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An input shaper-based model predictive control scheme is proposed for an overhead crane to suppress the swing of the payload. A control-oriented mathematical model of the crane is firstly derived based on the small angle hypothesis. Furthermore, three kinds of commonly used shapers are discussed and a zero vibration derivative shaper is selected for the crane. Then, a model predictive swing suppression controller is designed for the crane based on the selected shaper. Constraints on the control input and its slew rate are respected. Besides, the constraint on the swing angle of the payload is also respected as an output constraint. The constrained solution is given in the form of standard quadratic programming. The designed control scheme combines open-loop and closed-loop control techniques, achieving accurate positioning of the trolley and good swing suppression of the payload. A series of simulation demonstrates the effectiveness and advantages of the proposed scheme.

The drilling and anchoring robot is an important equipment to realize the intellectualization of fully mechanized coal mining. The control effect of its manipulator directly affects the safety and efficiency of the support operation of the drilling and anchoring robot. The control of drilling anchor manipulator usually adopts PID controller, but due to the limitation of integer order PID control algorithm and traditional empirical parameter adjustment, it is difficult to find a group of parameters with the best control effect in a short time, resulting in the failure of timely and accurate positioning of the end of the manipulator. In this paper, the combination of numerical modeling and simulation analysis is used to adjust the parameters of fractional order PI λ D μ controller by using search algorithm (GPS) and applied to the motion control of manipulator; Based on the independent joint control theory, the single input single output system model of hydraulic cylinder at the joint of manipulator is established by using Matlab-Simulink software and fractional PI λ D μ control technology. The fractional order control system is regulated by input shaping feedforward control technology(IS). The step response effect of the hydraulic system is further analyzed by setting input feedforward controllers with different gain ratios. The numerical simulation results show that the control strategy of “Input Shaping(IS) + Intelligent optimization algorithm (GPS) parameter adjustment + Fractional PI λ D μ control technology” can effectively improve the spatial accurate positioning of mining manipulator. The research expand the application of intelligent control technology in the field of mining equipment.

In this paper, the residual vibration control problem of a nuclear power plant’s fuel-transport system is discussed. The purpose of the system is to transport fuel rods to the target position within the minimum time. But according to observations, the rods oscillate at the end of the maneuver, causing an undesirable delay in the operation and affecting the system’s performance in terms both of productivity and of safety. In the present study, a mathematical model of the system was developed to simulate the under-water sway response of the rod while keeping in view the effects of the hydrodynamic forces imposed by the surrounding water. Experiments were performed to validate the model’s correctness. Further, simulation results were used to design the input shaping control that generates shaped velocity commands for transport of the fuel rods to the target position with the minimum residual vibration. It was observed that due to the under-water maneuvering, the fuel-handling system behaves as a highly damped process and that the generated shaped velocity commands fail to effect the desired suppression of the residual vibration. Therefore, keeping in view the highly damped nature of the system, a modified shaped command was generated that transported the fuel rods to the target position with the minimum residual vibration.

In this study, symmetric perturbation extra-insensitive input shapers (SPEI-ISs) are proposed to enhance the robustness of the impulse-time perturbation approach, particularly toward the low-frequency range, with respect to the modeled natural frequency. These perturbation-based extra-insensitive input shapers (PEI-ISs) provide a wider range of robustness than the well-known robust input shapers, which include derivative input shapers (e.g., ZVD, ZVDD, and ZVDDD shapers) and extra-insensitive input shapers (EI-ISs). However, robustness may be lost, particularly at lower frequencies, as a result of asymmetric placement of the notch points on the sensitivity curve. To address this issue, an SPEI-IS is derived by placing the notch points symmetrically to enhance robustness, particularly in the low-frequency range. In single-, two-and three-hump cases, explicit solutions are presented to demonstrate the usability of the proposed shapers. The robustness and transient response are evaluated through simulation and experiment and are compared to the response of conventional robust input shapers. It is concluded that the proposed SPEI-IS improves robustness and transient response.

This study is concerned with the active vibration control of a cart-pendulum system. The input-shaping control alone is not sufficient to suppress vibrations of the cart payload, especially when external disturbance is present. In order to solve this problem, a new control technique consisting of the input-shaping and the position-input position-output feedback controls is proposed. The input-shaping control minimizes vibrations during cart motion and the position-input position-output feedback control takes charge of suppressing residual vibrations after the cart reaches the desired position. The stability of the proposed position-input position-output feedback control was investigated theoretically. The testbed was built to validate the proposed method. It was proved both theoretically and experimentally that the proposed control technique can be successfully used to control vibrations of the pendulum.

