Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

A 3-DOF (X–Y–θ_Z) planar flexure-based mechanism is designed and monolithically manufactured using Wire Electro-Discharge Machining (WEDM) technology. The compact flexure-based mechanism is directly driven by three piezoelectric actuators (PZTs) through decoupling mechanisms. The orthogonal configuration in the x and y directions can guarantee the decoupling translational motion in these axes. The rotational motion and translational displacement in the x direction can be decoupled by controlling the piezoelectric actuators in the x axis with the same displacement values in same and opposite motion directions, respectively. The static and dynamic models of the developed flexure-based mechanism have been developed based on the pseudo-rigid-body model methodology. The mechanical design optimization is conducted to improve the static and dynamic characteristics of the flexure-based mechanism. Finite Element Analyses (FEA) are also carried out to verify the established models and optimization results. A novel hybrid feedforward/feedback controller has been provided to eliminate/reduce the nonlinear hysteresis and external disturbance of the flexure-based mechanism. Experimental testing has been performed to examine the dynamic performance of the developed flexure-based mechanism.     

Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Coordinate independent adaptive attitude tracking control design for spacecraft robust to time-varying system uncertainties

In this paper, we consider the adaptive attitude control of spacecraft with time-varying inertial properties. We use a coordinate independent approach for the purpose of designing the control and estimation laws in terms of the rotation matrices representing the spacecraft body frame and reference tracking signals. This method helps to overcome the difficulties regarding the attitude representation on SO(3) such as ambiguities associated with quaternion representation and inherent singularities inside Euler parameters. We model the time variations in inertial parameters in two different ways, and design adaptive control schemes for each case. As the first uncertain dynamic model, we consider a setting of spacecraft with multiple moving appendages, and based on this model, design an adaptive control scheme with three different versions, where Frobenious norm is used in measuring the deviation of the estimated inertia tensors from their actual values. The proposed adaptive control scheme is later extended for the more direct model where the inertia tensor of the spacecraft has a nonlinear relation with the norm of the input moment. Further, we derive the allowable sets of initial conditions to ensure the convergence of the tracking error. Simulation results are provided to illustrate the effectiveness of our proposed approach.     

Contribution to the indirect decentralized adaptive control of manipulation robots

In this paper, efficient approaches to the synthesis of indirect decentralized adaptive control for manipulation robots are presented. The first part of control synthesis consists of the estimation of unknown dynamic robot parameters using the methods of recursive identification and fast dynamic as well as identification models in a symbolic form. The second part of synthesis includes the self-tuning control strategy which is a basis for adaptive control synthesis according to the estimates of the unknown dynamic parameters. Using the theory of decentralized systems, a new robust algorithm for adaptive control with the ability of adaptation in the feedforward or feedback loop are proposed. A complete stability and convergence analysis is presented. A special part of the paper represents an analysis of practical implementation of the proposed control algorithms on modern microprocessor-based robot controllers. Based on this analysis, an efficient application of indirect adaptive algorithms in real time with high-quality system performance is shown. Adaptive algorithms are verified through simulation of trajectory tracking for an industrial robot with unknown dynamic parameters of payload.     

基于声波操纵的微小物体运动建模与控制

采用声波操纵克拉尼平板上的微小物体, 在精准医学、液滴和颗粒的工业控制等方面有着广阔的应用前景. 传统声波操纵认为在运动过程中, 声波对微粒的影响是无序的, 而近年来, 研究得出声振动是有序的, 但缺乏精确、有效的建模手段, 限制其应用. 针对该问题, 本文提出了结合Faster R-CNN算法与局部加权回归(LOESS)算法的方法对声波场进行建模. 采用图像识别技术辨识微粒在克拉尼平板上的位置, 计算在某一固定声波频率下微小粒子在克拉尼平板不同位置上的位移. 在积累大量位移数据后, 基于LOESS算法, 建立平板上的完整声波位移模型,分析声波力场如何在平面上对微小物体的运动施加影响, 并建立仿真模型, 进行克拉尼平板上微粒操纵的仿真实验. 最后, 本文将基于所搭建的声波操纵平台, 对易碎的速溶咖啡颗粒进行控制, 通过与仿真实验相对比, 验证了建模与控制方法的可行性, 证明该模型可实现微小粒子的运动控制.     

