SISO Control Research Articles

Controller switching with the anti-bump adapter

Switching on a new or retuned controller while keeping the control loop engaged tends to generate transient “bumps” in the commands and plant outputs. For a linear time-invariant (LTI) controller in state–space form, these bumps can be mitigated or even suppressed by resetting the controller state to an appropriate non-zero value adapted to the pre-switching trajectories of the feedback loop signals. This paper proposes a simple way to compute this adapted controller state by minimizing the difference between the commands actually applied immediately before switching and the virtual command trajectory which the new controller would have generated if it had been activated in parallel. This adapted state can be recursively computed as the output of an LTI system in standard state–space form, the anti-bump adapter. Computing the anti-bump adapter involves only standard matrix algebra and control concepts (e.g., observability and controllability matrices/Gramians). Calculations are very simple and can be translated into compact computer code. This bump suppression procedure is applicable to any discrete-time or continuous-time LTI SISO or MIMO controller, without any assumption on or knowledge of either the previously active controller or the plant. Illustrative applications to continuous-time and discrete-time switching problems and a Matlab® code for computing the anti-bump adapter are presented.

Research on Energy-Saving Control Strategies for Single-Effect Absorption Refrigeration Systems

The automatic control device is a critical component of absorption refrigeration systems. Its functional enhancement can reduce operating costs, improve energy efficiency, and ensure long-term stable unit operation. Given that absorption refrigeration systems operate under various dynamic conditions, the rational design of control strategies is particularly important. This study analyzes the influence of changes in the cooling water and heat source water flow rates on the outlet temperature of chilled water in the unit based on the open-loop response characteristics of absorption refrigeration systems. It proposes a dual-loop energy-saving control strategy for single-effect hot water lithium bromide absorption refrigeration systems based on the setpoint comprehensive optimization algorithm. Considering the multiple variables, strong coupling, large inertia, long time delay, and nonlinear characteristics of absorption refrigeration systems, as well as the difficulties in modeling these systems, this study applies a model-free adaptive control algorithm to the system’s control. It derives both SISO and MIMO model-free control algorithms with time-delay components. Through simulations comparing MFAC, improved MFAC, and traditional PID control, the dual-loop energy-saving control strategy is demonstrated to effectively reduce system heat consumption by approximately 20%, decrease power consumption by about 10%, and enhance the system’s SCOP by approximately 19.3%.

Automatic Re-tuning of Poor-Performing PI-based Control Systems

The goal of the work is to create a new method for automatic re-tuning of PI controllers. It is achieved by solving the following problems. The first problem is to develop a method to identify a FOPDT estimation model by analyzing the dynamics of a control loop with a PI controller. The second problem is to demonstrate that the use of the estimated model allows to obtain better processes in control systems with PI controllers by comparing the resulting FOPDT model with a number of reduced models. The third problem is to develop a five-stage algorithm for automatic re-tuning of PI controllers. The fourth problem is to verify the software implementation of the developed algorithm. The most significant result was that the basis for estimating the FOPDT model in a loop with a Ziegler-Nichols tuned PI controller was the estimation the ratio of the delay to the time constant of the FOPDT model based on an assessment of the process overshoot. When the real control plant dynamics did not match with the dynamics of the FOPDT model this way was found effective for finding the optimal tuning of the PI controller. The significance of the results obtained was a structural robustness in case of estimated FOPDT model usage. The effectiveness of the procedure has been demonstrated on both linear and nonlinear models. The developed procedure is proposed to be used to automate the procedure of re-tuning SISO control systems when the control loop performance degradation has been detected.

Decentralized control using selectors for optimal steady-state operation with changing active constraints

We study the optimal steady-state operation of processes where the active constraints change. The aim of this work is to eliminate or reduce the need for a real-time optimization layer, moving the optimization into the control layer by switching between appropriately selected controlled variables (CVs) in a simple way. The challenge is that the best CVs, or more precisely the reduced cost gradients associated with the unconstrained degrees of freedom, change with the active constraints. This work proposes a framework based on decentralized control that operates optimally in all active constraint regions, with region switching mediated by selectors. A key point is that the nullspace associated with the unconstrained cost gradient needs to be selected in accordance with the constraint directions so that selectors can be used. A main benefit is that the number of SISO controllers that need to be designed is only equal to the number of process inputs plus constraints. The main assumptions are that the unconstrained cost gradient is available online and that the number of constraints does not exceed the number of process inputs. The optimality and ease of implementation are illustrated in a simulated toy example with linear constraints and a quadratic cost function. In addition, the proposed framework is successfully applied to the nonlinear Williams–Otto reactor case study.

