Article: FPGA implementation of linear model predictive controller for real-time position control of DC motor Journal: International Journal of Circuits and Architecture Design (IJCAD) 2015 Vol.1 No.4 pp.281 - 294 Abstract: Model predictive control (MPC) is a predictive class of control algorithm which has been widely adopted for slow dynamic, constrained, multi-variable process control problems. The applicability of MPC for real-time control is restricted due to the associated computational complexity of quadratic programming (QP) problem and the choice of appropriate computing platforms. MPC can be formulated as a standard QP problem and according to receding horizon control strategy, in order to get optimal control signal to apply to the system, in each discrete time step, a QP problem is to be solved online. In order to meet high sampling frequency demand of real-time control applications, in this paper, we propose a novel accelerated field programmable gate array (FPGA)-based customised architecture for active set method (ASM)-based QP solver to implement linear MPC. The approach is implemented successfully on Xilinx's Virtex-4 FPGA and demonstrated practically by applying MPC to Quansers QET DC servomotor position control plant. From experimentation; it is observed that, FPGA-based implementation occupies 35% of Virtex-4 area and achieves 500 µs sample time. Inderscience Publishers - linking academia, business and industry through research

Title: FPGA implementation of linear model predictive controller for real-time position control of DC motor

Authors: Dayaram Sonawane; Deepak Ingole; Vihangkumar Naik

Addresses: Department of Instrumentation and Control, College of Engineering, Pune, India ' Department of Instrumentation and Control, College of Engineering, Pune, India ' Department of Instrumentation and Control, College of Engineering, Pune, India

Abstract: Model predictive control (MPC) is a predictive class of control algorithm which has been widely adopted for slow dynamic, constrained, multi-variable process control problems. The applicability of MPC for real-time control is restricted due to the associated computational complexity of quadratic programming (QP) problem and the choice of appropriate computing platforms. MPC can be formulated as a standard QP problem and according to receding horizon control strategy, in order to get optimal control signal to apply to the system, in each discrete time step, a QP problem is to be solved online. In order to meet high sampling frequency demand of real-time control applications, in this paper, we propose a novel accelerated field programmable gate array (FPGA)-based customised architecture for active set method (ASM)-based QP solver to implement linear MPC. The approach is implemented successfully on Xilinx's Virtex-4 FPGA and demonstrated practically by applying MPC to Quansers QET DC servomotor position control plant. From experimentation; it is observed that, FPGA-based implementation occupies 35% of Virtex-4 area and achieves 500 µs sample time.

Keywords: model predictive control; linear MPC; quadratic programming; QP solver; DC motor control; FPGA implementation; field programmable gate arrays; position control; DC motors; sampling frequency; active set method; ASM; servomotors.

DOI: 10.1504/IJCAD.2015.072609

International Journal of Circuits and Architecture Design, 2015 Vol.1 No.4, pp.281 - 294

Received: 19 Jun 2014
Accepted: 28 Dec 2014
Published online: 22 Oct 2015 *

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Title: FPGA implementation of linear model predictive controller for real-time position control of DC motor

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