Positioning control of liquid crystal elastomer actuator based on double closed-loop system structure

A liquid crystal elastomer (LCE) actuator capable of colorimetric humidity sensing is realized. The designed LCE features acid protonated amino azobenzene side groups in its structure, which endow the actuator with the hygroscopicity and act as the humidity reporter via color changes. Given that the protonated and deprotonated chromophore absorb visible light at different wavelengths, when the protonated LCE is under higher humidity, it absorbs more water that deprotonates azobenzene and leads to a change in color. This humidity-dependent color change is fast, because surface protonation of the actuator is enough. The initial color and the sensitivity to humidity variation are determined by the extent of acid protonation, and the reversible color changes are distinguishable by the naked eye over a wide humidity range. The humidity sensing of LCE actuator in motion is demonstrated using thermally driven rolling rod actuators. Moreover, through spatial-selective exposure of the rolling rod actuator to water mist, the moisture can act as a stimulus to change or reverse the rolling direction and reduce the rolling speed. The achieved nature-inspired colorimetric humidity sensing capability represents an intelligent function for LCE actuators and may widen their application scope.

The voltage closed-loop field-weakening scheme (VCFS) is an effective method to achieve the maximum output torque for induction motor high-speed drives. However, the cross-coupling between the inner current and outer voltage loops leads to system performance deterioration. To address this problem, this article proposed a unified complex vector field-weakening control. First, the inherent coupling problem in VCFS is analyzed based on the double closed-loop structure. On this basis, a complex vector structure is designed to unify the inner current and outer voltage loops, following with a decoupled criterion for controller coefficient selection. Compared with the conventional VCFS, the studied scheme can eliminate the natural complex vector zero in the voltage loop, leading to current ripple and voltage overshoot reduction. The experimental results confirm the effectiveness of the investigated scheme.

Tuning control parameters of a fuzzy controller depends on trial-and-error. How this can be accomplished efficiently is an important subject in fuzzy control that should be investigated. We propose a method in which membership functions of a fuzzy controller can be simply set up using the knowledge of tuning parameters in a conventional PID controller. In this method, fuzzy control is realized as follows: Piecewise linear membership functions determined using the knowledge of tuning parameters in a PID controller are set up in antecedent parts of four fuzzy control rules having simple structures. Then the simplified inference method that enables high-speed inference is applied to fuzzy control rules.

The wheeled mobile robots have been widely applied in daily applications for its simplicity, robustness, stability and low-cost of manufacturing. Typically, PID controller is implemented to drive a mobile robot. However, the performance of the robot is greatly depended on the PID control parameters are tuned and the robustness of the mechanical system. Since the analog controllers were replaced by digital controller, PID control parameters could be automatically tuned to adapt the variation of the system parameters and operating condition. In this manuscript, a mathematical model is developed for a line following mobile robotic system which is used as a restaurant serving robot. The serving robot is controlled by an adaptive PID controller using Q-learning algorithm. The simulation and experimental results are compared to verify the advantage of the adaptive PID controller over classical PID controller.

An Interactive PID Learning Module for Educational Purposes

Researching optimization problems of controller is need of industrial process control ,in which PID controller is widely used,which its parameters can be equivalent to optimization problems. In the industrial control the PID controller is widely used in excitation control system to improve its control performance.In order to find the optimal PID controller parameters effectively ,a kind of Adaptive Particle Swarm Optimization method (CAPSO) based on Cloud Theory is applied to fuzzy PID controller. Through the establishment of particle swarm algorithm of fuzzy PID controller parameters optimization model, which it can be used to optimize the membership function of fuzzy PID controller. Particle code adopts real coding. Particle dimension is related with the number of the input variables divided by fuzzy set and the number of control rules of whole fuzzy control system, thus the parameters of PID control are optimized on real time. The result from the simulation shows that compared with PID control and fuzzy control this system has several advantages which are small overshoots ,fast response ,and good stable performance to improve the control performance of excitation control system.

PID control is the most mature control method in classical control theory. PID control is widely used in the electromagnetic bearing control system. However, how to design PID control parameters to reduce the adjustment time and overshoot of electromagnetic bearings after disturbance is still an issue that needs to be further investigated. In this paper, the influence of "natural" stiffness and "natural" damping on system stability is evaluated to select the value range of P and D control parameters, and the value range of the I parameter is determined by using the Rouse criterion. Based on the genetic algorithm with a novel fitness function considering both the system phase margin and closed-loop bandwidth, the PID controller parameters are optimized. The simulation results show that the overshoot and the adjustment time of the genetic algorithm optimized PID controller are much smaller than that of the conventional method.

The main drive system using for four-high mill is usually a double closed loop DC motor speed regulating system. Generally, the speed controller and current controller are PID controllers, and the parameters of controllers are determined by the engineering design method. Once disturbance occur, the control effects are often just passable. In this paper, fuzzy logic is used to set the parameters of the speed PID controller, so as to improve the disturbance rejection ability. Simulation results show that the fuzzy tuning PID controller can give better control effect than the regular control.

