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Distributed generation based microgrid system could be a technically and economically viable alternative to reduce heavy pressure on existing power system transmission network. But stability is one of the main concerns for islanded mode operation of microgrid system. Voltage, current, and power of islanded microgrid system get affected by system oscillations, overshoots, and considerably large settling time to reach steady-state despite using the conventional proportional-integral-derivative (PID) controller. To mitigate these problems of islanded microgrid system, an optimal model predictive control (MPC) scheme is proposed in this article. The performance of the proposed controller is compared with the conventional PID controller which reveals that the overshoot is completely eliminated and the system oscillation is greatly reduced. Also, after implementation of the proposed MPC controller the voltage, current, and power of islanded microgrid system reaches steady-state 87.69%, 97.44%, and 97.43 % faster and rise time 83.86% faster than the conventional PID controller.

In order to keep pace with the ever increasing demand and maintain the stability of the power system, the frequency deviation and the terminal voltage variation of an electric power generating unit need to be taken care of within the shortest time span. In this paper an optimal model predictive control (MPC) scheme is proposed for providing robust control of frequency as well as the terminal voltage of a generating unit. The performance of the proposed controller is compared with the conventional proportional-integral-derivative (PID) controller, linear quadratic regulator (LQR) and the PID-LQR controller. The proposed control scheme mitigates frequency deviation ten times faster and also reinstates the terminal voltage three times faster than the existing controllers.

The design of a controller which compensates for the effects of creep, hysteresis, vibration, and cross-coupling in a piezoelectric tube scanner (PTS) is presented in this paper. The PTS is a key nanopositioning component installed in a commercial atomic force microscope (AFM) to perform scanning. The impediments to fast scanning due to PTS dynamics are: 1) the presence of mechanical resonances; 2) nonlinearities due to the piezoelectric characteristics; and 3) the cross-coupling effect between ${x}$ - and ${y}$ -axes in the PTS. In this paper, a multi-input multi-output model predictive control (MPC) scheme is designed to counteract the effects of creep, hysteresis, vibration, and cross-coupling in a PTS. Also, a damping compensator is included to suppress the vibration effect at its resonance frequency. The proposed controller achieves a high closed-loop bandwidth and significant damping of the resonant mode. To evaluate the performance improvement using the proposed control scheme, an experimental comparison with the existing AFM proportional-integral (PI) controller and a single-input single-output (SISO) MPC is conducted. Enhancement in the scanning speed up to 125 Hz is observed with the proposed controller.

An atomic force microscope (AFM) is an extremely versatile investigative tool in the field of nanotechnology, the performance of which is significantly influenced by its conventional zig-zag raster pattern scanning method. In this paper, in order to increase its imaging speed, we consider the use of a sinusoidal scanning method, i.e., a spiral scanning method with an improved model predictive control (MPC) scheme. In this approach, spirals are generated by applying waves, each with a single frequency and slowly varying amplitude, in the X-piezo (sine wave) and Y-piezo (cosine wave) of the piezoelectric tube scanner (PTS) of the AFM. As these input signals are single frequencies, the scanning can proceed faster than traditional raster scanning, without exciting the resonant mode of the PTS. The proposed MPC controller reduces the phase error between the reference position input and measured output sinusoids and provides better tracking of the reference signal. Also, a notch filter is designed and included in the feedback loop to suppress vibrations of the PTS at the resonant frequency. The experimental results show that, using the proposed method, the AFM is able to scan a 6 μm radius image within 2.04 s with a quality better than that obtained using the conventional raster pattern scanning method.

Nanotechnology is an area of modern science which deals with the control of matter at dimensions of 100 nm or less. In recent years, of all the available microscopy techniques, atomic force microscopy (AFM) has proven to be extremely versatile as an investigative tool in this field. However the performance of AFM is significantly limited by the effects of hysteresis, creep, cross-coupling, and vibration in its scanning unit, the piezoelectric tube scanner (PTS). This article presents the design and experimental implementation of a single-input single-output (SISO) model predictive control (MPC) scheme with a vibration compensator which is based on an identified model of the PTS. The proposed controller provides an AFM with the capability to achieve improved tracking and results in compensation of the nonlinear effects. The experimental results, which compare the tracking performances of the proposed controller for different reference signals, highlight the usefulness of the proposed control scheme.

An atomic force microscope (AFM) is an extremely versatile investigative tool in the field of nanotechnology, the performance of which is significantly influenced due to the nonlinear behavior of its scanning unit; i.e., the piezoelectric tube scanner (PTS). In order to increase the imaging speed of the AFM, a model predictive control (MPC) scheme is applied in both the X and Y-piezo axes of the PTS to reduce its nonlinearity effects and to improve in damping of the resonant mode. The proposed controller provides an AFM with the capability to achieve improved tracking and it results in the reduction of the hysteresis, creep, vibration, and cross-coupling effects in piezoactuators. The experimental results demonstrate the effectiveness of the proposed control scheme.

