Observer-based integral sliding mode control for sensorless PMSM drives using FPGA

This paper presents the design and evaluation of an observer-based integral sliding mode controller for sensorless Permanent Magnet Synchronous Motor (PMSM) drive based on the Field Programmable Gate Array (FPGA) technology. For enhancement of robustness, a flux angle estimator using an improved sliding mode observer is proposed to estimate the current and back electromotive force (EMF) as well as to derive the flux angle. These estimated values together with the computed rotor speed of the motor are fed back for the control purpose in both the current loop and the speed loop. To increase the performance of PMSM speed control, an integral sliding mode control (ISMC) is designed with integral operation to improve steady state accuracy against parameter variations and external disturbances. The developed controller has been implemented in an FPGA-based environment and the very high speed integrated circuit-hardware description language (VHDL) is adopted to show advantages of the proposed control system. By integrating the observer-based and integral sliding mode control techniques into speed control of a PMSM drive, the system performance can be substantially enhanced while improving its cost-effectiveness and reliability. The validity of the proposed approach is verified through simulation results based on Modelsim and Simulink co-simulation method. © 2013 IEEE

FPGA-based fuzzy sliding mode control for sensorless PMSM drive

This paper presents an observer-based fuzzy sliding mode controller for sensorless Permanent Magnet Synchronous Motor (PMSM) drive based on the Field Programmable Gate Array (FPGA) technology. For enhancement of robustness, a sliding mode observer (SMO) is proposed to estimate first the current and back electromotive force (EMF), then to derive the flux angle. These estimated values together with the computed rotor speed of the motor are fed back for the control purpose in both the current loop and the speed loop. To cope with dynamic uncertainty and external load, a fuzzy sliding mode control (FSMC) is designed by incorporating a fuzzy inference mechanism into the proposed sliding mode control scheme to tune the discontinunous gain in the speed control loop. An FPGA chip is designed for implementing the vector-controlled current loop as well as the speed control loop. The very high speed integrated circuit-hardware description language (VHDL) is adopted to describe advantageous behaviors of the proposed control system. By integrating advantages of the sensorless and fuzzy sliding mode control techniques into the speed controller of a PMSM drive, its performance can be substantially enhanced while improving cost-effectiveness and reliability. The validity of the proposed approach is verified through results based on the VDHL Modelsim and Simulink co-simulation method. © 2012 IEEE

FPGA-based cooperative control of indoor multiple robots

Cooperative control of a group of mobile robots remains a challenging topic in robotics. In the emerging trend of ubiquitous robotics, real-time control using vision-based surveillance strategies requires embedded systems with limited computational performance and energy saving. In this paper, a control-system-on-chip architecture is developed for coordination of control of an indoor robotic formation by using a field programmable gate array (FPGA) chip. The prototype features capabilities of colour-based motion object tracking, inter-robot distance estimation, trajectory estimation, velocity control, formation initialisation and maintenance. All algorithms are implemented in pure register-transfer and gate-level circuits with localisation from a global monocular camera. Experiment results are included for miniature robots deployed in a line formation. The FPGA's resource usage and power consumption are analysed to show efficiency of the proposed approach. © 2012 Inderscience Enterprises Ltd

FPGA-based sensorless PMSM speed control using reduced-order extended kalman filters

© 2014 IEEE. This paper presents the design and implementation of a field-programmable gate array (FPGA)-based architecture for the speed control of sensorless permanent-magnet synchronous motor (PMSM) drives. For the reduction of computation resources, as well as accuracy improvement in the rotor position estimation, a parallel reduced-order extended Kalman filter (EKF) is proposed in this work. Compared with an EKF, the system order is reduced and the iteration process is greatly simplified, resulting in significant savings of resource utility, while maintaining high estimation performance. The whole control system includes a current-control-and-coordinate-transformation unit, a proportional-integral (PI) speed controller, and other accessory modules, all implemented in a single FPGA chip. A hardware description language is adopted to describe advantageous features of the proposed control system. Moreover, the finite-state-machine method is applied with the purpose to reduce logic elements used in the FPGA chip. The validity of the approach is verified through simulation based on the Modelsim/Simulink cosimulation method. Finally, experimental results are obtained on an FPGA platform with an inverter-fed PMSM to show the feasibility and effectiveness of the proposed system-on-programmable-chip for PMSM drives

FPGA-based sensorless PMSM speed control using adaptive extended Kalman filter

© 2015 IEEE. This paper presents the design and implementation of an adaptive extended Kalman filter (EKF) for the sensorless Permanent Magnet Synchronous Motor (PMSM) on a Field Programmable Gate Array (FPGA) chip. The rotor position and speed of the motor are estimated by the adaptive EKF and their estimates are then used in vector control of the PMSM. Most EKF techniques for state estimation rely on fixed values of the state and measurement noise covariance matrices. In many practical applications, an a priori assumption of these matrices is often inadequate and it is desirable to tune online the process noise covariance to improve the filtering performance. For this, improved EKF versions can be obtained by incorporating an adjustment mechanism of the noise covariances into the filter. The adaptive EKF is, therefore, a promising estimator for sensorless PMSM drives with more accurate estimation features, provided it is feasible in implementation. Here, for realization of the PMSM sensorless control using the system-on-programmable-chip technology, high speed arithmetic functions and pipelining are employed in the FPGA implementation. The finite state machine (FSM) method is also used to facilitate the execution timing and chip design. The co-simulation of Modelsim/Simulink shows the effectiveness of the adaptive EKF-based PMSM speed estimation

