Design and control of 2-DoF joystick using MR-fluid rotary actuator

The purpose of this paper is to design a control algorithm for a 2-DoF rotary joystick model. Firstly, the structure of the joystick, which composes of two magneto-rheological fluid actuators (shorten MRFA) with optimal configuration coupled perpendicularly by the gimbal mechanism to generate the friction torque for each independent rotary movement, is introduced. The control strategy of the designed joystick is then suggested. Really, because of two independent rotary movements, it is necessary to design two corresponding controllers. Due to hysteresis and nonlinear dynamic characteristics of the MRFA, controllers based an accurate dynamic model are difficult to realize. Hence, to release this issue, the proposed controller (named self-turning fuzzy controllers-STFC) will be built through the fuzzy logic algorithm in which the parameters of controllers are learned and trained online by Levenberg-Marquardt training algorithm. Finally, an experimental apparatus will be constructed to assess the effectiveness of the force feedback controls. Herein, three experimental cases are performed to compare the control performance of open-loop and close-loop control method, where the former is done through relationship between the force at the knob and the current supplied to coil while the latter is realized based on the proposed controller and PID controller. The experimental results provide strongly the ability of the proposed controller, meaning that the STFC is robust and tracks well the desirable force with high accuracy compared with both the PID controller and the open-loop control method.

Research on edge controller based on industrial furnace

Traditional control instruments and DCS control systems are limited by shortcomings such as single control function, independent controlled elements, inability to close-loop control on site, and ineffective communication. Aiming at these problems, this paper proposes a kind of industrial furnace edge controller which has the functions of acquisition, calculation, control, storage, output and communication in one. The edge controller structure, edge computing and the control method applied to edge computing are designed. The fuzzy PID control method is compared with the conventional PID control method by taking the temperature control of resistance furnace as an example. The simulation shows that the control effect of fuzzy PID on resistance furnace temperature is obviously better than that of conventional PID. The test results also show that the performance indices for the fuzzy PID control are better, which again proves that the fuzzy PID control outperforms. The research results of this paper are of reference value for engineering applications.

Fuzzy logic aided PPF controller design to active vibration control of a flexible beam

This paper presents a fuzzy-logic-based observer and a positive position feedback controller to reduce a standard beam's free vibrations using a piezoelectric actuator. It is aimed that fuzzy-logic-based observer is used as feed-through and improves the overall performance of the PPF controller. For this aim, the cantilever beam and a piezoelectric patch are initially numerically modeled using the finite element method considering the close loop control algorithm. The displacement and strain responses results are compared with the experimental model. Then, two controllers are applied to the designed system: positive position feedback (PPF) and fuzzy-logic-based positive position feedback (FLBPPF). The uncontrolled and controlled system responses are investigated and compared in terms of the linear strain and tip displacement results. Using the FLBPPF controller, the settling times of controlled systems are decreased by about 20.7% and 41.6% regarding the linear strain and tip displacement response compared to the PPF controller.

Automated Close-Loop System for Three-Dimensional Characterization of Spatiotemporal Optical Vortex

Recent rapid advances in spatiotemporal optical pulses demand accurate characterization of the spatiotemporal structure of the produced light fields. We report an automated close-loop characterization system that is capable of reconstructing the three-dimensional intensity and phase structures of spatiotemporal wavepacket illustrated by characterizing spatiotemporal optical vortex in the spatiotemporal domain. The characterization technique is based on interfering a much shorter probe pulse with different slices of the object wavepacket along the temporal axis. A close-loop control program is developed to realize full automation of the data collection and reconstruction process. Experimental results of the intensity and phase distributions show that the designed close-loop system is efficient in quantitatively characterizing the generated spatiotemporal optical vortex. Such a linear characterization system can also be extended to measure many other kinds of spatiotemporal wavepacket and may find broad applications in spatiotemporal wavepacket studies.