One of the key barriers to an atomic force microscope (AFM) achieving high scanning speeds is its use of the traditional zig-zag raster pattern scanning technique. In this paper, we consider the use of a high-speed spiral imaging technique with an improved multi-input multi-output (MIMO) model predictive control (MPC) scheme with a damping compensator for faster scanning by an AFM. The controller’s design is based on an identified MIMO model of the AFM’s piezoelectric tube scanner (PTS) and it achieves a higher closed-loop bandwidth, significant damping of the resonant mode of the PTS, and reduces the cross-coupling effect between the PTS’s axes. The spirals produced have particularly narrow-band frequency measures which change slowly over time, thereby making it possible for the scanner to achieve improved tracking and continuous high-speed scanning rather than being restricted to the back and forth motion of raster scanning. To evaluate the performance improvement using this proposed control scheme for spiral scanning, an experimental comparison of its scanned images with those of the open-loop condition is performed. Experimental results show that, by using the proposed method, the AFM’s scanning speed is significantly increased up to 180 Hz.

The design of a multi-input–multi-output (MIMO) model predictive control (MPC) framework for reducing errors in images scanned by an atomic force microscope (AFM) is presented. To improve the damping capability of the proposed control framework, it is augmented with a damping compensator. The MIMO form of this control framework compensates the tilted natures of the scanned images by compensating the cross-coupling effect while its augmented damping compensator reduces the vibration effect by improving damping in the resonant mode of the AFM's piezoelectric tube scanner. Experimental results using the existing AFM proportional–integral controller and single-input–single-output MPC are also presented to show the effectiveness of the MIMO MPC controller. This Letter is an extension of an authors’ earlier published work.

This paper presents the design and experimental implementation of an observer-based model predictive control scheme with a notch filter to achieve accurate tracking and fast scanning for an atomic force microscope (AFM). The proposed controller reduces the tracking error by improving the damping of the resonant modes of the AFM piezoelectric tube scanner (PTS). The design of this controller is based on an identified model of the PTS. A Kalman filter is used to obtain full-state information in the presence of position sensor noise. A comparison of the experimentally obtained scanned images using the proposed controller and the existing AFM PI controller is given. The experimental results demonstrate the efficacy of the proposed controller.

Model predictive control (MPC) is a multivariable control algorithm commonly used when tracking a reference trajectory is the primary goal. It minimizes the steady-state tracking error, increases the closed-loop bandwidth, and enables the controller to track a reference signal, the major requirements for nanopositioning applications. These capabilities motivated this research on improving the positioning performance of the piezoelectric tube scanner (PTS) in an atomic force microscope (AFM) to achieve better imaging at high scanning speed. This paper surveys the effectiveness of an MPC controller for AFM imaging by considering its different features and comparing its results with those obtained from the in-built proportional integral (PI) controller.

Since its introduction, the atomic force microscope (AFM) has developed into a ubiquitous tool for 3D imaging and manipulating objects at a nanoscale level. However, the imaging performance of AFMs is limited because of the limitations of its scanning unit, i.e., piezoelectric tube scanner (PTS). This paper addresses the design and experimental implementation of a two-input two-output (TITO) model predictive control (MPC) scheme which aims to overcome the limiting factors of the PTS in order to achieve improved 3D images. The effectiveness of the proposed method is experimentally compared with the existing AFM proportional-integral (PI) controller, the resonant controller, and the single-input single-output (SISO) MPC controller.

In this paper, we first consider the use of a spiral rather than the conventional raster scanning method for improving the imaging performance of an atomic force microscope (AFM). To generate spirals, single-frequency, slowly varying amplitude sine and cosine waves are applied to the X- and Y-piezos, respectively, of the piezoelectric tube scanner (PTS) of an AFM. To demonstrate the performance improvement with the spiral scanning method, a comparison of spiral and raster scanning techniques is presented. In each case, the closed-loop operation is performed using a multi-input multi-output (MIMO) model predictive control (MPC) scheme augmented with a vibration compensator to minimize the tracking error.

Model predictive control (MPC) refers to a class of computer control algorithms which is commonly used when tracking a reference trajectory is the primary goal. It minimizes the steady-state tracking error, increases the closed-loop bandwidth, and enables the controller to track a reference signal, the major requirements for nanopositioning applications. These capabilities of MPC controllers have motivated this research to improve the positioning performance of the piezoelectric tube scanner (PTS) for better imaging performance of an atomic force microscope (AFM). The multi-input multi-output (MIMO) form of the controller designed in this work compensates for the cross-coupling effect while the damping compensator augmented with the plant enhances its damping capability. To evaluate the performance improvement using the proposed control frame work, an experimental comparison with the existing AFM proportionalintegral (PI) controller is conducted which demonstrates that it enhances image quality for scanning speeds up to 125 Hz.

The imaging performance of an atomic force microscope (AFM) at high scanning speeds is limited due to the cross-coupling properties of its scanning unit; i.e., the piezoelectric tube scanner (PTS). In order to increase the imaging speed of an AFM, a multi-input multi-output (MIMO) model predictive control (MPC) scheme is used for the PTS to reduce its cross-coupling effect. The design of this controller is based on an identified MIMO model of the AFM PTS. Also, a damping compensator is designed and included in the feedback loop with the plant to suppress the vibration of the PTS at the resonant frequency. Experimental results confirm the efficacy of the proposed controller.