FPGA sensorless PMSM drive with adaptive fading extended Kalman filtering

© 2014 IEEE. This paper addresses the design and implementation of an Adaptive Fading Extended Kaiman Filter (AF-EKF) for the sensorless Permanent Magnet Synchronous Motor (PMSM) on a Field Programmable Gate Array (FPGA) chip. The rotor position and speed of the motor are estimated by the implemented AF-EKF and their estimates are then used in vector control of the PMSM. In conventional Kaiman filtering, abrupt state changes may not be tracked adequately since sudden variations may seriously affect the auto-correlation Gaussian property of white noise in the filter residuals. For this, the AF-EKF has been developed to recover the estimation results in events of frequent and sharp state jumps. The AF-EKF is, therefore, a promising estimator for PMSM drives that are subject to frequently-varying loads speed commands. Here, for realization of the PMSM sensorless control using the system-on-programmable-chip technology, high-speed arithmetic functions and pipelining are employed in the FPGA implementation. The finite state machine method is also used to facilitate the execution timing and chip design. The co-simulation of Modelsim/Simulink shows effectiveness of the proposed chip-based AF-EKF PMSM speed estimation

FPGA-based control architecture integration for multiple-axis tracking motion systems

This paper addresses the integration of a multi-loop PI and neural fuzzy control system for multiple-axis motion positioning and tracking via the use of the Field Programmable Gate Array (FPGA) technology. The controlled plant here is an X-Y table driven by permanent magnet linear synchronous motors. The control system comprises two programmable servo-control systems for both axes, each includes a motion planner, a PI speed controller in the inner loop and a neural fuzzy controller (NFC) in the position loop. Here, to increase the tracking performance in dealing with unmodelled dynamics and cross-axis interferences, the NFC is designed by using a radial basis function neural network in combination with a parameter adjusting mechanism. The very high speed integrated circuit-hardware description language (VHDL) is adopted to describe advantageous behaviors of the proposed control system. To implement the whole control paradigm, the FPGA chip is developed in Quartus II and Nios II software environment, provided by Altera for analysis and synthesis of VHDL designs. Simulation results of the software/hardware co-design have verified the high performance and effectiveness of the proposed chip-based control system in positioning and trajectory tracking for the X-Y table motion. © 2011 IEEE

Robust exponential stabilization of underactuated mechanical systems in the presence of bounded disturbances using sliding mode control

This article addresses the robust exponential stabilization problem of underactuated mechanical systems in the presence of bounded external disturbances using sliding mode control. Based on the Lyapunov method, a sufficient condition for the existence of the smallest possible ball which bounds the reduced-order sliding mode dynamics, is first derived in terms of linear matrix inequality (LMI). A sliding mode controller is then synthesized to guarantee that system state trajectories are exponentially convergent to another ball with a prespecified convergence rate. A case study of the Pendubot is provided to illustrate the effectiveness of the proposed approach. © 2013 IEEE

FPGA-based sensorless PMSM drive using parallel reduced-order Extended Kalman Filter

This paper presents the design and evaluation of a Field Programmable Gate Array (FPGA)-based speed sensorless controller for Permanent Magnet Synchronous Motor (PMSM). The estimation of the rotor position and speed is achieved by using a parallel reduced-order Extended Kalman Filter (EKF) to alleviate the need of physical sensors. Compared with the traditional method of EKF, the system order is reduced, the process of iteration of speed estimation algorithm is greatly simplified and it is easy to realize the digital system. To achieve this objective, a comparison is made between the parallel reduced-order EKF, full-order EKF and sliding mode observer (SMO). The developed controller has been implemented in a FPGA-based environment and the very high speed integrated circuit-hardware description language (VHDL) is adopted to describe advantageous features of the proposed control system. The validity of the approach is verified through simulation results based on the Modelsim/Simulink co-simulation method. © 2012 IEEE

Improved reachable set bounding for linear systems with discrete and distributed delays

This paper addresses the problem of reachable set bounding for linear systems in the presence of both discrete and distributed delays. The time delay is assumed to be differentiable and vary within an interval. By using the Lyapunov-Krasovskii approach and delay decomposition technique, improved delay-dependent conditions for the existence of an ellipsoid-based bound of reachable sets of the system trajectories are derived in terms of matrix inequalities. Here, the new idea is to minimize the ellipsoids' projection distances on each axis with different exponential convergence rates, instead of minimizing the ellipsoidal radius with a single exponential rate. A smaller bound can thus be obtained from the intersection of these ellipsoids. The effectiveness of the proposed approach is illustrated by a numerical example. © 2012 IEEE