Chang Chieh Hang

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.

A new Smith predictor for controlling a process with an integrator and long dead-time

Abstmct-A new Smith predictor for control of a process with an integrator and long dead-time is proposed in this note. The controller deeouples the setpoint response from the load response. This simplifies both design and tuning. Simulation results obtained by controlling a typical process show that the new controller has superior performance compared to previous algorithms.

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.

Adaptive neural network control of nonlinear systems by state and output feedback

This paper presents a novel control method for a general class of nonlinear systems using neural networks (NNs). Firstly, under the conditions of the system output and its time derivatives being available for feedback, an adaptive state feedback NN controller is developed. When only the output is measurable, by using a high-gain observer to estimate the derivatives of the system output, an adaptive output feedback NN controller is proposed. The closed-loop system is proven to be semi-globally uniformly ultimately bounded (SGUUB). In addition, if the approximation accuracy of the neural networks is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussions.

Towards Intelligent PID Control

Abstract Auto-tuners for PID controllers have now been commercially available for a few years. These controllers are automating the task normally performed by an instrument engineer. The auto-tuners include some technique for extracting process dynamics from experiments and some control design method. They may even be able to select to use PI or PID control. For 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 capability. This seems technically feasible with the increased computing power that is now available in single loop controllers. This paper describes a PID controller with such reasoning capabilities.

A Reflective Review of Disruptive Innovation Theory

Disruptive Innovation Theory has created a significant impact on management practices and aroused plenty of rich debate within academia. Copious as the studies are, the scattered and conflicting nature of the literature on disruptive innovation in the last decade may pose a state of ambiguity for future research, thus necessitating a comprehensive review at this juncture. This paper first clarifies the basic concept and potential misinterpretations of the theory. Believing in the predictive value of the theory on firm performance, the authors then summarize and critique the research on how to enable potential disruptive innovation from internal, external, marketing and technology perspectives. The different perspectives inspired the authors to identify a number of key research directions within the disruptive innovation research domain. Potential future research is also briefly discussed by integrating disruptive innovation with other research domains, such as open innovation. Finally, in addition to theoretical contributions, the authors make practical contributions by outlining a series of potential inhibitors and enablers of disruptive innovation as managerial ‘take-aways’.

Relay feedback auto-tuning of process controllers — a tutorial review

The PID relay auto-tuner of Astrom–Hagglund is one of the simplest and most robust auto-tuning techniques for process controllers and has been successfully applied to industry for more than 15 years. This tuner is based on an approximate estimation of the critical point on the process frequency response from relay oscillations. Many developments have recently been reported to extend its applications. It turns out that more and accurate information on process dynamics can be obtained from the same relay test with the help of new identification techniques, and used to tune PID controllers better. Extensions are also made to tune model-based advanced controllers and multivariable controllers. The present paper reviews these developments and shows the state-of art in relay auto-tuning of process controllers.

Brief Parallel structure and tuning of a fuzzy PID controller

In this paper, a parallel structure of fuzzy PID control systems is proposed. It is associated with a new tuning method which, based on gain margin and phase margin specifications, determines the parameters of the fuzzy PID controller. In comparison with conventional PID controllers, the proposed fuzzy PID controller shows higher control gains when system states are away from equilibrium and, at the same time, retains a lower profile of control signals. Consequently, better control performance is achieved. With the proposed formula, the weighting factors of a fuzzy logic controller can be systematically selected according to the plant under control. By virtue of using the simplest structure of fuzzy logic control, the stability of the nonlinear control system can be analyzed and a sufficient BIBO stability condition is given. The superior performance of the proposed controller is demonstrated through an experimental example.

Brief Paper: Design and performance analysis of a direct adaptive controller for nonlinear systems

In this paper, a direct adaptive controller is developed based on multilayer neural networks (MNNs) for a class of nonlinear systems. The proposed scheme avoids the possible singularity problem of the controller usually met in adaptive control design. The system tracking error is proven to converge to a small neighborhood of zero, while the stability of the closed-loop system is guaranteed. The transient performance of the resulting adaptive system is analytically quantified, and an example is given to show the effectiveness of the scheme.