Robust adaptive control of a quadrotor helicopter

This work presents a direct approximate-adaptive control, using CMAC nonlinear approximators, for an experimental prototype quadrotor helicopter. The method updates adaptive parameters, the CMAC weights, as to achieve both adaptation to unknown payloads and robustness to disturbances. Previously proposed weight-update methods, such as e-modification, provide robustness by simply limiting weight growth. In order to let the weights grow large enough to compensate unknown payloads, the proposed method relies on a set of alternate weights to guide the training. The alternate weights produce nearly the same output, but with values clustered closer to the average weight so that the output remains relatively smooth. This paper describes the design of a prototype helicopter suitable for testing the control method. In the experiment the new method stops weight drift during a shake test and adapts on-line to a significant added payload, whereas e-modification cannot do both.     

Robust adaptive control: a unified approach

A complete tutorial review of the entire field is presented, beginning with simple instability examples to identify the causes of nonrobust behavior in adaptive control. Some of the mathematical groundwork is presented, and the theory for the design and analysis of adaptive laws is developed. Commonly used adaptive controller structures are discussed, highlighting their particular robustness properties. Particular attention is paid to model reference, pole placement, and linear quadratic controller structures. Designs and analyses of model reference, pole placement, and linear quadratic controllers, based on combining the corresponding controller structures with the various robust adaptive laws, are presented. Suggestions for future research are given     

An adaptive decoupling control for three-axis gyro stabilized platform based on neural networks

In order to improve the tracking and stabilization performance of three-axis gyro stabilized platform, an adaptive decoupling control based on neural networks is developed. The dynamic model of three-axis GSP is developed based on traditional Newton–Euler method. The nonlinearity and coupling system is full-state-linearized using feedback linearization, and neural networks are used to compensate for the disturbances and uncertainties. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Comparative simulations and experiments results show the effectiveness of the proposed control approach compared with the conventional control.     

Robust adaptive tracking control of uncertain electrostatic micro-actuators with H-infinity performance

A novel adaptive robust tracking control scheme is proposed for a class of single-degree-of-freedom (1DOF) electrostatic micro-actuator systems in the presence of parasitics, parameter uncertainties and external disturbances. This method integrates the adaptive dynamic surface control and H-infinity control techniques. Based on this method, both the design procedure and the derived tracking controller itself are simplified, and the controller guarantees that the output tracking error satisfies the H-infinity tracking performance. In addition, the tracking accuracy can be adjusted by an appropriate choice of the design parameters of the controller. Simulation results show that prescribed transient output tracking performance can be achieved, and the closed-loop system exhibits good robustness to system uncertainties.     

Robust adaptive control of sawyer motors without current measurements

We address nonlinear robust adaptive dynamic output feedback of voltage-fed dual-axis linear stepper (Sawyer) motors using a detailed motor model with electrical dynamics and significant uncertainties and disturbances. A coordinate transformation is proposed to decouple the model into three third-order subsystems along with an appended fifth-order subsystem. The controller utilizes only position and velocity measurements in each axis and achieves practical stabilization of position tracking errors. Adaptations are utilized so as not to require any knowledge of electromechanical system parameters. The controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. The controller corrects for the yaw rotation to achieve synchrony of motor and platen teeth.     

Nonlinear adaptive torque control of electro-hydraulic load system with external active motion disturbance

This paper develops a high performance nonlinear adaptive control method for electro-hydraulic load simulator (EHLS). The tracking performance of EHLS is mainly affected by the following factors: actuator’s active motion disturbance, flow nonlinear and parametric uncertainties, etc. Most previous studies on EHLS pay too much attention on actuator’s active motion disturbance, while deemphasize the other two factors. This paper concerns EHLS as a motion loading system. Besides actuator’s motion disturbance, both the nonlinear characteristics and parametric uncertainties of the loading system are addressed by the present controller. First, the nonlinear model of EHLS is developed, and then a Lyapunov-based control algorithm augmented with parameters update law is developed using back-stepping design method. The stability of the developed control algorithm is proven via Lyapunov analysis. Both the co-simulation and experiment are performed to validate the effectiveness of the developed algorithm.     