A PID Control Architecture Based on IEC 61499

This work presents an approach for PID control and optimization in a distributed system, using the IEC 61499 control standard. This standard enables communication among different PLCs, which are used to develop a three-layered event-driven control of a SISO loop. The lowest layer is in charge of cyclical data acquisition. The second layer carries out an event-based PID control. The highest layer runs a control optimization algorithm, specifically a simple tuning approach based on Ziegler-Nichols that is used to determine the PID parameters for different operating points. The proposed approach is assessed in a tank level SISO control problem, whose behavior can be modeled as a first-order plus dead time system in each operating point. For that purpose, it has been implemented using two PLCs and a software PLC running on an industrial computer. The experimental results on the SISO level control loop show the feasibility of the proposed approach for event-driven control in a distributed system and open interesting research questions in the intersection of controller design and distributed automation.

A testbed for studying the interactions between human operators and advanced control systems

Industrial chemical processes are operated under closed-loop control while being supervised by human operators. The low-level regulatory controllers are often supplemented by advanced multivariate control such as Model Predictive Control (MPC). Since MPC is complex, its control actions can be non-intuitive to the operator. The operator may turn off any controller if they suspect the control actions triggered by it. Hence, it is imperative to understand the operator's interaction with automation. In this work, we develop a testbed with the potential to understand the operator's confidence in MPC through a human factors approach. The testbed consists of a multi-unit chemical process instrumented with various sensors, multiple low-level SISO control loops, and a high-level MPC. The testbed is instrumented with a mechanism to record keystrokes, mouse movements, and mouse clicks to observe the operators’ interactions with the process (during various fault scenarios) through the provided Human Machine Interface.

New Insights on Robust Control of Tilting Trains with Combined Uncertainty and Performance Constraints

A rigorous study on optimized robust control is presented for non-preview (nulling-type) high-speed tilting rail vehicles. The scheme utilizes sensors on the vehicle’s body, contrary to that of preview tilt (which uses prior rail track information). Tilt with preview is the industrial norm nowadays but is a complex scheme (both in terms of inter-vehicle signal connections and when it comes to straightforward fault detection). Non-preview tilt is simple (as it essentially involves an SISO control structure) and more effective in terms of (the localization of) failure detection. However, the non-preview tilt scheme suffers from performance limitations due to non-minimum-phase zeros in the design model (due to the compound effect of the suspension dynamic interaction and sensor combination used for feedback control) and presents a challenging control design problem. We proposed an optimized robust control design offering a highly improved non-preview tilt performance via a twofold model representation, i.e., (i) using the non-minimum phase design model and (ii) proposing a factorized design model version with the non-minimum phase characteristics treated as uncertainty. The impact of the designed controllers on tilt performance deterministic (curving acceleration response) and stochastic (ride quality) trade-off was methodically investigated. Nonlinear optimization was employed to facilitate fine weight selection given the importance of the ride quality as a bounded constraint in the design process.

Robust Adaptive Tracking Control of a 3D Vertical Motion System for Nanometer Precision Applications

In this paper we address the modeling and tracking control problem of an overactuated lift and tilt vertical nanopositioning system. We derive a model based on the rigid body dynamics which adequately describes the first resonance mode of each motion axis. This model is validated with measured data in the frequency domain to illustrate that it adequately reflects the real behavior. We further device an abstract model for the derivation of advanced control strategies. By virtue of the single axis model, three SISO controllers are implemented. The control strategy is accomplished comprising a nominal feedforward and LQG-type controller plus an L1 adaptive augmentation with output feedback. The baseline (or nominal) controller features sufficiently high bandwidth for the mere stabilization, decoupling, and disturbance rejection, while the L1 adaptive component plays a central role for recovering the nominal closed-loop dynamics in the presence of parametric uncertainties w.r.t. the input gain which are quite difficult to handle in the nominal design. The effectiveness and robustness of the proposed control strategy is verified via real-time experiments featuring subnanometer and nanoradian tracking errors which seem to be fully-dominated by the measurement noise.

Design of siso control systems accounting measurement noises

Design of siso control systems accounting measurement noises

Design of fractional order PID controller based on minimum variance control and application of dynamic data reconciliation for improving control performance

Fractional order PID (FOPID) has received much attention in recent years and has been applied in different fields. However, the parameter tuning of FOPID is a tough problem. In order to design an optimal FOPID controller, a parameter tuning method based on minimum variance control (MVC) rule is proposed in both SISO and MIMO control systems Considering the influence of measurement noise with Gaussian and non-Gaussian distribution, which is generally ignored in the controller design based on MVC rule, this paper applies dynamic data reconciliation (DDR) technology to suppress its influence and improve the control performance of the designed FOPID. In the case of considering Gaussian and non-Gaussian distributed measurement noise, SISO and MIMO control systems are employed to verify the effectiveness of the proposed FOPID parameter tuning and DDR method. The results show that the designed FOPID improves the performance of the control system, and the DDR technology suppresses the negative effect of measurement noise and improves the control performance of the designed FOPID.

