Cluster unmanned aerial vehicles (UAVs) are widely demanded. To achieve high rate and large capacity communication with cluster UAVs, one of the key but still challenge task is to perform multi-target acquisition, pointing and tracking (APT) under complex airborne environment. To solve this problem, this paper gives one composite axis APT system for multi-target laser communication with cluster UAVs. The APT system consists of a gimbal mirror and piezoelectric fast steering mirrors (FSMs), which can achieve independent and synchronous control of multiple optical axes. The cascade control scheme is designed for the gimbal mirror and the H-infinite controller is designed for the FSM. To further improve the control accuracy, the hysteresis compensator based on least square support vector machines (LS-SVM) is proposed. The pruning error minimization method of LS-SVM is applied to reduce the computational cost. The simulation studies validate the control performance of the multi-target APT system. Finally, the experimental prototype is developed. The experimental results further validate the effectiveness of the proposed multi-target APT system.

A dual-drive H-gantry is commonly used in many industrial processes to meet the requirement of high-precision Cartesian motion. Unlike the rigid-linked gantry stage, the flexure-linked counterpart allows a small degree of rotation of the crossarm to prevent possible damages. However, by this design, the chattering of control signals and inappropriate stiffness of the flexure may induce the resonant modes of the gantry. Hence, to maintain the precision tracking of the midpoint position and the orientation of the gantry, as well as to minimize the vibration on the end effector, we seek the most suitable flexure stiffness and controller parameters by formulating a constrained linear-quadratic optimization problem. Since such a mechatronic design problem is not solvable via standard linear-quadratic regulator formulas, we convert it to a constrained projection gradient-based optimization problem, which can be efficiently solved by direct computation of projection gradient and line search of optimal step length. A fast convergence of parameters is achieved after first several iterations. Through a series of comparative experiments, the effectiveness of the proposed method is validated.

Performance of traditional model-based control relies upon accurate modeling. In motion control of flexible systems, it is desirable to use the reduced-order model for ease of trajectory planning and pole placement, but its performance is constrained by modeling inaccuracies due to the existence of friction and multiple flexible modes. To improve the tracking performance, we have developed a data-based method for iterative tuning of the parameters in the reduced-order inverse model within a three-degree-of-freedom composite control structure. The proposed method solely makes use of the input-output data obtained during closed-loop experiments to fine-tune the inverse system model, and accurate system modeling is not required. Unbiasedness of the cost function gradient estimation is proven under reasonable assumptions of stochastic properties of the perturbations. Simulation and experiments are conducted to further illustrate the proposed method and show its practical appeals in industrial applications.

In this work, the design of a novel the flexure-linked dual-drive H-gantry is firstly introduced. Compared to conventional stacked X-Y tables, the advantages of this gantry are on decoupled X-Y actuation, better mechanical reliability, larger driving force, and shorter response time. However, after deriving its reduced-order dynamical model, it is found that the precision of the end effector is significantly affected by the position dependent torque caused by the inter-parallel-axes driving forces on the fixed inertia frame and coupling forces from the pair of flexures. These form barriers that limit precision positioning and tracking performance over a large workspace. Thus, in the following part, a robust integral of the sign of the error (RISE) control with novel jerk adaptation is proposed on top of the standard PID and feedforward scheme. Compared with some prior RISE schemes with gain adaptation, the proposed scheme yields bounded robust gain in the presence of noisy velocity estimation. Real-time experiments on the actual test-bed indicate that both improvement of motion precision and prevention of resonant mode excitation over a large workspace are successfully achieved in the proposed scheme.

Accurate modeling and identification of the piezoelectric actuators (PAs) are increasingly demanded for intelligent micro-nano manufacturing to improve the accuracy of positioning and scanning. In this paper, one coupled fractional-order creep and hysteresis model is established only using 5 parameters. Then, the properties of the coupled fractional-order creep and hysteresis are investigated under sinusoidal and step inputs. The identification approaches are thus proposed by leveraging the special characteristics of the proposed fractional-order model. Simulation and experimental studies are carried out to validate the effectiveness of the proposed fractional-order creep and Bouc-Wen hysteresis model. Additionally, model-based inversion feedforward is implemented to validate the parameter identification. The experimental results demonstrate the effectiveness of the modeling and parameter identification approaches.