A Novel Micro-positioning Controller for Piezoelectric Actuators

As a key technology for autonomous underwater operations, precise tracking control in tight space environments is a great challenge. With the aid of high maneuverability of the underwater bionic robot, this article proposes an integrated tracking control framework for a robotic dolphin to move through narrow areas, including top-level planning, middle-level tracking, and bottom-level control allocation. First, a nonlinear model predictive control-based planning method is presented with full consideration of tracking accuracy and obstacle avoidance safety. Second, in order to improve the anti-interference ability, we derive a nonlinear path tracking control law by combining the backstepping technique with a nonlinear disturbance observer. More importantly, through hydrodynamic analysis of the bionic multimodal motions under flippers and flukes, a fuzzy-based nonlinear control allocation system is particularly adopted to convert calculated control forces into bionic motion parameters. Finally, extensive simulations and aquatic experiments are conducted, and the obtained results validate the effectiveness of proposed methods, providing a new idea to further ocean exploration.

This paper proposes a modified sliding mode controller with proportion-integral (Pl)-based saturation (PISSMC) for nano-positioning of Piezoelectric Actuators (PEAs). Based on the sliding mode theory, the controller can consider hysteresis as the uncertainty of the system, which the non-linearities of hysteresis and model imperfection can be processed to achieve precise positioning and tracking control. The PI term of this controller can decrease the steady-state error of the system and alleviate the chattering of the discontinuous part of the Sliding Mode Controller (SMC). Further, as the only measurable information is the position state, a high-gain observer is adopted to estimate the other states. The designed controller employs a linear PEA system as parameters estimation of the model to estimate the control gain and compensate for the process non-linearity. The robust stability of the PISSMC is proved through a Lyapunov stability analysis. Experimental results demonstrate that compared with the traditional SMC, the proposed controller can accomplish better control performance, such as more accurate resolution, less steady-state error and slighter chattering.

This paper is to develop an optimal electro-hydraulic dual-shaking table system with high waveform replication precision. The parameters of hydraulic cylinders, servo valves, hydraulic supply power and gravity balance system are designed and optimized in detail. To improve synchronization and tracking control precision, a hybrid control strategy is proposed. The cross-coupled control using a novel based on sliding mode control based on adaptive reaching law (ASMC), which can adaptively tune the parameters of sliding mode control (SMC), is proposed to reduce the synchronization error. To improve the tracking performance, the observer-based inverse control scheme combining the feed-forward inverse model controller and disturbance observer is proposed. The system model is identified applying the recursive least squares (RLS) algorithm and then the feed-forward inverse controller is designed based on zero phase error tracking controller (ZPETC) technique. To compensate disturbance and model errors, disturbance observer is used cooperating with the designed inverse controller. The combination of the novel ASMC cross-coupled controller and proposed observer-based inverse controller can improve the control precision noticeably. The dual-shaking table experiment system is built and various experiments are performed. The experimental results indicate that the developed system with the proposed hybrid control strategy is feasible and efficient and can reduce the tracking errors to 25% and synchronization error to 16% compared with traditional control schemes.

In this paper, the hysteresis modeling and compensation are carried out and verified for a piezo-driven XY parallel micropositioning stage aiming at a sub-micron precise motion tracking control. Specifically, inverse modified Prandtl-Ishlinskii (MPI) model-based feedforward in combination with a proportional-integral-derivative (PID) feedback control algorithm is implemented for the real-time control. The MPI model is identified by optimizing the weight parameters through particle swarm optimization (PSO) to match the model output to experimental data. For the purpose of comparisons, a feedforward controller using the inverse MPI model solely is realized as well. The performance of feedforward plus feedback over stand-alone feedforward control is examined by experimental studies conducted on the prototype micropositioning stage. Results show that the combined control scheme can reduce the nonsymmetric hysteresis to a negligible level and produce a sub-micron accuracy motion tracking, which provides a sound base of practical control of the micropositioning system for micro/nano scale manipulation.

