Validation of a multivariable relay-based PID autotuner with specified robustness

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Universal direct tuner for loop control in industry

This paper introduces a direct universal (automatic) tuner for basic loop control in industrial applications. The direct feature refers to the fact that a first-hand model, such as a step response first-order plus dead time approximation, is not required. Instead, a point in the frequency domain and the corresponding slope of the loop frequency response is identified by single test suitable for industrial applications. The proposed method has been shown to overcome pitfalls found in other (automatic) tuning methods and has been validated in a wide range of common and exotic processes in simulation and experimental conditions. The method is very robust to noise, an important feature for real life industrial applications. Comparison is performed with other well-known methods, such as approximate M-constrained integral gain optimization (AMIGO) and Skogestad internal model controller (SIMC), which are indirect methods, i.e., they are based on a first-hand approximation of step response data. The results indicate great similarity between the results, whereas the direct method has the advantage of skipping this intermediate step of identification. The control structure is the most commonly used in industry, i.e., proportional-integral-derivative (PID) type. As the derivative action is often not used in industry due to its difficult choice, in the proposed method, we use a direct relation between the integral and derivative gains. This enables the user to have in the tuning structure the advantages of the derivative action, therefore much improving the potential of good performance in real life control applications

Automatic Tuning of PID Controllers Based on Asymmetric Relay Feedback

This thesis presents an improved version of the classic relay autotuner. The proposed autotuner uses an asymmetric relay function to better excite the process in the experiment phase. The improved excitation provides the possibility to obtain better models and hence better tuning, without making the autotuner more complicated or time consuming.Some processes demand more accurate modeling and tuning to obtain con-trollers of sufficient performance. The proposed autotuner can classify these processes from the experiment. In an advanced version of the autotuner an additional experiment could be dhttps://localhost/admin/login.phpesigned for these processes, in order to further increase the possibilities in modeling and tuning. The experiment design would then rely on information from the relay experiment. A simple version of the autotuner could instead make a somewhat better model estimation immediately, or suggest that some extra effort may be put in modeling if the control performance of the loop is crucial. The main focus in this thesis is on the simple version of the autotuner.The proposed autotuner uses the process classification for model and controller selection also in the simple version. The processes are classified according to their normalized time delays. In this thesis a simple method of finding the normalized time delay from the asymmetric relay experiment is presented and evaluated.Research presented on different versions of the relay autotuner is often based solely on simulations. In large simulation environments, the ability to automatically tune the large amount of PID controllers is practical and time-saving. However, the ability to use the autotuner in an industrial setting, requires considerations not always present in a simulation environment. This thesis investigates many of these issues, regarding parameter settings and possible error sources. The proposed autotuner is implemented, tested and evaluated both in a simulation environment and by industrial experiments. The simple version of the autotuner gives satisfactory results, both in simulations and on the industrial processes. Still, there is a possibility to further increase the performance by an advanced version of the autotuner

A survey of recent advances in fractional order control for time delay systems

Several papers reviewing fractional order calculus in control applications have been published recently. These papers focus on general tuning procedures, especially for the fractional order proportional integral derivative controller. However, not all these tuning procedures are applicable to all kinds of processes, such as the delicate time delay systems. This motivates the need for synthesizing fractional order control applications, problems, and advances completely dedicated to time delay processes. The purpose of this paper is to provide a state of the art that can be easily used as a basis to familiarize oneself with fractional order tuning strategies targeted for time delayed processes. Solely, the most recent advances, dating from the last decade, are included in this review

Robust controller design: Recent emerging concepts for control of mechatronic systems

