Proportional Integral Controller Tuning Research Articles

Tuning of Robust Distant Downstream PI Controllers for an Irrigation Canal Pool. II: Implementation Issues

Based on the companion paper results, this paper presents a robust tuning method to tune a proportional integral (PI) controller that fulfills the design requirements for a single pool with different hydraulic conditions. The robust PI controller parameters are obtained analytically as a function of the physical parameters of the canal pool. Important implementation issues are also considered. Rules are provided for the sampling time selection in order to recover the continuous-time performance. When the sampling time is imposed, it has to be included in the controller design, by modifying the delay of the system. A simple way is proposed to take account of the gate opening as control action variable, instead of the upstream discharge. This robust PI tuning method is evaluated by simulation on a full nonlinear model of two different canal pools for different flow conditions and different implementations: continuous-time control, discrete-time control, using the discharge or the gate opening as control action variable. Simulation results show that the method leads to efficient realistic PI controllers for a canal pool.

Tuning of Robust Distant Downstream PI Controllers for an Irrigation Canal Pool. I: Theory

The paper proposes a new method to tune robust distant downstream proportional integral (PI) controllers for an irrigation canal pool. The method emphasizes the role of gain and phase margins in the controller design, by linking the selection of these robustness indicators to the time domain specifications. This leads to link the frequency domain approach used by automatic control engineers to the time domain approach used by hydraulic engineers. The maximum error corresponding to an unpredicted perturbation is shown to be directly linked to the gain margin and the settling time to the phase margin of the controlled system. The tuning method gives analytical expressions for the controller parameters as function of physical parameters of the canal pool in order to satisfy desired performance requirements. The model is first expressed in terms of dimensionless variables, in order to get generic tuning formulas. The dimensionless PI coefficients are then expressed as functions of time-domain performance requirements. The PI tuning method is evaluated by simulation on a full nonlinear model for a canal pool taken from the ASCE test cases.

An artificial neural network for online tuning of genetic algorithm-based PI controller for interior permanent magnet synchronous motor drive

An artificial neural network (ANN) for online tuning of a genetic algorithm based PI controller for interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating various uncertainties. At each operating condition a genetic algorithm (GA) is used to optimize proportional-integral (PI) controller parameters in a closed loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A radial basis function network (RBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed controller is successfully implemented in real-time using a digital signal processor board DS1102 for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed approach is found to be a robust controller for application in the IPMSM drive

Comparison of PI Controller Tuning Methods

The development of model-based methods for tuning proportional-integral (PI) and proportional-integral-derivative (PID) controllers is a topic of renewed research interest. A number of techniques have appeared in the last five years aimed at improving upon the standard λ-tuning or direct synthesis (DS) approaches. This paper compares the Skogestad internal model control (SIMC), direct synthesis for disturbance rejection (DS-d), and Wang-Shao (WS) tuning algorithms with the IMC improved PI technique as implemented on first-order-plus-deadtime systems. The main objective was to assess the relative control effort and robustness of these proportional-integral controllers when tuned for the same level of performance. Recommendations were provided for selecting the most appropriate tuning method for a given application based upon the primary function of the feedback loop (servo versus regulatory, etc.) and the plant deadtime-to-time constant ratio.

A Summary of PI and PID Controller Tuning Rules for Processes with Time Delay. Part 1: PI Controller Tuning Rules

The ability of proportional integral (PI) and proportional integral derivative (PID) controllers to compensate many practical industrial processes has led to their wide acceptance in industrial applications. The requirement to choose either two or three controller parameters is perhaps most easily done using tuning rules. A summary of tuning rules for the PI control of single input, single output (SISO) processes with time delay is provided in this paper.

A Summary of PI and PID Controller Tuning Rules for Processes with Time Delay. Part 2: PID Controller Tuning Rules

The ability of proportional integral (PI) and proportional integral derivative (PID) controllers to compensate many practical industrial processes has led to their wide acceptance in industrial applications. The requirement to choose either two or three controller parameters is perhaps most easily done using tuning rules. A summary of tuning rules for the PID control of single input, single output (SISO) processes with time delay is provided in this paper.