This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

This paper presents a modified Prandtl-Ishlinskii (P-I) (MPI) model for the asymmetric hysteresis description and compensation of piezoelectric actuators. Considering the fact that the classical P-I (CPI) model is only efficient for the symmetric hysteresis description, the MPI model is proposed to describe the asymmetric hysteresis nonlinearity of piezoceramic actuators (PCAs). Different from the commonly used approach for the development of asymmetric P-I models by replacing the classical play operator with complex nonlinear operators, the proposed MPI model still utilizes the classical play operator as the elementary operator, while a generalized input function is introduced to replace the linear input function in the CPI model. By this way, the developed MPI model has a relative simple mathematic format with fewer parameters to characterize the asymmetric hysteresis behavior of PCAs. The benefit for the developed MPI model also lies in the fact that an analytic inverse model of the CPI model can be directly applied for the inverse compensation of the asymmetric hysteresis nonlinearity represented by the developed MPI model in real-time applications. To validate the developed MPI model and the inverse hysteresis compensator, simulation, and experimental results on a piezoceramic actuated platform are presented.

Modeling and Compensation of Asymmetric Hysteresis Nonlinearity for Piezoceramic Actuators With a Modified Prandtl–Ishlinskii Model

The three previous industrial revolutions profoundly transformed agriculture industry from indigenous farming to mechanized farming and recent precision agriculture. Industrial farming paradigm greatly improves productivity, but a number of challenges have gradually emerged, which have exacerbated in recent years. Industry 4.0 is expected to reshape the agriculture industry once again and promote the fourth agricultural revolution. In this paper, first, we review the current status of industrial agriculture along with lessons learned from industrialized agricultural production patterns, industrialized agricultural production processes, and the industrialized agri-food supply chain. Furthermore, five emerging technologies, namely, the Internet of Things, robotics, Artificial Intelligence, big data analytics, and blockchain, toward Agriculture 4.0 are discussed. Specifically, we focus on the key applications of these emerging technologies in the agricultural sector and corresponding research challenges. This paper aims to open up new research opportunities for readers, particularly industrial practitioners.

IEEE transactions on industrial informatics

This paper presents the design and testing of a novel continuous third-order integral terminal sliding mode control (3-ITSMC) strategy dedicated to motion tracking control of a piezoelectric-driven nanopositioning system. In comparison with the available sliding mode controllers, the significant improvement of the proposed controller lies in the fact that it completely eliminates the chattering effect, achieves a finite-time convergence, and produces a higher sliding mode precision. The model uncertainty involving the hysteresis effect is estimated by the perturbation estimation technique. Higher order derivatives of the position are generated by using a robust exact differentiator. Based on an integral terminal type of sliding surface, a third-order sliding mode precision is obtained by resorting to the third-order supertwisting algorithm. The convergence and stability have been proved in theory. The performance improvement of the developed controller versus the conventional second-order and third-order sliding mode controllers is validated by carrying out both simulation and experimental studies. Results demonstrate that the proposed 3-ITSMC controller provides quicker transient response speed and smaller steady-state error for the piezoelectric nanopositioning system along with a better robustness against model uncertainty and external disturbance.

Continuous Integral Terminal Third-Order Sliding Mode Motion Control for Piezoelectric Nanopositioning System

Rate-dependent hysteretic nonlinearity, which is an inherent characteristic of piezoelectric actuators (PEAs), causes a significant challenge in precise motion control of piezoelectric nanopositioning stages. In this paper, by assuming that the model of PEA takes a Hammerstein structure, a novel control strategy that combines iterative learning control (ILC) and the direct inverse of hysteresis is proposed to compensate for both nonlinearities and uncertainties of system simultaneously. Different from those existing direct inverse compensation methods whose control performance highly relies on the accuracy of the hysteresis model, the proposed control strategy is more robust by adding an additional ILC loop. Since ILC is essentially a feedforward control scheme that fully utilizes the input and output information in previous iterations, the tracking precision can be improved promptly in the iteration domain. Comparative experiments are performed to test the efficacy of the proposed algorithm for polynomial, triangular, and step signals. Results show that it is superior to pure proportional–integral (PI) controller and even PI controller combined with inverse compensator in the sense that the root mean square, relative, as well as maximal absolute errors of output tracking have been decreased remarkably within five iterations.