Robust adaptive sliding-mode control using fuzzy modeling for aninverted-pendulum system

In this paper, a new robust adaptive control architecture is proposed for operation of an inverted-pendulum mechanical system. The architecture employs a fuzzy system to adaptively compensate for the plant nonlinearities and forces the inverted pendulum to track a prescribed reference model. When matching with the model occurs, the pendulum will be stabilized at an upright position and the cart should return to its zero position. The control scheme has a sliding control input to compensate for the modeling errors of the fuzzy system. The gain of the sliding input is automatically adjusted to a necessary level to ensure the stability of the overall system. Global asymptotic stability of the algorithm is established via Lyapunov's stability theorem. Experiments on an inverted-pendulum system are given to show the effectiveness of the proposed control structure     

Development of a three-axis active vibration isolator using zero-power control

This paper presents the development of an active 3-degree-of-freedom (DoF) vibration isolation system using zero-power magnetic suspension. The developed system is capable to suppress direct disturbances and isolate ground vibrations of the 3-DoF motions, associated with vertical translational and rotational modes. Two categories of control strategy for the actuators are proposed, i.e., local control and mode control. The latter method allows to overcome limitations of the poor performances for rotational modes exhibited by the former. A mathematical model of the system is derived and each DoF motion is treated separately for the control system. It is demonstrated analytically that the infinite stiffness to static direct disturbances can be generated and the resonance peak due to floor vibration can effectively be suppressed for the system. Moreover, the experiments have been carried out to measure the static and dynamic responses of the isolation table to direct disturbances, and transmissibility characteristic of the isolator from the floor. The results indicate good vibration isolation and attenuation performances, and show the efficacy of the developed isolator for industrialization.     

Robust feedback linearization using an adaptive PD regulator for a sensorless control of a throttle valve

With classic gasoline injection systems, engine efficiency and emissions are affected by the control of the throttle plate, in particular its angular position. Depending on the current engine load, the angular position must track a trajectory as determined by the accelerator. This paper considers two problems. The first one is the design of a state observer. A velocity estimator is proposed based on measurements of current. If the effect of the noise is minimized, the angular position can be achieved through a cascade structure between a particular velocity estimator and an inversion of the electrical system. This approach allows us to avoid a more complex structure for the observer, and yields an acceptable performance and the elimination of bulky position sensor systems. The elimination of the position sensor system simplifies the production system of the valve. The second problem, the robustness of the tracking, is addressed using a minimum variance control approach. This paper presents feasible real-time self-tuning of an approximated proportional derivative (PD) regulator, which compensates for the tracking error caused by inexact feedback linearization. It is interesting to note that the structure of the approximated PD regulator is similar to the velocity estimator. Robustness in the proposed loop control is achieved. Measured results on a real experimental setup with hardware-in-the-loop are shown.     

Time delay control with state feedback for azimuth motion of thefrictionless positioning device

A time delay controller with state feedback is proposed for azimuth motion control of the frictionless positioning device which is subject to the variations of inertia in the presence of measurement noise. The time delay controller, which is combined with a low-pass filter to attenuate the effect of measurement noise, ensures the asymptotic stability of the closed-loop system. It is found that the low-pass filter tends to increase the robustness in the design of the time delay controller, as well as the gain and phase margins of the closed-loop system. Numerical and experimental results support that the proposed controller guarantees a good tracking performance, irrespective of the variation of inertia and the presence of measurement noise     

PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage

This paper presents a new scheme of adaptive sliding mode control (ASMC) for a piezoelectric ultrasonic motor driven X–Y stage to meet the demand of precision motion tracking while addressing the problems of unknown nonlinear friction and model uncertainties. The system model with Coulomb friction and unilateral coupling effect is first investigated. Then the controller is designed with adaptive laws synthesized to obtain the unknown model parameters for handling parametric uncertainties and offsetting friction force. The robust control term acts as a high gain feedback control to make the output track the desired trajectory fast for guaranteed robust performance. Based on a PID-type sliding mode, the control scheme has a simple structure to be implemented and the control parameters can be easily tuned. Theoretical stability analysis of the proposed novel ASMC is accomplished using a Lyapunov framework. Furthermore, the proposed control scheme is applied to an X–Y stage and the results prove that the proposed control method is effective in achieving excellent tracking performance.     