Robust adaptive tracking control for servo mechanisms with continuous friction compensation

In this paper, a robust adaptive tracking control scheme is developed for servo mechanisms with nonlinear friction dynamics. A continuously differentiable friction model is used to capture the friction behaviors (e.g. Stribeck effect, Coulombic friction and Viscous friction). The robust integral of the sign of the error (RISE) feedback term is employed to design an innovative adaptive controller to compensate nonlinear friction and bounded disturbances. To reduce the effect of noise pollution, the desired trajectory is employed to replace the output signal in controller design. The developed adaptive controller can guarantee the asymptotic tracking performance for nonlinear servo mechanisms in the presence of nonlinear friction and bounded disturbances. Comparative experimental results are used to validate the effectiveness of the developed control algorithm.     

An adaptive neural network approach to the tracking control of micro aerial vehicles in constrained space

This paper presents an adaptive neural network approach to the trajectory tracking control of micro aerial vehicles especially when they are flying in a limited indoor area. Differing from conventional controllers, the proposed controller employs the outer position loop to directly generate angular velocity commands in the presence of unknown aerodynamics and disturbances and then the fast inner loop to handle the angular rate control. Adaptive neural networks are deployed to estimate all the uncertain factors with the adaptation law derived from the Lyapunov function. To achieve a real-time performance, a norm estimation approach of ideal weights is designed to achieve a high bandwidth and lighten the burden of computation burden. Meanwhile, a barrier Lyapunov function is introduced to guarantee the constraint of vehicle positions as well as the validity of the neural network estimation. Simulations and practical flight tests are conducted to verify the feasibility and effectiveness of the proposed control strategy.     

A modified direct adaptive robust motion trajectory tracking controller of a pneumatic system

In this study, we developed and tested a high-precision motion trajectory tracking controller of a pneumatic cylinder driven by four costless on/off solenoid valves rather than by a proportional directional control valve. The relationship between the pulse width modulation （PWM） of a signal＇s duty cycle and control law was determined experimentally, and a mathematical model of the whole system established. Owing to unknown disturbances and unmodeled dynamics, there are considerable uncertain nonlinearities and parametric uncertainties in this pneumatic system. A modified direct adaptive robust controller （DARC） was constructed to cope with these issues. The controller employs a gradient type adaptation law based on discontinuous projection mapping to guarantee that estimated unknown model parameters stay within a known bounded region, and uses a deterministic robust control strategy to weaken the effects of unmodeled dynamics, disturbances, and parameter estimation errors. By using discontinuous projection mapping, the parameter adaptation law and the robust control law can be synthesized separately. A recursive backstepping technology is applied to account for unmatched model uncertainties. Kalman filters were designed sepa- rately to estimate the motion states and the derivative of the intermediate control law in synthesizing the deterministic robust control law. Experimental results illustrate the effectiveness of the proposed controller.     

Recursive filtering adaptive fault‐tolerant tracking control for uncertain switched multivariable nonlinear systems

This article synthesizes a recursive filtering adaptive fault‐tolerant tracking control method for uncertain switched multivariable nonlinear systems. The multivariable nonlinear systems under consideration have both matched and mismatched uncertainties, which satisfy the semiglobal Lipschitz condition. A piecewise constant adaptive law generates adaptive parameters by solving the error dynamics with the neglection of unknowns, and the recursive least squares is employed to minimize the residual error by categorizing the total uncertainty estimates into matched and mismatched components. A filtering control law is designed to compensate the actuator faults and nonlinear uncertainties such that a good tracking performance is delivered with guaranteed robustness. The matched component is canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is performed to eliminate the effect of the mismatched component on the output. By exploiting the average dwell time principle, the error bounds are derived for the states and control inputs compared with the virtual reference system which defines the best performance that can be achieved by the closed‐loop system. Both numerical and practical examples are provided to illustrate the effectiveness of the proposed switching recursive filtering adaptive fault‐tolerant tracking control architecture, comparisons with model reference adaptive control are also carried out.     

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.