High-Precision Tracking of Piezoelectric Actuator Using Iterative Learning Control and Direct Inverse Compensation of Hysteresis

The scanning accuracy of piezoelectric mechanisms over broadband frequencies is limited due to inherent dynamic hysteresis. This phenomenon has been a key bottleneck to the use of piezoelectric mechanisms in fast and precision scanning applications. This paper presents a systematic model identification and composite control strategy without hysteresis measurement for such applications. First, least squares estimation using harmonic signals is applied to achieve the Preisach density function. Next, the hysteresis output is estimated, such that the non-hysteretic dynamics can be identified. The discrete composite control strategy is proposed with a feedforward-feedback structure. The feedforward controller is the primary component designed for the performance. The secondary proportional-integral (PI) feedback controller is employed to suppress disturbances for robustness. Finally, the identification and composite control strategy is implemented with a dSPACE 1104 board for a real piezoelectric actuator setup. The experimental results indicate that adequate scanning performance can be sustained at a rate higher than the first resonant frequency.

Discrete Composite Control of Piezoelectric Actuators for High-Speed and Precision Scanning

This paper presents a comprehensive approach for the identification of the hysteresis and coupled nonhysteretic dynamics of piezoelectric actuators over a broad range of frequencies. The approach leverages on the special characteristics and distinctions of the hysteretic and nonhysteretic components to identify them in sequence, efficiently. The nonhysteretic dynamics is identified using square wave input signals. The creep dynamics is identified using an input signal with a long period. Conversely, electric and vibration dynamics are identified using an input signal with a small period. Moreover, the drift due to the creep is eliminated by employing its model inversion. The Preisach hysteresis is identified with specially designed harmonic input signals and sampling rules, which overcome the persistent excitation problem of hysteresis identification and improve the computational efficiency. Simulation and experiments are conducted to validate the effectiveness of the identification approach.

Development of an Approach Toward Comprehensive Identification of Hysteretic Dynamics in Piezoelectric Actuators

In this paper, the singular value decomposition (SVD) based identification and compensation of the hysteretic phenomenon in piezo actuators are addressed using a Preisach model. First, this paper presents an SVD-based least squares algorithm and a revision approach of the identification through updating the SVD. With the identified parameters and a log of the memory curve, a Preisach-based inversion compensator is constructed which is complemented with a feedback controller to address the inevitable and residual modeling errors. Experimental results are furnished for both the identification and compensation approaches. The Preisach-based feedforward controller significantly improves the tracking performance and reduces the root-mean-square (RMS) tracking error of a PID controller by 76.7% and 89% at 1 Hz and 25 Hz, respectively. With the proposed composite controller, the percent-RMS errors at 1 Hz and 25 Hz are reduced to 0.035% and 0.31%, respectively.

SVD-based Preisach hysteresis identification and composite control of piezo actuators.

High-performance instruments are very sensitive to vibrations and jitters. In this article, a new approach towards multi-degree-of-freedom DOF active vibration isolation and its application in spacecraft jitter suppression are presented. Model reference adaptive control MRAC with acceleration feedback is used to isolate random disturbances. However, a side effect of this algorithm is that displacements at low frequencies are amplified. Thus, the MRAC is augmented with proportional–integral–differential PID displacement feedback to suppress vibration displacements. The MRAC-PID composite control is applied to a 4-leg platform to isolate vibrations and suppress tip/tilt jitters. The scheme is also used to isolate 6-DOF vibrations and steer the payload of a flexible spacecraft. Satisfactory performance of vibration isolation and jitter attenuation has been observed.

Active vibration isolation based on model reference adaptive control

This paper presents the application of iterative learning control (ILC) to compensate hysteresis in a piezoelectric actuator. The proposed controller is a hybrid of proportional-integral-differential (PID) control, whose main function is for trajectory tracking, and a chatter-based ILC, whose main function is for hysteresis compensation. Stability analysis of the proposed ILC is presented, with the PID included in the dynamic of the piezoelectric actuator. The performance of the proposed controller is analysed through simulation and verified with experiment with a piezoelectric actuator.

Lei Liu

Papers

Discrete Composite Control of Piezoelectric Actuators for High-Speed and Precision Scanning

Development of an Approach Toward Comprehensive Identification of Hysteretic Dynamics in Piezoelectric Actuators

SVD-based Preisach hysteresis identification and composite control of piezo actuators.

Active vibration isolation based on model reference adaptive control

Compensation of hysteresis in piezoelectric actuator with iterative learning control