A digital PID controller for real time and multi loop control: a comparative study

Samet, L.; Masmoudi, N.; Kharrat, Maher; Kamoun, Lotfı

doi:10.1109/icecs.1998.813324

Cited by 37 publications

(18 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Nevertheless, the whole architecture will deliver much more interesting results if combined with an optimized PID. The second work [3] proposes serial, parallel, and mixed PID architectures incorporating different number (1-3) of multiplication cores. High power consumption, even with the serial architecture, and complex control-part are the two major shortcomings of this proposal.…”

Section: Background and Motivationmentioning

confidence: 99%

High-Speed and Low-Power PID Structures for Embedded Applications

Oudjida

Chaillet

Liacha

et al. 2011

Integrated Circuit and System Design. Power and Timing Modeling, Optimization, and Simulation

View full text Add to dashboard Cite

Section: Background and Motivationmentioning

confidence: 99%

High-Speed and Low-Power PID Structures for Embedded Applications

Oudjida

Chaillet

Liacha

et al. 2011

Integrated Circuit and System Design. Power and Timing Modeling, Optimization, and Simulation

View full text Add to dashboard Cite

“…The practice of using FPGAs to implement control theory has been pursued since the 1990's, which was the point at which it was first feasible to use these devices for control applications [Gwaltney et al 2002]. Examples of research implementing PIDs on FPGAs are Samet et al [1998] where various architectures of PIDs are tested on earlier FPGAs. In Mic et al [2008] an FPGA is used along with Matlab/Simulink to design PIDs on FPGAs for motor control.…”

Section: Implementing Pids In Control Systemsmentioning

confidence: 99%

Hardware architectural support for control systems and sensor processing

Vyas

Gupte

Gill

et al. 2013

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

The field of modern control theory and the systems used to implement these controls have shown rapid development over the last 50 years. It was often the case that those developing control algorithms could assume the computing medium was solely dedicated to the task of controlling a plant, for example, the control algorithm being implemented in software on a dedicated Digital Signal Processor (DSP), or implemented in hardware using a simple dedicated Programmable Logic Device (PLD). As time progressed, the drive to place more system functionality in a single component (reducing power, cost, and increasing reliability) has made this assumption less often true. Thus, it has been pointed out by some experts in the field of control theory (e.g., Astrom) that those developing control algorithms must take into account the effects of running their algorithms on systems that will be shared with other tasks. One aspect of the work presented in this article is a hardware architecture that allows control developers to maintain this simplifying assumption. We focus specifically on the Proportional-Integral-Derivative (PID) controller. An on-chip coprocessor has been implemented that can scale to support servicing hundreds of plants, while maintaining microsecond-level response times, tight deterministic control loop timing, and allowing the main processor to service noncontrol tasks.In order to control a plant, the controller needs information about the plant's state. Typically this information is obtained from sensors with which the plant has been instrumented. There are a number of common computations that may be performed on this sensor data before being presented to the controller (e.g., averaging and thresholding). Thus in addition to supporting PID algorithms, we have developed a Sensor Processing Unit (SPU) that off-loads these common sensor processing tasks from the main processor.We have prototyped our ideas using Field Programmable Gate Array (FPGA) technology. Through our experimental results, we show our PID execution unit gives orders of magnitude improvement in response time when servicing many plants, as compared to a standard general software implementation. We also show that the SPU scales much better than a general software implementation. In addition, these execution units allow the simplifying assumption of dedicated computing medium to hold for control algorithm development.

show abstract

“…In control theory applications, closed-loop algorithms have been studied and implemented in FPGA's. In [6] a parallel PID design is used to completely control a wheelchair; in [7] different PID implementations in reconfigurable hardware are evaluated and used. A parallel PID algorithm with fuzzy gain conditioner is proposed and tested in [8].…”

Section: Previous Workmentioning

confidence: 99%

FPGA-based Controller for Haptic Devices

Galvan

Botturi

Fiorini

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Teleoperation with force feedback is a complex task and a good haptic device is a key element. In this paper we present an innovative hardware/software structure used to control an actuated 6 dof joystick in a teleoperation task. To increase speed and reliability, parts of the kinematic calculation are embedded into the joystick controller. To implement this idea we used an FPGA to handle both the low level tasks and the algorithmic part of the approach. This speedup does not preclude the possibility of changing the control strategies, the parameters and the feedback calculations as well, necessary to carry out experiments about human perception. Thus the need of flexibility and performance, and the choice of an FPGA. We tested the setup proposed in a real teleoperation task within our software framework (Penelope) collecting data of speed, precision and reliability.

show abstract

A digital PID controller for real time and multi loop control: a comparative study

Cited by 37 publications

References 4 publications

High-Speed and Low-Power PID Structures for Embedded Applications

High-Speed and Low-Power PID Structures for Embedded Applications

Hardware architectural support for control systems and sensor processing

FPGA-based Controller for Haptic Devices

Contact Info

Product

Resources

About