Control Structure Design Using Global Sensitivity Analysis for Mineral Processes under Uncertainties

Multiple-input and multiple-output (MIMO) systems can be found in many industrial processes, including mining processes. In practice, these systems are difficult to control due to the interactions of their input variables and the inherent uncertainty of industrial processes. Depending on the interactions in the MIMO process, different control strategies can be implemented to achieve the desired performance. Among these strategies is the use of a decentralized structure that considers several subsystems and for which a SISO controller can be designed. In this study, a methodology based on global sensitivity analysis (GSA) to design decentralized control structures for industrial processes under uncertainty is presented. GSA has not yet been applied for this purpose in process control; it allows us to understand the dynamic behavior of systems under uncertainty in a broad value range, unlike approaches proposed in the literature. The proposed GSA is based on the Sobol method, which provides sensitivity indices used as interaction measures to establish the input–output pairing for MIMO systems. Two case studies based on a semi-autogenous grinding (SAG) mill and a solvent extraction (SX) plant are presented to demonstrate the applicability of the proposed methodology. The results indicate that the methodology allows the design of 2 × 2 and 3 × 3 decentralized control structures for the SAG mill and SX plant, respectively, which exhibit good performance compared to MPC. For example, for the SAG mill, the determined pairings were fresh ore flux/fraction of mill filling and power consumption/percentage of critical speed.

Chaotic dynamics induced by anti-slug control in offshore oil production plants

The dynamic behavior of an offshore oil production plant obtained through an anti-slug scheme based on a feedback PI control was studied. Three different SISO control scenarios were evaluated considering different controlled variables and the effect of the PI control constants tuning on the suppression of oscillatory behavior related to the slugging flow phenomenon. It was shown that the PI control, when the pressure at the top of the riser was the controlled variable, was able to induce chaotic oscillations. Additionally, the proper characterization of the chaotic behavior was performed allowing to determine the PI control tuning conditions that favor the appearance of this complex behavior.

Robust Dynamic CPU Resource Provisioning in Virtualized Servers

We present robust dynamic resource allocation mechanisms to allocate application resources meeting Service Level Objectives (SLOs) agreed between cloud providers and customers. In fact, two filter-based robust controllers, i.e., <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_{\infty }$</tex-math></inline-formula> filter and Maximum Correntropy Criterion Kalman filter (MCC-KF), are proposed. The controllers are self-adaptive, with process noise variances and covariances calculated using previous measurements within a time window. In the allocation process, a bounded client mean response time ( <inline-formula><tex-math notation="LaTeX">$\mathop {\mathrm{mRT}}$</tex-math></inline-formula> ) is maintained. Both controllers are deployed and evaluated on an experimental testbed hosting the RUBiS (Rice University Bidding System) auction benchmark web site. The proposed controllers offer improved performance under abrupt workload changes, shown via rigorous comparison with current state-of-the-art. On our experimental setup, the Single-Input-Single-Output (SISO) controllers can operate on the same server where the resource allocation is performed; while Multi-Input-Multi-Output (MIMO) controllers are on a separate server where all the data are collected for decision making. SISO controllers take decisions not dependent to other system states (servers), albeit MIMO controllers are characterized by increased communication overhead and potential delays. While SISO controllers offer improved performance over MIMO ones, the latter enable a more informed decision making framework for resource allocation problem of multi-tier applications.

Generalized discrete decoupling and control of MIMO systems

AbstractThis paper proposes an efficient discrete‐time decoupling algorithm for multiple input multiple output (MIMO) systems having strong coupling between inputs and outputs. A design method for discrete decouplers is proposed to eliminate the cross‐coupling effects present in MIMO systems. The proposed decoupling technique is based on relative gain array (RGA) approach of MIMO system. In order to perform closed‐loop control, individual discrete‐time PID controllers are designed based on Kharitonov theorem for each of the SISO control loops of the resulting decoupled MIMO system. The closed‐loop performance of the MIMO system under consideration is investigated in simulation and in real time which illustrate that the proposed decoupling algorithm satisfactorily nullifies the interaction between the inputs and outputs. The control scheme exhibits perfect tracking of the reference commands even in presence of disturbances. Twin rotor MIMO system (TRMS) is considered as the real‐time example to validate the proposed method. Further, the performance of the compensated TRMS system is analyzed in frequency domain in presence of common actuator nonlinearities dead zone and saturation together. The performances of the controllers are found to be efficient even in presence of actuator nonlinearities.

