On PID control of dynamic systems with hysteresis using a Prandtl-Ishlinskii model

Riccardi, Leonardo; Naso, David; Turchiano, Biagio; Janocha, Hartmut; Palagachev, Dian K.

doi:10.1109/acc.2012.6315107

Cited by 15 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the main goal of this section is to validate the framework for the stability analysis provided in section V, the details of the actuator are omitted (refer to [17], [14]) and we focus the attention on its hysteretic-dynamic description as in Fig. 2. In particular, the identified dynamics of the actuator correspond to those of a first-order linear system.…”

Section: Resultsmentioning

confidence: 99%

PID control of linear systems with an input hysteresis described by Prandtl-Ishlinskii models

Riccardi

Naso

Turchiano

et al. 2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

This paper deals with the stability analysis of PI and PID control of dynamic systems with an input hysteresis described by a modified Prandtl-Ishlinskii model. The problem of the asymptotic tracking of constant references is reformulated as the stability of a polytopic linear differential inclusion. This offers a simple linear matrix inequality condition that, when satisfied with the chosen PI or PID controller gains, ensures the tracking of constant references, allows the designer to establish a performance index and allows using powerful analysis and design tools for the controller. The validation of the approach is performed experimentally on a Magnetic Shape Memory Alloy micrometric positioning system. I. INTRODUCTIONHE use of smart materials such as piezoelectric ceramics as well as magnetostrictive, thermal shape memory and magnetic shape memory alloys (MSMA) in innovative devices has generated the fairly active research area of unconventional actuators [1]. Especially in positioning applications, the phenomenon of hysteresis, which arises in almost every unconventional actuator, is known to produce poor tracking performance or even instability if not properly handled by the controller. Moreover, the rate-independent hysteresis is often coupled with a further dynamic component (for example, the mechanical load that a positioning actuator has to move), leading to a rate-dependent input-output behavior. Literature offers a wide range of solutions to control hysteretic systems. A well-known strategy is to achieve a linearization of the input-output characteristic by inverting a model of the hysteresis, and relies on the maturity of several phenomenological models [2],[3],[4]. This method can be enforced with an outer control loop to improve the performance. Moreover, the inverse model can be made adaptive if the hysteresis effects are time-varying (for instance, due to temperature effects [5]) and/or the dynamic part of the plant is unknown [6],[7]. Unfortunately, the presence of the model and/or the inverse model can lead to complex control algorithms. Other approaches do not explicitly develop a model for the hysteresis, but rather attempt to compensate its effects by proper tuning of the Manuscript received March 3, 2012.

show abstract

Section: Resultsmentioning

confidence: 99%

PID control of linear systems with an input hysteresis described by Prandtl-Ishlinskii models

Riccardi

Naso

Turchiano

et al. 2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…12 shows an experimental result from [35]. C1 is a PI controller designed with the methods described in [21], while C1e has the same proportional and integral gains, but uses a simple integrator reset strategy for reducing the current. A comparison shows that C1e has 62% Joule losses less than C1.…”

Section: A Modeling and Control Of Msma Actuatorsmentioning

confidence: 99%

“…In particular, (5) allows the user to seek for controller parameters that guarantee the achievement of a predefined control goal by solving a linear matrix inequality (LMI) problem. The interested reader can refer to [16], [29], [21] and [30] for successful application of these ideas to MSMA actuators.…”

Section: A Modeling and Control Of Msma Actuatorsmentioning

confidence: 99%

See 1 more Smart Citation

Modeling and control of innovative smart materials and actuators: A tutorial

Riccardi

Rizzello

Naso

et al. 2014

2014 IEEE Conference on Control Applications (CCA)

Self Cite

View full text Add to dashboard Cite

The need for mechatronic devices that are lightweight, less cumbersome and able to produce small, quick and precise movements or forces is ever increasing in many fields of engineering. Many recent design solutions are based on electrically, magnetically or thermally activated materials, often referred to as smart materials. This tutorial paper overviews the main properties and the resulting applications of two recently discovered smart materials, magnetic shape memory alloys (MSMAs) and electroactive polymers (EAPs), which have complementary characteristics and seem suitable to overcome some of the inherent limitations of other materials widely used in industrial applications, such as piezoelectric ceramics. As many other smart materials, MSMAs and EAPs exhibit nonlinear, hysteretic and time-varying behaviors, and therefore this tutorial discusses the main ways to model and effectively compensate these critical issues with advanced control strategies.

show abstract

“…Only a few studies, however, have been dedicated to MSM-specific control problems until today. A PID feedback (PID) position controller has been applied to a multistable push-pull actuator in [8] where two MSM rods act in an antagonistic way, and to one-way MSM strain actuator with a return spring coaction in [9]. A hybrid control presented in [10] combines a PID position controller with a Petri net, which is specially designed to obtain a larger MSM response.…”

Section: Introductionmentioning

confidence: 99%

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Ruderman

Bertram

2014

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

Magnetic shape memory (MSM) actuators belong to active material technologies with a high energy density and outstanding field-strain relation. Large-scale multivariate fieldstress-strain hysteresis effects, however, antagonize their broad use because of the inherent difficulties with control. In this brief, we describe and compare experimentally several MSM control strategies, including the observer-based inverse hysteresis approach proposed in the previous works and combined here with a linear feedback controller by connecting both in parallel. For a prototypic MSM actuator with return spring, it is shown that the actuator plant can be approximated by an appropriate hysteresis operator and a linear transfer function of residual dynamics. The positioning profiles with a bandwidth 0.1-10 Hz and amplitudes between 0.01 and 0.1 mm have been evaluated by the experiments.Index Terms-Control systems, hysteresis, inversion, magnetic shape memory (MSM), observer, Preisach model, smart actuators.

show abstract

On PID control of dynamic systems with hysteresis using a Prandtl-Ishlinskii model

Cited by 15 publications

References 15 publications

PID control of linear systems with an input hysteresis described by Prandtl-Ishlinskii models

PID control of linear systems with an input hysteresis described by Prandtl-Ishlinskii models

Modeling and control of innovative smart materials and actuators: A tutorial

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Contact Info

Product

Resources

About