In atomic force microscopy (AFM), the dynamics and nonlinearities of its nanopositioning stage are major sources of image distortion, especially when imaging at high scanning speed. This chapter discusses the design and experimental implementation of an observer-based model predictive control (OMPC) scheme which aims to compensate for the effects of creep, hysteresis, cross-coupling, and vibration in piezoactuators in order to improve the nanopositioning of an AFM. The controller design is based on an identified model of the piezoelectric tube scanner (PTS) for which the control scheme achieves significant compensation of its creep, hysteresis, cross-coupling, and vibration effects and ensures better tracking of the reference signal. A Kalman filter is used to obtain full-state information about the plant. The experimental results illustrate the use of this proposed control scheme.

The imaging performance of an atomic force microscope (AFM) at high scanning speeds is limited due to the nonlinear behavior of its scanning unit; i.e., the piezoelectric tube scanner (PTS). In order to increase the imaging speed of the AFM, a model predictive control (MPC) scheme is applied in both the X and Y piezo axes of the PTS to reduce its nonlinearity effects and a modified MPC-Notch scheme is used to improve in damping of the resonant mode. In order to verify the performance improvement achieved by the proposed schemes, scanned images from them, the existing AFM proportional-integral (PI) controller, and an open-loop AFM system are compared.

Tracking a reference signal is one of the major problems of an atomic force microscope (AFM). This article presents the design and experimental implementation of a model predictive control (MPC) scheme, with a vibration compensator for achieving accurate tracking for an AFM at higher scanning rates. To evaluate the improvement in performance attained by this control scheme, an experimental comparison of its tracked signals against different reference signals at different scanning rates is conducted. The experimental results demonstrate the effectiveness of the proposed controller. Refereed/Peer-reviewed

In this article the design and experimental implementation of an observer based model predictive control (OMPC) scheme for active damping of the first two resonant modes of a smart structure is presented. The design of this controller is based on an identified model of the plant. A Kalman filter is used to obtain full state information. The experimental results verify the efficacy of the proposed controller Refereed/Peer-reviewed

This article presents the design and experimental implementation of an observer-based model predictive control (OMPC) scheme with a notch filter which aims to compensate for the effects of creep, hysteresis, cross-coupling, and vibration in piezoactuators in order to improve the nanopositioning of an atomic force microscope (AFM). The controller design is based on an identified model of the piezoelectric tube scanner (PTS) for which the control scheme achieves significant compensation of its creep, hysteresis, cross-coupling, and vibration effects and ensures better tracking of the reference signal. A Kalman filter is used to obtain full-state information of the plant. The experimental results exemplify the use of this proposed control scheme. Refereed/Peer-reviewed

An atomic force microscope (AFM) is an extremely versatile investigative tool in the field of nanotechnology, the performance of which is significantly influenced by its conventional zig-zag raster pattern scanning method. In this paper, we consider the use of a spiral scanning method with an improved model predictive control (MPC) scheme for its faster scanning. The proposed MPC controller reduces the phase error between the input and output sinusoids and provides better tracking of the reference signal. Also, a notch filter is designed and included in the feedback loop with the plant to suppress vibrations of the piezoelectric tube scanner (PTS) at the resonant frequency. Consequently, the proposed controller achieves a higher closed-loop bandwidth and significant damping of the resonant mode of the AFM's PTS. Experimental results show that, by using the proposed method, the AFM's scanning speed is significantly increased to up to 180 Hz and produces improved image quality. Refereed/Peer-reviewed

This paper presents the design of a model predictive control (MPC) scheme with a notch filter for reducing the tracking error of an atomic force microscope (AFM) by damping the resonant mode of the piezoelectric tube (PZT) scanner. The development of a controller for the AFM imaging and scanning speed is illustrated in this paper. Experimental results show that the proposed controller can increase the scanning speed significantly as compared with the existing PI controller.

This paper addresses the design and experimental implementation of an observer based model predictive control (OMPC) scheme for improved imaging of an atomic force microscope (AFM). An identified model of the AFM piezoelectric tube (PZT) scanner is used to design the proposed controller. A Kalman filter is used to obtain full state information and also to filter the output sensor noise. To evaluate the performance improvement using the proposed control scheme an experimental comparison has been made with scanned images between the proposed controller and the open-loop AFM images. This comparison shows the expediency of the proposed controller.

This article presents the design of a model predictive control (MPC) scheme for fast tracking and accurate scanning of an atomic force microscope (AFM). The design of this controller is based on an identified model of the AFM piezoelectric tube (PZT) scanner. Total development of the AFM imaging and scanning speed has been illustrated through this paper by proper design and implementation of the MPC controller. Experimental results show that the MPC can increase the scanning speed significantly in contrast with the existing PI controller.