This paper proposes the voltage/current double-loop control PWM method to depress the harmonic. After that, the PID controller's parameter design method is researched to depress the harmonic better. At last, the output current of the inverter is analyzed through the GCPV model accomplished in MATLAB considering the change of the light intensity. The result is good(the harmonic content is within the scope of the standard) and the dynamic performance of the GCPV is well when adjusting the PID controller's parameters. The simulation results prove the effectiveness and value of this paper's harmonic depression method.

In recent years, the research on control strategy of three-phase grid-connected inverter has attracted significant attention. Proportion integration (PI) control method is widely utilized to control the grid-connected inverter. However, coordinate transformation is an essential and complex step during the design process of the conventional PI controller. It is difficult to implement in practice due to the complex coordinate transformation. The proportional-resonant (PR) control method of the three-phase grid-connected inverter is proposed, where the conventional PI controller is replaced by PR controller. PR controller has a simple structure as the complex coordinate transformation can be neglected. In order to improve the power factor and the stability of the system, double closed loop structure is also introduced in the proposed control strategy. In the end, simulation software is developed, and the simulation results confirm the effectiveness of the proposed control method.

ABSTRACTThis paper involves the design of non-overshooting PD and PID controllers for some special plants. The PID controller parameters are determined to reach a stable closed-loop system with monotonically decreasing frequency response. Thus specific regions in the controller parameters space are obtained. Gain crossover frequency and phase isodamping property are employed to choose an appropriate solution among the obtained solutions. The performance of the proposed PD and PID controllers in position and velocity control of a laboratory DC servomechanism system is investigated through experimental tests.

In this paper, a robust fuzzy-tuned PID controller is proposed for the trajectory tracking and vibration control of a flexible joint manipulator system (FJMS) with parametric uncertainties. Flexible joint manipulators are widely used in industry due to their flexibility, light in weight and fast response, low cost, and low energy consumption. The dynamic modeling via Euler-Lagrange equation for a single link flexible joint manipulator system (FJMS) is presented first. By analyzing the characteristics of the high order linear system, the Fuzzy-Tuned PID control strategy is utilized. The parameters of classical PID controller are updated by the intelligent method of fuzzy logic. With the adaptivity to the parametric uncertainties from the system stiffness and moment of inertia, the contrived approach provides more efficient results compared to existing techniques in terms of vibration suppressions, time response, and overshoot. Finally, the effectiveness of the controller is corroborated through multiple experiments on the QUANSER's flexible joint manipulator system (FJMS).

A fuzzy-PID speed controller proposed in this paper is designed for the Doubly Salient Motor (DSM) with axial flux, which has high efficiency of rotor and power density. This paper started from the structure and mathematical model of axial flux DSM, and then analyzed its operating characteristics. Due to nonlinear functions of Flux and torque rotor position and phase current, application of linear control methods cannot meet the requirements of non-linear, variable structure and variable parameters. In order to stabilize the motor and achieve the maximum speed quickly, a fuzzy-PID speed controller utilizes the fuzzy control strategy to get tuning rules of three parameters in PID controller, comparing to very complicate conventional PID control parameters self-tuning process. Simulation results show that the fuzzy PID control is superior to the traditional PID control, which can effectively improve the response speed and interference immunity, shorten the rise time and reduce the overshoot.

In order to improve the stability of the output voltage of the two-stage matrix converter (TSMC) under disturbance load and unbalance load, a control strategy based on expert adaptive PID control is presented. Under synchronous rotating coordinate through d-q transformation, the system adopts the expert PID controllers to trace the given voltage of d-q components. The parameters of PID controller are regulated adaptively and by contrast with the traditional PID control, the closed-loop control system with the expert PID control has the better dynamic performance and stronger robustness. Numerical simulation verified the validity and effectiveness of the proposed control method.

The spontaneous amino-yne click reaction is introduced for the first time as a fast, efficient, and ambient temperature strategy for preparing multi-responsive Liquid Crystal Elastomer (LCE) actuators. This synthetic approach relies on the amino-yne cross-linking between secondary amines along the main chain of poly(β-amino ester) liquid crystal oligomers and a dipropiolate-functionalized cross-linker, rendering β-aminoacrylate cross-linking points. After alignment and locking via dynamic transesterification at 30°C, the resulting LCE actuators exhibit reversible and reproducible thermal and light-induced actuation. The generated tension and activation kinetics are easily tunable by adjusting the cross-linker content. Additionally, leveraging the acid-triggered reactivity of the network enables it to respond to additional stimuli, including water-driven actuation. By integrating the capability for dynamic bond exchange, this LCE formulation opens new avenues for designing structures with complex molecular orientation patterns. As a proof of concept, a star-shaped soft actuator is fabricated, demonstrating diverse programmable actuation modes.