Robust motion/force control of uncertain holonomic/nonholonomic mechanical systems

In this paper, robust control strategies are presented systematically for both holonomic mechanical systems and a large class of nonholonomic mechanical systems in the presence of uncertainties and disturbances. First, robust control strategies are presented for both kinds of systems using the bounds of system parameters, respectively. Then, adaptive robust control strategies are presented by tuning the parameter estimates online. Proportional plus integral feedback control is used for force control for the benefit of real-time implementation. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance while the constraint force remains bounded.     

Robust cyclic adaptive beamforming using a compensation method

This paper deals with the problem of robust adaptive array beamforming using signal cyclostationarity. The constrained cyclic adaptive beamforming (C-CAB) algorithm presented by Wu and Wong (1996) [6] has been shown to be effective in performing adaptive beamforming without requiring the direction vector or the waveform of the desired signal. However, this algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequency of the desired signal. In this paper, we first evaluate the performance degradation of the C-CAB algorithm in the presence of cycle frequency error (CFE). A novel compensation method in conjunction with the subspace projection is then proposed to tackle the problem due to CFE. We reconstruct the required cyclic conjugate correlation matrix by using a compensation matrix to cope with the deterioration of its dominant singular value when CFE exists. Finally, several simulation examples are provided to show the effectiveness of the proposed algorithm.     

具有自适应可调误差半径的鲁棒波束赋形算法

传统的自适应波束形成器对各类型的阵列误差较为敏感尤其是在较大的波达方向(Direction of Arrival,DOA)误差存在的情况下,阵列的输出信干噪比严重下降.为了解决这个问题,文中提出了一种新的具有自适应可调误差半径的鲁棒波束形成器.每一步迭代都是以经典的鲁棒Capon波束形成器为基础,且使用的误差不确定度都是依据子空间投影定理推导出的一个二次约束二次规划问题的最优解.由于估计出的导向矢量不确定度均小于传统自适应波束形成器中使用的误差量,因此,阵列的输出性能得以提高.此外,为了能够扩展算法的适用性,引入了可变椭圆不确定集来同时处理多重误差因素.最终的实验结果证明了算法的正确性和有效性.     

Robust depth sensing with adaptive structured light illumination

Automatic focus and exposure are the key components in digital cameras nowadays, which jointly play an essential role for capturing a high quality image/video. In this paper, we make an attempt to address these two challenging issues for future depth cameras. Relying on a programmable projector, we establish a structured light system for depth sensing with focus and exposure adaptation. The basic idea is to change current illumination pattern and intensity locally according to the prior depth information. Consequently, multiple object surfaces appearing at different depths in the scene can receive proper illumination respectively. In this way, more flexible and robust depth sensing can be achieved in comparison with fixed illumination, especially at near depth.     

一种不依赖状态估计的自适应输出反馈控制方法

研究了一种不依赖状态估计的自适应输出反馈控制方法。首先引入伪控制信号使系统反馈线性化，然后设计一个线性动态补偿器和在线神经网络，自适应消除不确定性和建模所引起的误差。对一含有末建模动态的非线性系统的仿真结果表明，该控制方法能够消除系统的稳态误差，提高系统动态性能，并且具有较好的鲁棒性。     

Robust regression of scattered data with adaptive spline-wavelets.

A coarse-to-fine data fitting algorithm for irregularly spaced data based on boundary-adapted adaptive tensor-product semi-orthogonal spline-wavelets has been proposed in Casta?o and Kunoth, 2003. This method has been extended in Casta?o and Kunoth, 2005 to include regularization in terms of Sobolev and Besov norms. In this paper, we develop within this least-squares approach some statistical robust estimators to handle outliers in the data. Our wavelet scheme yields a numerically fast and reliable way to detect outliers.     

Robust servosystem design with two degrees of freedom and itsapplication to novel motion control of robot manipulators

A novel robust servosystem design method based on the two-degree-of-freedom (TDOF) controller and its application to advanced motion control for a robot manipulator is proposed. This servosystem is derived from the simple parametrization. The command input response and the closed loop characteristics can be specified independently by using two parameters which belong to the ring of stable and proper rational functions. The sensitivity and the complementary sensitivity functions can be determined straightforwardly through the optimization of the two design parameters. The control performance of the servosystem has been demonstrated. A completely decentralized joint control system for multiaxis robut manipulators has been realized. In particular, various kinds of robot motion controls, such as compliance, force, and hybrid controls, are realized in a unified way based on the robust position control. This servosystem has been implemented using DSP