Robust adaptive control of conjugated polymer actuators

Conjugated polymers are promising actuation materials for bio and micromanipulation systems, biomimeticrobots, and biomedical devices. Sophisticated electrochemomechanical dynamics in these materials, however,poses significant challenges in ensuring their consistent, robust performance in applications. In this paper aneffective adaptive control strategy is proposed for conjugated polymer actuators. A self-tuning regulator isdesigned based on a simple actuator model, which is obtained through reduction of an infinite-dimensionalphysical model and captures the essential actuation dynamics. The control scheme is made robust againstunmodeled dynamics and measurement noises with parameter projection, which forces the parameter estimates tostay within physically-meaningful regions. The robust adaptive control method is applied to a trilayer polypyrroleactuator that demonstrates significant time-varying actuation behavior in air due to the solvent evaporation.Experimental results show that, during four-hour continuous operation, the proposed scheme delivers consistenttracking performance with the normalized tracking error decreasing from 11% to 7%, while the error increasesfrom 7% to 28% and to 50% under a PID controller and a fixed model-following controller, respectively. In themean time the control effort under the robust adaptive control scheme is much less than that under PID, whichis important for prolonging the lifetime of the actuator

Robust adaptive control of conjugated polymer actuators

Conjugated polymers are promising actuation materials for bio- and micromanipulation systems, biomimetic robots, and biomedical devices. Sophisticated electrochemomechanical dynamics in these materials, however, poses significant challenges in ensuring their consistent, robust performance in applications. In this paper, an effective adaptive control strategy is proposed for conjugated polymer actuators. A self-tuning regulator is designed based on a simple actuator model, which is obtained through reduction of an infinite-dimensional physical model and captures the essential actuation dynamics. The control scheme is made robust against unmodeled dynamics and measurement noises with parameter projection, which forces the parameter estimates to stay within physically meaningful regions. The robust adaptive control method is applied to a trilayer polypyrrole (PPy) actuator that demonstrates significant time-varying actuation behavior in air due to the solvent evaporation. Experimental results show that, during 4-h continuous operation, the proposed scheme delivers consistent tracking performance with the normalized tracking error decreasing from 11% to 7%, while the error increases from 7% to 28% and to 50% under a proportional-integral-derivative (PID) controller and a fixed model-following controller, respectively. In the meantime, the control effort under the robust adaptive control scheme is much less than that under PID, which is important for prolonging the lifetime of the actuator

Modeling and inverse feedforward control for conducting polymer actuators with hysteresis

Conducting polymer actuators are biocompatible with a small footprint, and operate in air or liquid media under low actuation voltages. This makes them excellent actuators for macro- and micro-manipulation devices, however, their positioning ability or accuracy is adversely affected by their hysteresis non-linearity under open-loop control strategies. In this paper, we establish a hysteresis model for conducting polymer actuators, based on a rate-independent hysteresis model known as the Duhem model. The hysteresis model is experimentally identified and integrated with the linear dynamics of the actuator. This combined model is inverted to control the displacement of the tri-layer actuators considered in this study, without using any external feedback. The inversion requires an inverse hysteresis model which was experimentally identified using an inverse neural network model. Experimental results show that the position tracking errors are reduced by more than 50% when the hysteresis inverse model is incorporated into an inversion-based feedforward controller, indicating the potential of the proposed method in enabling wider use of such smart actuators

Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control

Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller\u27s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers

Fiber-reinforced Conjugated Polymer Torsional Actuator and Its Nonlinear Elasticity Modeling

Abstract-Reported conjugated polymer actuators have typically been limited to bender or linear extender configurations. In this paper, we present a fiber-reinforced conjugated polymer actuator capable of torsional motion. By incorporating platinum fibers into the material matrix during the electrochemical fabrication process, we create anisotropy in the interaction between the fiber and the material matrix, resulting in torsion and other associated deformations upon actuation. A nonlinear elasticitybased model is utilized to capture the actuator performance for both small and large deformations. The effectiveness of the model is verified through comparison with experimental results

Conducting polymer microactuators operating in air

We report for the first time on microsized conducting polymer actuators, which operate in air and in liquids. These actuators are potentially useful for a wide range of applications from biotechnology to microrobots. Furthermore, the actuators are fabricated using an excimer laser ablation technique, which does not require clean-room facilities and can provide high throughput production. Preliminary characterization results presented show that the tip displacement of the microactuators is linearly proportional to the magnitude of the input voltage

Doctor of Philosophy

dissertationConducting polymer actuators have shown numerous improvements in mechanical performance over the last couple of decades, but can be better utilized in applications with the ability to adjust to unknown operating conditions, or improved during their lifetime. This work employs the process of sequential growth to initially fabricate polypyrrole-metal coil composite actuators, and then again for further actuator growth during its lifetime of operation. The novel synthesis process was first shown through the use of a custom testing apparatus that could support the sequential growth process by allowing different actuation and synthesis solutions to be controlled in the test cell, as well as facilitate mechanical performance testing. Open-loop testing demonstrated the actuator system performance for multiple growth stages over multiple input frequencies, and was then compared to the parameters identified to fit a simplified model during operation. The simplified model was shown to differentiate from the experimental data, but provided useful optimal growth prediction values with a performance cost evaluation algorithm. The model could predict the optimal growth determined by the experimental data to within one growth stage. Performance was improved by using a proportional-derivative feedback controller where the gains were calculated by the desired response at each growth stage for each sample. The cost performance was performed again with the closed-loop data, but did an inferior job of predicting the optimal amount of growth for each sample compared to the open-loop data. The simplified model accurately tracked the behavior changes through multiple stages of growth. The main contributions of this work include a novel testing apparatus and synthesis method for multiple growth steps, the implementation of a simplified model for tracking and optimal growth stage prediction, and the application of a model-based proportional-derivative feedback controller