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In this paper, a new composite controller (feedforward + feedback) is proposed for the trajectory tracking control of a piezo-driven bridge displacement amplifier. A hysteresis model considering dynamic effects is established based on the modified Bouc–Wen (MBW) model, which can describe the asymmetry and frequency-dependence behaviors. The effectiveness of the modified model is verified by the experimental comparison. A feedforward controller is designed to compensate for hysteresis nonlinearity based on the inverse multiplicative structure of the modified model. A feedback controller with the Kalman observer is designed based on a modified model predictive control (MMPC). The proportional term and integral term of feedback error are introduced into the MPC control law to improve the response speed and reduce the steady-state error. The proposed MBW + MMPC is compared with MBW + proportional–integral–derivative (PID), and MBW + MPC. The experimental tracking results of continuously differentiable signals and non-differentiable signals verify MBW + MMPC feasibility and show that it can improve tracking performance. [ABSTRACT FROM AUTHOR]

The robust control issues in trajectory tracking of an unmanned aerial robot (UAR) are challenging tasks due to strong parametric uncertainties, large nonlinearities, and high couplings in robot dynamics. This paper investigates the dynamical modelling and robust control of an aerial robot using a hexarotor with a 2-degrees-of-freedom (DOF) manipulator in a complex aerial environment. Firstly, the kinematic model and dynamic model of the aerial robot are developed by the Euler-Lagrange method. Afterwards, a linear active disturbance rejection control is designed for the robot to achieve a high-accuracy trajectory tracking goal under heavy lumped disturbances. In this control scheme, the modelling uncertainties and external disturbances are estimated by a linear extended state observer, and the high tracking precision is guaranteed by a proportion-differentiation (PD) feedback control law. Meanwhile, an artificial intelligence algorithm is applied to adjust the control parameters and ensure that the state variables of the robot converge to the references smoothly. Furthermore, it requires no detailed knowledge of the bounds on unknown dynamical parameters. Lastly, numerical simulations and experiments validate the efficiency and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

This article presents an integrated approach for the parameter identification of a small-scale unmanned helicopter. With the flight experiment data collection and preprocessing, a hybrid identified algorithm combining the improved artificial bee colony algorithm and prediction error method is proposed to obtain the unknown dynamical parameters of the linear model. The proposed algorithm is valid to use thanks to an adaptive search equation, a novel probability-scaling method, and a chaotic operator and has a good performance in search speed and quality. Afterwards, we design a wind tunnel test to modify the main rotor time constant of the identified model. The identified accuracy and feasibility of the proposed approach are verified by making a time-domain comparison with three other algorithms. Results show that the dynamical characteristics of the helicopter can be determined accurately by the identified model. And the proposed approach is propitious to enhance the reliability and availability of the identified dynamical model. [ABSTRACT FROM AUTHOR]

Abstract The vibration isolation system is crucial to high-precision space systems. This paper studies dynamics and control of a six-axis vibration isolator via a flexible Stewart platform. The parasitic stiffness induced by flexible joints is considered in dynamics modeling and compensated in control for the first time. The explicit dynamic equations are established based on the pseudo-rigid-body model and the principle of virtual power. After validation by ADAMS/Flex and the finite element method, the dynamic equations are used for designing a decoupled controller. The control force is synthesized based on the leg's force and position feedback. The impact of bending and torsional stiffness of flexible joints is compensated and the MIMO system is consequently decoupled in modal space, making parameter design and performance implementation more convenient and effective. The identical sub-controller for every SISO system makes the six-DOF isolator achieve the capability of vibration isolation simultaneously for the six modes. With a proportional plus integral compensator as the sub-controller, the vibration isolation bandwidth and active damping can be regulated separately. [ABSTRACT FROM AUTHOR]

The forward kinematics is the basis of the design and control of the parallel robots. This paper aims to provide an efficient solution to the forward kinematics of a class of six-degrees-of-freedom parallel robots for real-time applications. With a unit dual quaternion used as the generalized coordinates of the robot system, the forward kinematic equations are derived to be a set of quadratic ones. An efficient algorithm is proposed to get the actual solution to them. The convergence and singularity problems of the new algorithm have been discussed. We have provided a convergence strategy and revealed the internal relation of the singularity with that of the parallel robot, proving the feasibility of the algorithm and giving the working condition in the practical applications. The new algorithm have been compared to the Newton's method for an 8-U P S parallel robot, resulting in the time consumptions of 0.2187 milliseconds and 14.25 milliseconds respectively. And then we perform a simulation of the state-feedback control for an 8- P US parallel robot. The two examples present the applications of the new algorithm and demonstrate its validity and efficiency. [ABSTRACT FROM AUTHOR]

Robot-assisted training is a promising technology in clinical rehabilitation providing effective treatment to the patients with motor disability. In this paper, a multi-modal control strategy for a therapeutic upper limb exoskeleton is proposed to assist the disabled persons perform patient-passive training and patient-cooperative training. A comprehensive overview of the exoskeleton with seven actuated degrees of freedom is introduced. The dynamic modeling and parameters identification strategies of the human-robot interaction system are analyzed. Moreover, an adaptive sliding mode controller with disturbance observer (ASMCDO) is developed to ensure the position control accuracy in patient-passive training. A cascade-proportional-integral-derivative (CPID)-based impedance controller with graphical game-like interface is designed to improve interaction compliance and motivate the active participation of patients in patient-cooperative training. Three typical experiments are conducted to verify the feasibility of the proposed control strategy, including the trajectory tracking experiments, the trajectory tracking experiments with impedance adjustment, and the intention-based training experiments. The experimental results suggest that the tracking error of ASMCDO controller is smaller than that of terminal sliding mode controller. By optimally changing the impedance parameters of CPID-based impedance controller, the training intensity can be adjusted to meet the requirement of different patients. [ABSTRACT FROM AUTHOR]