Nowadays, piezoelectric actuators (PA) are used in fast power actuations and high power applications as requested in machine tools or helicopters flap applications. Regarding to the low power capability and high loss ratios of linear amplifiers, Switching Power Amplifiers (SA75X) is designed by Cedrat Technologies to drive piezoelectric actuators in such applications. The switching technique (up to 100 kHz) allows high current peaks required by impulse or by high frequency applications on large piezoelectric actuators (or actuators in parallel) and allows energy harvesting. Output voltage, current, and actuator position are monitored via controller board and using sensor feedbacks. Furthermore, the developed system (SA75X+actuators) can operate in open or closed loop system with an output signal frequency up to 1 kHz. The OEM version of the powerful switching amplifier (SA75D:20Amax) has a dimensions of 100x100x100mm, i.e. 1 litter, and a weight of 850g.The power ratio of this amplifier is thus of 1.5kVA/L and 1.75kVA/Kg. The output power capability, signal noise ratios, and control robustness of the SA75X justifies the proposed solution Theoretical, simulation, and experimental tests of the SA75D (20Amax) will be presented to improve the amplifier performances

The electro-hydraulic proportional position servo system is a kind of highly non-linear and time-varying system as well as parameter uncertainties. It is often difficult to achieve satisfactory control results with the traditional control methods. Considering that the adaptive neural network PID control method has the characteristics of online learning and adjustment PID control parameters adaptively, this paper puts forward to adopt BP-PID control method for the position servo control of electro-hydraulic proportional system. An online adaptive BP-PID controller is designed. The simulation model of the system is established based on Simulink platform. The step response and Sinusoidal tracking characteristics are researched for electro-hydraulic proportional position servo system by using traditional PID and BP-PID control algorithms through simulations and experiments. The results show that BP-PID has a strong ability of online learning and self-tuning PID parameters. Compared with the traditional PID control method, the BP-PID control has strong self-adaptability and robustness, and can significantly improve the step response speed and tracking control precision.

To enhance the performance for high-speed tracking control of a piezoelectric tube actuator (PTA), an improved direct inverse rate-dependent PI model is obtained in this paper, and then adopted to design a practical feedforward controller achieving high-speed tracking control for a high-frequency trajectory with strong robustness. Specifically, based on the Prandtl-Ishlinskii (PI) model, an improved direct rate-dependent inverse model is set up for the PTA, with a polynomial function module introduced to eliminate the influence caused by the structure nonlinearity. Then, considering the features of the PTA structure, some preprocessing procedure is proposed to handle the collected experimental data, with the results utilized to identify all the unknown parameters over a wide bandwidth. Based on the obtained model, a practical feedforward controller, which presents the advantages of high-speed response, simple structure and convenient implementation, is then designed to enable the PTA to track high-frequency trajectories with satisfactory precision. Some experimental results are provided, which clearly demonstrate the high precision of the constructed/identified model, and the satisfactory performance of the proposed practical feedforward tracking control law.

Piezoelectric actuator (PEA) is one of the key component in micro/nano manipulation equipment. However, the inherent hysteresis significantly limits its motion accuracy. In this paper, a Prandtl-Ishlinskii (PI) based feedforward and feedback compound control strategy is designed to eliminate the hysteretic nonlinearity of PEA, and thus linearizing the input/output relationship. An inverse hysteresis model is directly identified and validated using the open loop characteristics of the PEA. The inverse hysteresis model is used as the feedforward compensator. In order to further improve the performance of the PEA, a feedforward and feedback compound control strategy is also designed and tested. A PEA equipped with strain gauges is selected in the experimental investigation. Experimental results show that the hysteresis can be successfully compensated using only feedforward control, and better performance is achieved using the feedforward and feedback compound control.

Articulating crane (AC) is used in various industrial activities. The articulated multisection arm exacerbates nonlinearities and uncertainties, making the precise tracking control challenging. This study proposes an adaptive prescribed performance tracking control (APPTC) for AC to robustly fulfill the task of precise tracking control, with adaptation to resist time-variant uncertainties, whose bounds are unknown but lie in prescribed fuzzy sets. Particularly, a state transformation is applied to simultaneously track the desired trajectory and satisfy the prescribed performance. Adopting the fuzzy set theory to describe uncertainties, APPTC does not invoke any IF-THEN fuzzy rules. There is no linearizations, or nonlinear cancelation for APPTC, thus making it approximation free. The performance of the controlled AC is twofold. First, deterministic performance in fulfilling the control task is ensured by the Lyapunov analysis using uniform boundedness and uniform ultimate boundedness. Second, fuzzy-based performance is further improved by an optimal design, which seeks the optima of control parameters by formulating a two-player Nash game. The existence of Nash equilibrium is theoretically proved, and its acquisition process is given. The simulation results are provided for validations. This is the first endeavor that explores the precise tracking control for fuzzy AC.