The residual vibration caused by joint flexibility tends to be nonlinear and time-varying due to the complicated dynamics characteristics of 6-DOF industrial robot. To address the time-varying residual vibration problem, this paper proposes a pre-adaptive input shaping method. By simplifying the 6-DOF industrial robot standard flexible dynamics equation, the flexible dynamical parameters can be identified without additional joint encoders or other measuring instrument, while the natural frequency of each joint can also be calculated from the identified dynamical parameters. Then by setting the calculated natural frequency as the initial condition, an iterative learning scheme based on the secant method can be applied to obtain a better natural frequency estimate. Finally, using the iteration results, the input shaper’s parameters can be updated, which makes the shaper adapt to the variation of system parameters. The results of model validation show that the simplified dynamic model can reflect the robot dynamic characteristics accurately. The vibration experimental results demonstrate the effectiveness of the proposed pre-adaptive input shaper in suppressing the residual vibration.

In this article, a promoted method of adaptive input shaping based on recursive least square with forgetting factor is proposed to achieve zero residual vibration of time-varying flexible systems. First, the zero residual vibration condition of the flexible system is reviewed. Then, the mathematical analysis of recursive least square–based adaptive input shaping is presented; it can be seen that the traditional recursive least square method could calculate the least square solution with all historical I/O data. That is to say, with the increase in time and larger amount of I/O data, the current data could hardly affect the results of the updated input shapers’ coefficients; thus, the problems of insufficient adaptability and noise accumulation occur. So, a forgetting factor is introduced in the recursive calculation to give less calculation weight on historical data and improve the sensitivity of the current data; thus, the above-mentioned problem could be significantly avoided. At last, the verification experiments of adaptive input shaping are implemented on a two-link flexible manipulator, which is a classical flexible system with severely time-varying dynamics; the results validate the effectiveness of the improved adaptive input-shaping method for the vibration control of these flexible systems.

We develop a new technique for preshaping input commands to control microelectromechanical systems (MEMS). In general, MEMS are excited using an electrostatic field which is a nonlinear function of the states and the input voltage. Due to the nonlinearity, the frequency of the device response to a step input depends on the input magnitude. Therefore, traditional shaping techniques which are based on linear theory fail to provide good performance over the whole input range. The technique we propose combines the equations describing the static response of the device, an energy balance argument, and an approximate nonlinear analytical solution of the device response to preshape the voltage commands. As an example, we consider set-point stabilization of an electrostatically actuated torsional micromirror. The shaped commands are applied to drive the micromirror to a desired tilt angle with zero residual vibrations. Simulations show that fast mirror switching operation with almost zero overshoot can be realized using this technique. The proposed methodology accounts for the energy of the significant higher modes and can be used to shape input commands applied to other nonlinear micro- and macro-systems.

Input-shaping is one of the most practical open-loop control strategies for gantry cranes, especially those having predefined paths and operating at constant cable lengths. However, when applied to quay-side container cranes, its performance is far from satisfactory. A major source of the poor performance can be linked to the significant difference between the gantry crane model and the quay-side container crane model. Gantry cranes are traditionally modeled as a simple pendulum. However, a quay-side container crane has a multi-cable hoisting mechanism.In this paper, a two-dimensional four-bar-mechanism model of a container crane is developed. For the purpose of controller design, the crane model is reduced to a double pendulum with two fixed-length links and a kinematic constraint. The method of multiple scales is used to develop a nonlinear approximation of the oscillation frequency of the simplified model. The resulting frequency approximation is used to determine the switching times for a bang-off-bang input-shaping controller. The performance of the controller is numerically simulated on the full model of the container crane, and is compared to the performance of similar controllers based on a nonlinear frequency approximation of a simple pendulum and a linear frequency approximation of a constraint double pendulum. Results demonstrate a superior performance of the controller based on the nonlinear frequency approximation of the constraint double pendulum.The effect of the oscillation frequency on the controller performance is investigated by varying the model's frequency around the design value. Simulations revealed that the performance of the controller suffers serious degradation due to small changes in the model frequency. To alleviate the shortcomings of the input-shaping controller, a delayed-position feedback controller is successfully applied at the end of each transfer maneuver to eliminate residual oscillations without affecting the commands of the input-shaping controller.

Non-volatile computing-in-memory (nvCIM) architecture can reduce the latency and energy consumption of artificial intelligence computation by minimizing the movement of data between the processor and memory. However, artificial intelligence edge devices with high inference accuracy require large-capacity nvCIM macros capable of high-bit-precision dot-product operations. Here we report a four-megabit nvCIM macro that combines memory cells with peripheral circuitry and is based on 22-nm-foundry binary resistive random-access memory devices and complementary metal–oxide–semiconductor (CMOS) processes. The fully CMOS-integrated macro features an asymmetrically modulated input-and-calibration scheme, a calibrated-and-weighted current-to-voltage stacking read scheme, and input-shaping hardware to overcome the challenges involved in designing large-capacity nvCIM macros with high bit precision. The macro offers latencies between 5.2 and 15.2 ns and energy efficiency between 194.4 and 15.6 tera-operations per second per watt in binary to 8-bit-input–8-bit-weight dot-product operations. Advanced complementary metal–oxide–semiconductor technology and resistive random-access memory can be used to create high-bit-precision compute-in-memory macros for low latency and efficient edge computing.