A New Active Control Driver Circuit for Satellite’s Torquer System Using Second Generation Current Conveyor

In this article a new active control driver circuit is designed using the second-generation current conveyor for the satellite’s torquer system. The torquer plays an important role in the attitude control of the satellite. Based on the magneto-meter data, the satellite’s microprocessor calculates the required current for the torque and sends a reference command. A close loop control system is designed, which generates the desired output current. The parameters of the controller are optimized using a variant of the well-known evolutionary algorithm, the genetic algorithm (GA). This variant is known as the segmented GA. The controller is experimentally implemented using the commercially available integrated circuit, the AD844. The error between the experimental and simulation results has RMS values in range of 0.01–0.16 A for the output current and 0.41–0.6 V for the output voltage. It has mean value of 0.01 A for the output current and has mean values in the range of 0.33–0.48 V for the output voltage. It has standard deviation of 0.01 A for the output current and standard deviations in the range of 0.24–0.35 V for the output voltage. Thus, there is a close match between the simulation and experimental results, validating the design approach. These designs have many practical applications, particularly for nanosatellites powered by photovoltaic panels.

A Hardware-in-the-Loop-on-Chip Development System for Teaching and Development of Dynamic Systems

This paper proposes a low-cost on-chip Hardware-in-the-Loop (HIL) platform for teaching and fast prototyping of dynamic systems. A dual-core digital signal controller (DSC)-based solution is proposed for the HIL system. CPU core A, as the simulation engine, is dedicated to circuit and system simulation. The actuation and control logic are implemented in CPU core B, which is working as the control engine. Inter-processor communication is used to interchange variables between the CPUs. The digital-to-analog converter and digital outputs are used to send the duty cycle and system state variables to the oscilloscope for users’ visual feedback. Two typical systems with fast and slow dynamics are modeled and implemented in the simulation engine. Under the excitation generated by the control engine, system dynamics can be observed for studying purposes. Close-loop control for a buck converter is also demonstrated on the developed prototype, where both input voltage and load variations performance are tested. The test results indicate that the digital simulator can well emulate the average small signal model of a power converter in open-loop and close-loop scenario. Meanwhile, the control parameters can be modified for system performance evaluation and education purposes. The proposed low-cost HIL system can be easily applied to the engineering teaching as well as fast prototype development phase of product design.

Theoretical and experimental research on the cartridge two-dimensional (2D) electro-hydraulic servo valve

A cartridge 2D EHSV based on torque motor is proposed in this paper, which is keeping the advantages of conventional 2D valve, such as compact structure, high power-to-weight ratio, and excellent dynamic characteristics. In order to explore its dynamic characteristics, the design concept and operating principle of the cartridge 2D EHSV valve is presented first. Then the mathematical model of cartridge 2D EHSV valve is derived, especially the rotational viscous damping coefficient which is studied in detail. The simulation results of the open(closed)-loop model show that the support pressure plays an insignificant role in the dynamic characteristics of 2D EHSV, only the phase bandwidth of the closed-loop model increases. And the rise time of the open-loop model is about 10 ms, and the frequency bandwidth is about 40 Hz, while the rise time is about 4 ms and the frequency bandwidth is about 100 Hz of the closed-loop model. Furthermore, as verified by experimental results, the rising time of the step response is about 7 ms and the bandwidth is approximately 38 Hz under the open-loop control, while that is 6 ms and 117 Hz for 25% input signal under the close-loop control. Finally, the difference between the experiment and the simulation is discussed. It is concluded that the cartridge 2D EHSV has excellent dynamic characteristics.

Learn to Make Decision with Small Data for Autonomous Driving: Deep Gaussian Process and Feedback Control

Autonomous driving is a popular and promising field in artificial intelligence. Rapid decision of the next action according to the latest few actions and status, such as acceleration, brake, and steering angle, is a major concern for autonomous driving. There are some learning methods, such as reinforcement learning which automatically learns the decision. However, it usually requires large volume of samples. In this paper, to reduce the sample size, we exploit the deep Gaussian process, where a regression model is trained on small sample datasets and captures the most significant features correctly. Besides, to realize the real-time and close-loop control, we combine the feedback control into the process. Experimental results on the Torcs simulation engine illustrate smooth driving on virtual road which can be achieved. Compared with the amount of training data in deep reinforcement learning, our method uses only 0.34% of its size and obtains similar simulation results. It may be useful for real road tests in the future.