Weng Khuen Ho

Automatic Tuning and Adaptation for PID Controllers—A Survey

Adaptive techniques such as gain scheduling, automatic tuning and continuous adaptation have been used in industrial single-loop controllers for about ten years. This paper gives a survey of the different adaptive techniques, the underlying process models and control designs. The paper ends with an overview of industrial adaptive single-loop controllers.

Tuning of PID controllers based on gain and phase margin specifications

Abstract Simple formulae are derived to tune/design the PI and PID controllers to meet user-specified gain margin and phase margin. These formulae are particularly useful in the context of adaptive control and auto-tuning, where the controller parameters have to be calculated on-line. The results in this paper can be used to predict the achievable rise time of the closed-loop system, which is useful for self-diagnosis—a desirable feature of ‘intelligent’ controllers. New insights into the internal model control design for the PID controller are also given.

Towards intelligent PID control

Abstract Autotuners for PID controllers have been commercially available since 1981. These controllers automate some tasks normally performed by an instrument engineer. The autotuners include methods for extracting process dynamics from experiments and control design methods. They may be able to decide when to use PI or PID control. To make systems with a higher degree of automation it is desirable to also automate tasks normally performed by process engineers. To do so, it is necessary to provide the controllers with reasoning capabilities. This seems technically feasible with the increased computing power that is now available in single-loop controllers. This paper describes some features that may be included in the next generation of PID controllers.

A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization

In this paper, a new memetic algorithm (MA) for multiobjective (MO) optimization is proposed, which combines the global search ability of particle swarm optimization with a synchronous local search heuristic for directed local fine-tuning. A new particle updating strategy is proposed based upon the concept of fuzzy global-best to deal with the problem of premature convergence and diversity maintenance within the swarm. The proposed features are examined to show their individual and combined effects in MO optimization. The comparative study shows the effectiveness of the proposed MA, which produces solution sets that are highly competitive in terms of convergence, diversity, and distribution

On solving multiobjective bin packing problems using evolutionary particle swarm optimization

The bin packing problem is widely found in applications such as loading of tractor trailer trucks, cargo airplanes and ships, where a balanced load provides better fuel efficiency and safer ride. In these applications, there are often conflicting criteria to be satisfied, i.e., to minimize the bins used and to balance the load of each bin, subject to a number of practical constraints. Unlike existing studies that only consider the issue of minimum bins, a multiobjective two-dimensional mathematical model for bin packing problems with multiple constraints (MOBPP-2D) is formulated in this paper. To solve MOBPP-2D problems, a multiobjective evolutionary particle swarm optimization algorithm (MOEPSO) is proposed. Without the need of combining both objectives into a composite scalar weighting function, MOEPSO incorporates the concept of Paretos optimality to evolve a family of solutions along the trade-off surface. Extensive numerical investigations are performed on various test instances, and their performances are compared both quantitatively and statistically with other optimization methods to illustrate the effectiveness and efficiency of MOEPSO in solving multiobjective bin packing problems.

Optimal Gain and Phase Margin Tuning for PID Controllers

Simple tuning formulas for the design of the PID controllers to satisfy both robustness and performance requirements are given. Robust control design is an area of intensive research. The PID formulas given in this paper are simple and can be easily adopted by the industry.

Brief Relay auto-tuning of PID controllers using iterative feedback tuning

In this paper, ideas from iterative feedback tuning (IFT) are incorporated into relay auto-tuning of the proportional-plus-integral-plus-derivative (PID) controller. The PID controller is auto-tuned to give specified phase margin and bandwidth. Good tuning performance according to the specified bandwidth and phase margin can be obtained and the limitation of the standard relay auto-tuning technique using a version of Ziegler-Nichols formula can be eliminated. Furthermore, by using common modelling assumptions for the relay system, some of the required derivatives in the IFT algorithm can be derived analytically. The algorithm was tested in the laboratory on a coupled tank and good tuning result was demonstrated.

Relay auto-tuning in the presence of static load disturbance

Abstract Static load disturbances during the relay tuning experiment introduce errors in the estimates of the ultimate gain and ultimate period. This paper shows how an automatic bias can be used to overcome the problem.

Automatic Tuning and Adaptation for PID Controllers - A Survey

Adaptive techniques such as gain scheduling, automatic tuning and continuous adaptation have been used in industrial single-loop controllers for about ten years. This paper gives a survey of the different adaptive techniques, the underlying process models and control designs. The paper ends with an overview of industrial adaptive single-loop controllers.

Tuning of PI controllers based on gain and phase margin specifications

The authors examine a class of tuning formula associated with the relay auto-tuning, cross correlation auto-tuning and other self-tuning PI/PID controllers. These methods measure the ultimate gain, ultimate period, simplified process model parameters e.g. gain, time constant and dead-time or some related frequency response data e.g. a point on the Nyquist curve. The estimates are then used in the tuning formulae. It has been found from extensive simulation that the modified Ziegler-Nichols formulae give good responses over a wide range of process dynamics. A more general approach is to use the combined phase and gain margins approach. However, the method to date could only achieve a compromise in phase and gain margins by designing to move the compensated Nyquist curve to pass through a specified design point. The performance of this tuning formula, however, is found to be too conservative especially when the dead time is large. The authors propose an analytical method to tune/design the PI controller to pass through two design points and the Nyquist curve as specified by separate gain margin (A/sub m/) and phase margin.<<ETX>>