The recent industrial revolution puts competitive requirements on most manufacturing and mechatronic processes. Some of these are economic driven, but most of them have an intrinsic projection on the loop performance achieved in most of closed loops across the various process layers. It turns out that successful operation in a globalization context can only be ensured by robust tuning of controller parameter as an effective way to deal with continuously changing end-user specs and raw product properties. Still, ease of communication in non-specialised process engineering vocabulary must be ensured at all times and ease of implementation on already existing platforms is preferred. Specifications as settling time, overshoot and robustness have a direct meaning in terms of process output and remain most popular amongst process engineers. An intuitive tuning procedure for robustness is based on linear system tools such as frequency response and bandlimited specifications thereof. Loop shaping remains a mature and easy to use methodology, although its tools such as Hinf remain in the shadow of classical PID control for industrial applications. Recently, next to these popular loop shaping methods, new tools have emerged, i.e. fractional order controller tuning rules. The key feature of the latter group is an intrinsic robustness to variations in the gain, time delay and time constant values, hence ideally suited for loop shaping purpose. In this paper, both methods are sketched and discussed in terms of their advantages and disadvantages. A real life control application used in mechatronic applications illustrates the proposed claims. The results support the claim that fractional order controllers outperform in terms of versatility the Hinf control, without losing the generality of conclusions. The paper pleads towards the use of the emerging tools as they are now ready for broader use, while providing the reader with a good perspective of their potential

Relay Feedback and Multivariable Control

This doctoral thesis treats three issues in control engineering related to relay feedback and multivariable control systems. Linear systems with relay feedback is the first topic. Such systems are shown to exhibit several interesting behaviors. It is proved that there exist multiple fast relay switches if and only if the sign of the first non-vanishing Markov parameter of the linear system is positive. It is also shown that these fast switches can appear as part of a stable limit cycle. A linear system with pole excess one or two is demonstrated to be particularly interesting. Stability conditions for these cases are derived. It is also discussed how fast relay switches can be approximated by sliding modes. Performance limitations in linear multivariable control systems is the second topic. It is proved that if the top left submatrices of a stable transfer matrix have no right half-plane zeros and a certain high-frequency condition holds, then there exists a diagonal stabilizing feedback that makes a weighted sensitivity function arbitrarily small. Implications on control structure design and sequential loop-closure are given. A novel multivariable laboratory process is also presented. Its linearized dynamics have a transmission zero that can be located anywhere on the real axis by simply adjusting two valves. This process is well suited to illustrate many issues in multivariable control, for example, control design limitations due to right half-plane zeros. The third topic is a combination of relay feedback and multivariable control. Tuning of individual loops in an existing multivariable control system is discussed. It is shown that a specific relay feedback experiment can be used to obtain process information suitable for performance improvement in a loop, without any prior knowledge of the system dynamics. The influence of the loop retuning on the overall closed-loop performance is derived and interpreted in several ways

Online adaptive and intelligent control strategies for multizone VAV systems

Nearly one half of the total energy used in buildings is consumed by HVAC systems. With escalating cost of energy, several energy efficiency strategies have been implemented in buildings. Among these, the use of VAV systems, and improved method of controlling such systems have received greater attention. This thesis is devoted to design and development of online adaptive control strategies which will be augmented with optimal and intelligent-control algorithms. The considered VAV system consists of zone air temperature control, discharge air temperature control, water temperature control and air pressure control loops. Online adaptive control strategies are developed for these control loops. In order to design reliable online controls a robust RLS identification algorithm for estimating the parameters of the modeled processes is developed. It is shown that this algorithm avoids wrong estimation and requires fewer variables compared with classical RLS techniques. Three different online control strategies were designed. These are: a robust optimal control algorithm (ROCA), a simplified optimal adaptive control (SOAC) for FOPDT systems, and a two-loop adaptive control strategy which improves both temperature and airflow regulations in VAV systems. ROCA is an on-line optimal proportional-integral plus feedforward controller tuning algorithm for SISO thermal processes in HVAC systems. It was optimized by combining the H {592} based PI tuning It is shown that the two-loop adaptive control strategy has both stronger robustness to time-varying thermal loads and lower sensitivity to airflow rate changes into other zones. The developed control strategies were tested by simulation and experiments in a VAV laboratory test facility which uses existing energy management control systems used in commercial buildings. Also, an adaptive neural network controller is developed. The proposed controller was constructed by augmenting the PID control structure with a neural network control algorithm and an adaptive balance parameter. Simulation results show that the proposed controller has stronger robustness, improved regulation and tracking functions for FOPDT type plants compared to classical PID controllers. Experiments were conducted to verify the characteristics of the developed controller on the DAS in a two-zone VAV test facility. Applications of the developed control strategies to different control loops in VAV system were demonstrated by conducting several experimental tests under realistic operating condition