Sliding Mode Control to Track Trajectories for Two-Linked Robot Arm

Two-linked robot arm is a popular model in both laboratory and actual industry. This is a MIMO system which has the same number of inputs and outputs. Because of the interactions between variables, normal SISO control algorithms, such as PID algorithm, do not prove their effectiveness in process of operation. In this paper, we propose using a method of sliding algorithm to control two-linked robot tracking expected trajectories. Results of controlling are proved to be successful through Matlab/Simulink.

Reference Tracking Control for Maneuvering Vessels considering Input Delay

Due to increasing vessel sizes and traffic volumes, maneuvering is becoming more and more challenging. Therefore, bridge personnel should be assisted by providing control systems for maneuvering. In addition to an expected improvement in safety and efficiency, automatic maneuvering is also relevant with regard to future autonomous shipping. This paper contributes to position control and heading control, which form the basis for higher-level guidance systems. An extension of the widely used dynamic positioning approach is presented to realize integral reference tracking. This provides the capability to follow a predefined trajectory.The coupled acceleration behavior of the vessel in terms of a full mass matrix is taken into account by a compensation approach, so that a SISO controller design becomes applicable.In the case of the investigated application, there was a significant input delay, which led to greatly reduced control performance and oscillation around the reference value. These problems were solved by applying the so-called reduction transformation approach to the use case of a maneuvering vessel. The time constant of the closed loop system is chosen as the design parameter of the controller design. It represents the choice between performance and economy, which is made by the operator. The realization of the demanded time constant is implemented by a simple optimization loop that yields the actual feedback gain for linear quadratic optimal control.Real-world tests of the presented system were carried out in a model basin with a scale model of an offshore supply vessel to validate the functionality of the entire control system.

Study on outlier robustness of minimum variance control performance assessment

SummaryMinimum variance (MinVar) method for control performance assessment constitutes one of the most common approaches to the control quality estimation. There are dozens of versions, enriched with numerous reported industrial implementations. MinVar methodology uses the idea of minimum variance, which has been introduced by Kalman. Therefore, it should be remembered that MinVar concept relies on the same assumptions as an idea of the minimum variance control. Among other assumptions, it is essential that the modeled disturbance is an independent random sequence. This article addresses scenarios, when loop noise exhibits non‐Gaussian properties and is characterized by outliers having fat‐tailed distribution. Sensitivity analysis of minimum variance method against such disturbances is evaluated using commonly used PID SISO control benchmarks. It is shown that MinVar method may be significantly biased in such non‐Gaussian situations, which are very frequent in the industrial reality. Reasons of the biased performance are traced and respective solutions are proposed.

Industrial datasets and a tool for SISO control loops data visualization and analysis

The demand for high performance in industries increases as competitive pressure grows. This opens opportunities for control loop performance monitoring (CPM) techniques, which have been widely proposed over the last three decades. The large number of techniques is valuable, but it brings problems in selecting the right technique for a given application. Industrial data are not easily available due to confidential reasons. Thus, new techniques are commonly tested in a few examples that cover a limited number of scenarios. Also, the tests are not standardized and are not performed using the same dataset. This complicates the comparison of the techniques. This work shares three datasets with different features found on industries, which go from long-range raw data to selected fragments with adequate sampling time. Also, an open-source tool for SISO data visualization and analysis is provided. This tool allows for easy visualization and testing of new techniques.

Loop shaping based robust control for floating offshore wind turbines

In this work, a thorough and complete methodology for the widely used SISO controller is described for floating offshore wind turbines (FOWTs). The motivation is to develop clear, easy implementable and automated design criteria of blade pitch control design, which takes both stability and performance into account for FOWTs without adding new sensors. The primary design criteria is to achieve a similar dynamic step response behaviour, i.e. overshooting, rise time and settling time across the operating points above rated wind speeds. The proposed design procedure can be performed by lower order numerical models with only two degrees of freedom, which can be derived analytically. The minimal required system information eases an early stage controller design, as well as the system engineering and integrated substructure design. The proposed design procedure is evaluated on three state of the art floating wind turbines. The resulting gain scheduling is quite different from the one for onshore turbines. The overall response is satisfying and comparable with an existing stability-oriented robust SISO controller at operation points where stability is critical. An improved performance is found for higher wind speeds.

Synthesis of Discrete Modal SISO Controllers by Engineering Performance Indices

The linear discrete minimum-phase plant with one control input, one measured output and with an unmeasured external disturbance is considered. The problem is stated of the design of the discrete output controller that provides the preset engineering performance indices: control error, settling time, stability margins radius. Analytical formulas are obtained that allow to relate the engineering performance indices with the desired closed system characteristic polynomial roots in the modal control problem when choosing real non-negative roots. At the same time, the specified control error and the settling time lead to the constraints on the maximum absolute value of the desired roots, while the values of the desired roots, providing the given stability margins radius, may not satisfy these constraints, so the specified values of the performance indices should be revised. Examples are given showing the effectiveness of the approach proposed.