Adaptive sliding mode control with hysteresis compensation-based neuroevolution for motion tracking of piezoelectric actuator

The intrinsic hysteresis behavior of piezoelectric material limits the tracking control accuracy of the actuators. This paper describes a tracking control method for piezoelectric actuators based on the combination of feedforward and feedback loops. The hysteresis of piezoelectric actuators is linearized in feedforward loop with an inverse hysteresis model based on a neural network. The number of parameters in the neural network based inverse model is relatively small and the parameters are easy to identify. The feedback loop is used to reduce the accumulated error produced by the inverse hysteresis model. The experimental results show that the accuracy is significantly improved in tracking control by using the combination of feedback and feedforward control.

Nowadays, due to advantages of maneuverability, portability and low cost, the mini quadrotor unmanned aerial vehicle (UAV) catches much attention. In some special applications such as narrow space search, stealth detection and cooperative detection in huge region, the mini quadrotor UAV is more suitable than a big one. However, light weight and mini size lead to phenomenon that it is hard for mini quadrotor UAV to use complex control method. Besides, the performance of wind resistant is significant for practicability. In this paper, the under-actuated dynamics, strong nonlinear and coupling characteristics has been analyzed. After that, we propose a three-dimensional fuzzy PID control method for stabilizing attitude control and precise trajectory tracking control. The error, derivative of the error and the second order derivative of the error are the three-dimensional inputs of the controller. After using Simulink, the result shows that the proposed control method realizes precise trajectory tracking and robust attitude control. Furthermore, a kind of turbulent wind field, generated based on Dryden model, is added to disturb the control process. This study shows that three-dimensional fuzzy control method is better than the conventional fuzzy PID method under impact of wind disturbance. Finally, the results prove that our proposed control method has both excellent static and dynamic characteristics.

In this paper we present a new tracking control method for holographic digital data storage systems. Holographic data storage systems that use disk media need a different tracking method from those of optical and hard disk drives. Here we present the design and implementation of the controller. Due to the intermittent characteristics of the tracking error signal (TES), the tracking controller is designed to regulate the tracking error only while valid TES is generated. Since the valid TES appears intermittently, we use a feedforward controller while the TES is not valid. Furthermore, the feedback control and feedforward control are mode switched depending on the radio frequency sum signal level. We also show the stability of the closed loop system employing the mode switching controller. Experimental results show the effectiveness of the proposed tracking control algorithm. For a plusmn100 mum repeatable runout at 1 Hz, we were able to reduce the TES to 3.13 mum (1sigma) with feedforward mode switching control.

This paper investigates network-based output tracking control for a T-S fuzzy system that can not be stabilized by a nondelayed fuzzy static output feedback controller, but can be stabilized by a delayed fuzzy static output feedback controller. By intentionally introducing a communication network that produces proper network-induced delays in the feedback control loop, a stable and satisfactory tracking control can be ensured for the T-S fuzzy system. Due to the presence of network-induced delays, the fuzzy system and the fuzzy tracking controller operate in an asynchronous way. Taking the asynchronous operation and network-induced delays into consideration, the network-based tracking control system is modeled as an asynchronous T-S fuzzy system with an interval time-varying delay. A new delay-dependent criterion for L2 -gain tracking performance is derived by using the deviation bounds of asynchronous normalized membership functions and a complete Lyapunov-Krasovskii functional. Applying a particle swarm optimization technique with the feasibility of the derived criterion, a novel design algorithm is presented to determine the minimum L2 -gain tracking performance and control gains simultaneously. The effectiveness of the proposed method is illustrated by performing network-based output tracking control of a Duffing-Van der Pol's oscillator.

This paper deals with a hybrid actuator composed by a piezo and a hydraulic part and with a Robust Model Predictive Control (RMPC) structure combined with a feedforward control in camless engine motor applications. A combination between a feedforward control based on an inversion of the system and an MPC structure is considered. The idea of the conception of the proposed new actuator is to use the advantages of both, the high precision of the piezo and the force of the hydraulic part. In fact, piezoelectric actuators (PEAs) are commonly used for precision positionings, despite PEAs present nonlinearities, such as hysteresis, saturations, and creep. In the control problem such nonlinearities must be taken into account. In this paper the Preisach dynamic model with the above mentioned nonlinearities is considered together with a feedforward control combined with a RMPC. Simulations of the implementation with real data are shown.