The estimation and compensation of processes with time delays

The estimation and compensation of processes with time delays have been of interest to academics and practitioners for several decades. A full review of the literature for both model parameter and time delay estimation is presented. Gradient methods of parameter estimation, in open loop, in the time and frequency domains are subsequently considered in detail. Firstly, an algorithm is developed, using an appropriate gradient algorithm, for the estimation of all the parameters of an appropriate process model with time delay, in open loop, in the time domain. The convergence of the model parameters to the process parameters is considered analytically and in simulation. The estimation of the process parameters in the frequency domain is also addressed, with analytical procedures being defined to provide initial estimates of the model parameters, and a gradient algorithm being used to refine these estimates to attain the global minimum of the cost function that is optimised. The focus of the thesis is subsequently broadened with the consideration of compensation methods for processes with time delays. These methods are reviewed in a comprehensive manner, and the design of a modified Smith predictor, which facilitates a better regulator response than does the Smith predictor, is considered in detail. Gradient algorithms are subsequently developed for the estimation of process parameters (including time delay) in closed loop, in the Smith predictor and modified Smith predictor structures, in the time domain; the convergence of the model parameters to the process parameters is considered analytically and in simulation. The thesis concludes with an overview of the methods developed, and projections regarding future developments in the topics under consideration

Design and Certification of Industrial Predictive Controllers

Three decades have passed since milestone publications by several industrial and academic researchers spawned a flurry of research and commercial, industrial activities on model predictive control (MPC). The improvement in efficiency of the on-line optimization part of MPC led to its adoption in mechanical and mechatronic systems from process control and petrochemical applications. However, the massive strides made by the academic community in guaranteeing stability through state-space MPC have not always been directly applicable in an industrial setting. This thesis is concerned with design and a posteriori certification of feasibility/stability of input-output MPC controllers for industrial applications without terminal conditions (i.e. terminal penalty, terminal constraint, terminal control). MPC controllers which differ in their modelling and prediction method are categorized into three major groups, and a general equivalence between these forms is established. Then an overview on robust set invariance is given as it plays a fundamental role in our analysis of the constrained control systems. These tools are used to give new tuning guidelines as well as a posteriori tests for guaranteeing feasibility of the suboptimal or optimal predictive control law without terminal conditions, which is fundamental towards stability of the closed loop. Next, penalty adaptation is used as a systematic procedure to derive asymptotic stability without any terminal conditions and without using set invariance or Lyapunov arguments. This analysis however is restricted to repetitive systems with input constraints. Then, predictive control without terminal conditions is considered for nonlinear and distributed systems. The invariance tools are extended to switching nonlinear systems, a proof of convergence is given for the iterative nonlinear MPC (NMPC), and a guarantee on overall cost decrease is developed for distributed NMPC, all without terminal conditions. Reference generation and parameter adaptation are shown to be effective mechanisms for NMPC and distributed NMPC (DNMPC) under changing environmental conditions. This is demonstrated on two benchmark test-cases i.e. the wet-clutch and hydrostatic drivetrain, respectively. Terminal conditions in essence are difficult to compute, may compromise performance and are not used in the industry. The main contribution of the thesis is a systematic development and analysis of MPC without terminal conditions for linear, nonlinear and distributed systems.This work was supported within the framework of the LeCoPro project (grant nr. 80032) of the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen)