufficient conditions are established for building the ADRC for the minimum-phase system and the open-loop stable system when the plant parameters, orders and relative degrees are unknown, the corresponding ideal dynamics are analyzed, and the theoretical results are verified by the simulations. Considering the wide application and the long history of the PID/PI controller, a method is given to design ADRC quickly based on the existing (generalized or conventional) PID/PI controller. A plenty of simulations are made to illustrate this PID/PI-based design method and the corresponding close-loop performances. The simulation examples include the minimum/nonminimum-phase plants, the stable/integrating plants, the high/low-order plant, and the plants with time delays. Such plants are from a wider scope than the theoretical result, and representative of many kinds of the industrial processes. That leads to a new way to simplify the ADRC design via absorbing the engineering experience in designing the PID/PI controller.     

Multilevel adaptive control of nonlinear interconnected systems

This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks.     

A novel adaptive sliding mode control with application to MEMS gyroscope

This paper presents a new adaptive sliding mode controller for MEMS gyroscope; an adaptive tracking controller with a proportional and integral sliding surface is proposed. The adaptive sliding mode control algorithm can estimate the angular velocity and the damping and stiffness coefficients in real time. A proportional and integral sliding surface, instead of a conventional sliding surface is adopted. An adaptive sliding mode controller that incorporates both matched and unmatched uncertainties and disturbances is derived and the stability of the closed-loop system is established. The numerical simulation is presented to verify the effectiveness of the proposed control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as the consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances.     

Sliding mode control of a simulated MEMS gyroscope

The microelectromechanical systems (MEMS) are penetrating more and more into measurement and control problems because of their small size, low cost, and low power consumption. The vibrating gyroscope is one of those MEMS devices that will have a significant impact on the stability control systems in transportation industry. This paper studies the design and control of a vibrating gyroscope. The device has been constructed in a Pro-E environment and its model has been simulated in the finite-element domain in order to approximate its dynamic characteristics with a lumped model. A model reference adaptive feedback controller and the sliding mode controller have been considered to guarantee the stability of the device. It is shown that the sliding mode controller of the vibrating proof mass results in a better estimate of the unknown angular velocity than that of the model reference adaptive feedback controller.     

利用自适应卡尔曼滤波实现光电跟踪中的复合控制

为了在光电跟踪控制系统中实现复合控制以提高跟踪精度,构建了基于模型自适应卡尔曼滤波算法的复合控制结构。首先,利用跟踪脱靶量数据和仪器位置数据合成目标角位置数据;然后,利用模型自适应卡尔曼滤波算法对目标角位置数据进行滤波估计以获得目标角速度信息;最后,将目标角速度信息前馈到速度回路,从而构成复合控制系统。实验结果表明:采用复合控制结构后,目标跟踪精度提高了50%。基于模型自适应卡尔曼滤波算法的复合控制技术能够在保持原反馈控制系统稳定性的条件下提高跟踪精度。     

Chaos synchronization of gyroscopes using an adaptive robust finite-time controller

The problem of robust finite-time chaos synchronization between two chaotic nonlinear gyroscopes with model uncertainties, external disturbances and unknown parameters is investigated. Appropriate adaptive laws are derived to tackle the unknown parameters. Based on the adaptive laws and the finite-time control technique, suitable adaptive control laws are designed to ensure the stability of the resulting synchronization error system in a given finite time. Numerical simulations and comparative examples are presented to illustrate the applicability and usefulness of the proposed finite-time control strategy.     

基于模糊神经网络的精密角度定位PID控制

针对精密角度定位系统存在非线性、时变性,传统PID控制难以获得理想控制效果的问题,提出一种基于模糊神经网络的PID控制方法,将模糊控制、神经网络与PID控制相结合,采用3层前向网络、动态BP算法,利用神经网络的自学习和自适应能力,实时调整网络的权值,改变PID控制器的控制参数,整定出一组适用于控制对象的kp、ki、kd参数,实现精密角度定位PID控制的自适应和智能化。实验结果表明,采用BP神经网络整定的PID控制较传统的PID控制,控制性能有较大的提高,能有效提高定位精度,缩短定位时间。     

Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation

This paper addresses the high performance motion control of hydraulic actuators with parametric uncertainties, unmodeled disturbances and unknown valve dead-zone. By constructing a smooth dead-zone inverse, a robust adaptive controller is proposed via backstepping method, in which adaptive law is synthesized to deal with parametric uncertainties and a continuous nonlinear robust control law to suppress unmodeled disturbances. Since the unknown dead-zone parameters can be estimated by adaptive law and then the effect of dead-zone can be compensated effectively via inverse operation, improved tracking performance can be expected. In addition, the disturbance upper bounds can also be updated online by adaptive laws, which increases the controller operability in practice. The Lyapunov based stability analysis shows that excellent asymptotic output tracking with zero steady-state error can be achieved by the developed controller even in the presence of unmodeled disturbance and unknown valve dead-zone. Finally, the proposed control strategy is experimentally tested on a servovalve controlled hydraulic actuation system subjected to an artificial valve dead-zone. Comparative experimental results are obtained to illustrate the effectiveness of the proposed control scheme.     

Robust time-delay control of a reclaimer

In this paper, a robust time delay control for a reclaimer is investigated. Supplying the same amount of raw material throughout the reclaimation process, from the raw yard to a sinter plant, is important to keep the quality of the molten steel uniform. As the parameter values of the reclaimer are not available, the boom rotational dynamics. is modeled as a second order differential equation with unknown coefficients. The unknown parameters in the nominal model are estimated using recursive estimation method. Another important factor in the control problem of a reclaimer is the large time delay in output measurement. Assuming a multiplicative uncertainty, that accounts for both the unstructured uncertainty neglected in the modeling and the structured uncertainty in the parameter estimation, a robust Smith predictor is designed. A robust stability criterion for the multiplicative uncertainty is derived. Following the work of Goodwinet al. (1992), a quantifying procedure of the multiplicative uncertainty bound, through experiments, is described. Experimental and simulation results are provided.     

Dynamic response-based characterization of ring-based vibratory angular rate sensors

Dynamic response behaviour of a rotating ring is investigated in order to better understand the achievable performance improvements as well as system limitations. For this purpose, the governing equations that represent the transverse as well as the tangential in-plane motion of a rotating ring are derived via the Hamilton’s principle. These equations are then discretized to represent a two-degree-of-freedom time-varying gyroscopic system. The asymmetry effects are considered important and are included by considering mass mismatch in the system mass matrix. In order to predict dynamic behaviour of a ring system subjected to external excitation and body rotation, time and frequency response analyses are performed. The natural frequency variations due to the gyroscopic coupling presented in the system are first characterized for varying input angular rates. The effects of system parameters such as damping and mass mismatch on the sensor sensitivity and operating range are quantified via suitable time and frequency response analyses.     

组合动力验证机助推段纵向控制器设计

针对飞行器的飞行特点和自身的气动结构,建立复杂的非线性数学模型,给出静稳定性和模态特性的分析.为解决高超声速飞行器在助推段因纵向静不稳度大而导致的常规控制律鲁棒性不足的问题,设计基于角速率指令内回路的纵向控制律,并从时域、频域、鲁棒性三方面进行分析,得出指令内回路适用于助推段纵向控制的结论.     

不确定性双臂空间机器人自适应模糊优化控制

考虑空间环境存在惯性参数未知及外部扰动等不确定性因素,针对自由漂浮双臂空间机器人(DFFSR)关节角运动控制问题,提出了一种自适应模糊优化控制方法。首先,基于系统动量守恒关系及Lagrange方法,建立DFFSR系统关节空间的动力学方程;而后,考虑系统惯性参数未知导致惯性矩阵无法求解问题,利用模糊控制理论的万能逼近特性,通过在线参数辨识建立系统自适应模糊模型;由此,同时考虑系统存在外界扰动以及输出力矩的优化问题,基于SDRE优化控制理论,设计一种自适应模糊优化控制方法,实现了DFFSR系统关节角的精确运动控制。一组对比仿真验证了所提控制方法的可靠性。     

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods.     

Development of an adaptive radial basis function neural network estimator-based continuous sliding mode control for uncertain nonlinear systems

In this paper an adaptive neural network (NN)-based nonlinear controller is proposed for trajectory tracking of uncertain nonlinear systems. The adopted control algorithm combines a continuous second-order sliding mode control (CSOSMC), the radial basis function neural network (RBFNN) and the adaptive control methodology. First, a second-order sliding mode control scheme (SOSMC), which is published recently in literature for linear uncertain systems, is extended for nonlinear uncertain systems. Second, an adaptive radial basis function neural network estimator-based continuous second order sliding mode control algorithm (CSOSMC-ANNE) is adopted. In CSOSMC-ANNE control methodology, a radial basis function neural network with adaptive parameters is exploited to approximate the unknown system parameters and improve performance against perturbations. Also, the discontinuous switching control of SOSMC is supplanted with a smooth continuous control action to completely eliminate the chattering phenomenon. The convergence and global stability of the closed-loop system are proved using Lyapunov stability method. Numerical computer simulations, with dynamical model of the nonlinear inverted pendulum system, are presented to demonstrate the effectiveness and advantages of the presented control scheme.     

嵌入式时栅角位移传感器短周期误差分析与补偿

为提高嵌入式时栅角位移传感器测量精度,从传感信号形成机理出发,对短周期误差成因进行了详细分析。通过对绕组等效分析和激励信号分析,确定了短周期误差的主要特性为一次和二次误差,一次误差来源为零点残余误差和直流分量误差,二次误差来源为激励信号正交误差。针对短周期误差补偿,提出了基于超限学习机的误差补偿方法,通过对测量值与真实值样本的训练得到模型最优参数,根据模型参数建立短周期误差模型,利用所得误差模型实现对短周期误差的补偿。实验结果表明,短周期误差分析结果与传感器实际误差特性一致,采用该补偿方法传感器短周期误差大幅度降低,降低了约96%。对比和重复性实验表明,该方法与谐波补偿法相比精度提高了约1倍,误差补偿效果更优,同时方法具有良好的测量稳定性,对提高嵌入式时栅角位移传感器的测量精度具有重要的理论和现实意义。     

Adaptive control for spacecraft rendezvous subject to actuator faults and saturations

An adaptive saturated fault-tolerant controller is proposed for a spacecraft rendezvous maneuver with a cooperative target spacecraft. The six-degree-of-freedom (6-DOF) relative dynamics subject to unknown inertial parameters, external disturbances, actuator faults and saturations are formulated in the pursuer's body-fixed frame. To design controller satisfying asymmetric magnitude constraints, a modified smooth hyperbolic tangent function is applied to approximate the non-differentiable saturation function. Based on the augmented system technique, an adaptive fault-tolerant saturated controller is designed for the pursuer by using a Nussbaum function matrix compensating for the nonlinear term arising from the input saturations. In addition, a Levant differentiator is introduced to obtain the derivative of the virtual control in finite time that avoids the complicated calculation. It is proved via Lyapunov stability theory that all the signals in the closed-loop augmented system are bounded and the relative errors asymptotically converge to zero. Numerical simulations are performed to illustrate effectiveness of the proposed controller.