Control Design Framework Research Articles

A Novel Sliding Mode Control Framework for Electrohydrostatic Position Actuation System

A novel sliding mode control (SMC) design framework is devoted to providing a favorable SMC design solution for the position tracking control of electrohydrostatic actuation system (EHSAS). This framework is composed of three submodules as follows: a reduced-order model of EHSAS, a disturbance sliding mode observer (DSMO), and a new adaptive reaching law (NARL). First, a reduced-order model is obtained by analyzing the flow rate continuation equation of EHSAS to avoid the use of a state observer. Second, DSMO is proposed to estimate and compensate mismatched disturbances existing in the reduced-order model. In addition, a NARL is developed to tackle the inherent chattering problem of SMC. Extensive simulations are conducted compared with the wide adoption of three-loop PID method on the cosimulation platform of EHSAS, which is built by combining AMESim with MATLAB/Simulink, to verify the feasibility and superiority of the proposed scheme. Results demonstrate that the chattering can be effectively attenuated, and the mismatched disturbance can be satisfyingly compensated. Moreover, the transient performance, steady-state accuracy, and robustness of position control are all improved.

Optimization and control of offshore wind farms with energy storage systems

This paper studies the optimal control strategies of hybrid renewable energy systems, focusing on offshore wind farms with energy storage systems (ESS), considering challenges of economic costs, operational reliability, and environmental impacts. Wind energy is widely exploited as a promising renewable energy source worldwide. The development of offshore wind farms (OWF) is emerging to utilize wind energy on a large scale, but face more complicated operational conditions and higher costs. A systematic methodology is proposed to optimize the costs of an OWF with ESS based on a framework that extends from the supervisory level dispatch strategies to individual pitch control for load reduction and fatigue mitigation. This holistic approach is able to improve the efficiency and economic performance of a wind farm through overall system optimization, while explicitly operating each wind turbine using a formally designed control framework leading to an extension of their service lifespan. This work provides novel solutions of wind energy and storage components deployment and has strong application potential.

An Enhanced Robust Control Algorithm Based on CNF and ISM for the MEMS Micromirror against Input Saturation and Disturbance.

Input saturation is a widespread phenomenon in the field of instrumentation, and is harmful to performance and robustness. In this paper, a control design framework based on composite nonlinear feedback (CNF) and integral sliding mode (ISM) technique is proposed for a MEMS micromirror to improve its performance under input saturation. To make the framework more effective, some essential improvements are supplied. With the application of the proposed design framework, the micromirror under input saturation and time-varying disturbances can achieve precise positioning with satisfactory transient performance compared with the open-loop performance.

Stability Analysis of a Set of Uncertain Large-Scale Dynamical Models with Saturations

From a sparse set of large-scale Linear Time Invariant (LTI) dynamical models, a methodology to generate a low-order parameter-dependent and uncertain model, with guaranteed bounds on the approximation error is firstly obtained using advanced approximation and interpolation techniques. Secondly, the stability of the aforementioned model, represented as a Linear Fractional Representation (LFR) and subject to actuator saturation and dynamical uncertainties, is addressed through the use of an irrational multiplier-based Integral Quadratic Constraint (IQC) approach. The effectiveness of the approach is assessed on a complex set of aeroservoelastic aircraft models used in an industrial framework for control design and validation purposes.

Reduced modelling and fixed‐order control of delay systems applied to a heat exchanger

The authors present an integrated approach for designing low-order multi-objective controllers for linear time-delay systems (TDSs), combining recently developed methods for reduction of delay systems and fixed-order control design, respectively. As a benchmark problem for process control applications, a model of an experimental heat transfer setup is used, which serves to motivate the adopted combination of model reduction and control technique. The former corresponds to a Krylov based reduction procedure, which is generalised to multiple-input-multiple-output systems with state, input and output delays, and allows the adaptive construction of an accurate low-order linear time-invariant approximation of the original linear TDS. Concerning the latter, a fixed-order controller is synthesised for the delay-free approximation, exploiting a recently proposed linear matrix inequality based framework for fixed-order controller design, and validated on the original model. In this way, the systematic overall design procedure, which is grounded in convex optimisation, complements approaches based on directly optimising stability and performance measures as a function of the controller parameters, which may lead to highly nonconvex, even non-smooth optimisation problems. The successful design of a fixed-order multi- H 2 controller is validated on the benchmark problem, confirming the potential of the adopted approach for realistic industrial applications.

A Systematic Framework for Process Control Design and Risk Analysis in Continuous Pharmaceutical Solid-Dosage Manufacturing

The paradigm shift in the pharmaceutical industry to continuous manufacturing, which has recently progressed from conceptual demonstration to pilot production, has stimulated the development and application of process systems engineering (PSE) tools for implementing efficient and robust control strategies. In this study, a systematic framework for process control design and risk analysis for continuous pharmaceutical solid-dosage manufacturing is proposed, consisting of system identification with state-space models; control design and analysis metrics; hierarchical three-layer control structures; risk mapping, assessment and planning (Risk MAP) strategies; and control performance indicators. The framework is applied to a feeding-blending system, wherein the major source of variance in the product quality arises. It can be demonstrated that the variance in the feeding-blending system can be mitigated and managed through the proposed systematic framework for control design and risk analysis. The process analytical technology (PAT) tool for mass fraction measurement of active pharmaceutical ingredient (API) and its relative standard deviation (RSD) were indispensable to achieve an efficient control design at the advanced layers. Specifically, the improvements in control performance by implementing advanced model-based control strategy are found to be limited by model-plant mismatch and the sampling time of the PAT tools.

Investigating the simultaneous process design and control of a membrane reactor for hydrogen production via methane steam reforming

In the present work, the simultaneous process design and control of a membrane reactor for H2 production via methane steam reforming (MSR) is performed. The problem is stated as a non-linear optimization problem with non-linear constraints, which includes economic and controllability criteria in the objective function. A linear model predictive controller (MPC) is implemented to enforce the desired dynamic performance. Utilizing this methodology two pre-defined process flowsheets for H2 production through the low temperature MSR, utilizing palladium-based membranes, are optimally designed based on economic criteria in the form of annualized capital and operating cost, and controllability criteria, in the form of the sum of squared errors during dynamic transitions. The first flowsheet is consisted of an integrated membrane reactor (IMR), whereas the second flowsheet under consideration is consisted of a cascaded arrangement between a reactor and a membrane module in series (CRM). Several other auxiliary processes such as heat exchangers, splitters, and mixers are employed. Rigorous nonlinear dynamic models have been developed assuming one dimensional transport and pseudo-homogenous conditions in the reaction zone in order to emulate the plant dynamics, whereas a linearized version of it is used by the MPC algorithm. Optimization results demonstrate the ability of the integrated process and control design framework to achieve a superior operating performance for a range of several factors affecting the operating conditions of the reactor.

Stabilizing plug-and-play regulators and secondary coordinated control for AC islanded microgrids with bus-connected topology

This paper presents a distributed hierarchical control architecture for voltage and frequency stabilization and reactive power sharing in AC islanded microgrids. In the primary control layer, each generation unit is equipped with a local regulator for voltage and frequency stability acting on the corresponding voltage-source converter. Following the plug-and-play design approach previously proposed by some of the authors, whenever the addition/removal of a distributed generation unit is required, feasibility of the operation is automatically checked by designing local controllers through convex optimization. The update of the voltage-control layer, when units plug-in/-out, is therefore automatized and stability of the microgrid is always preserved. Moreover, local control design is based only on the knowledge of parameters of power lines and it does not require to store a global microgrid model. In this work, we focus on islanded microgrids with bus-connected topology and enhance the primary plug-and-play layer with local virtual impedance loops and secondary coordinated controllers ensuring bus voltage tracking and reactive power sharing. In particular, the secondary control architecture is distributed, hence mirroring the modularity of the primary control layer. We validate primary and secondary controllers by performing experiments with both linear and nonlinear loads, on a setup composed of three bus-connected distributed generation units. Most importantly, the stability of the microgrid after the addition/removal of distributed generation units is assessed. Overall, the experimental results show the feasibility of the proposed modular control design framework, where generation units can be added/removed on the fly, thus enabling the deployment of virtual power plants that can be resized over time.

A Model-Based Control Design Approach for Linear Free-Piston Engines

A general design approach is presented for model-based control of piston position in a free-piston engine (FPE). The proposed approach controls either “bottom-dead-center” (BDC) or “top-dead-center” (TDC) position. The key advantage of the approach is that it facilitates controller parameter selection, by the way of deriving parameter combinations that yield both stable BDC and stable TDC. Driving the piston motion toward a target compression ratio is, therefore, achieved with sound engineering insight, consequently allowing repeatable engine cycles for steady power output. The adopted control design approach is based on linear control-oriented models derived from exploitation of energy conservation principles in a two-stroke engine cycle. Two controllers are developed: A proportional integral (PI) controller with an associated stability condition expressed in terms of controller parameters, and a linear quadratic regulator (LQR) to demonstrate a framework for advanced control design where needed. A detailed analysis is undertaken on two FPE case studies differing only by rebound device type, reporting simulation results for both PI and LQR control. The applicability of the proposed methodology to other common FPE configurations is examined to demonstrate its generality.

A Unified Framework for Asynchronous Control of Positive Switched Systems

This paper addresses the asynchronous control of positive switched systems. First, a unified controller design framework for the asynchronous control of switched positive systems is presented using linear programming and matrix transformation, where the “unified” property means that most of the asynchronous control problems of positive switched systems can be solved by employing the presented controller framework. Then, the unified controller framework is extended to the asynchronous L1 controller design of switched positive systems. Comparisons show that the unified controller design removes all restrictions in existing literature. Finally, a comparison example is given to illustrate the validity of the presented approach.

Intelligent Critic Control With Disturbance Attenuation for Affine Dynamics Including an Application to a Microgrid System

In this paper, a computationally efficient framework for intelligent critic control design and application of continuous-time input-affine systems is established with the purpose of disturbance attenuation. The described problem is formulated as a two-player zero-sum differential game and the adaptive critic mechanism with intelligent component is employed to solve the minimax optimization problem. First, a neural identifier is developed to reconstruct the unknown dynamical information incorporating stability analysis. Next, the optimal control law and the worst-case disturbance law are designed by introducing and tuning a critic neural network. Moreover, the closed-loop system is proved to possess the uniform ultimate boundedness. At last, the present method is applied to a smart microgrid and then is further adopted to control a general nonlinear system via simulation, thereby substantiating the performance of disturbance attenuation.

Switching predictive control for continuous-time Markovian jump delay systems

This paper is concerned with switching model predictive control (SMPC) for continuous-time Markovian jump delay systems (MJDSs). First, a piecewise constant switching predictive controller, which only depends on the average dwell time (ADT) switching laws rather than the jumping modes, is obtained by employing the ADT approach under the infinite-time predictive control design framework. Such a control strategy is proposed to make a trade-off between robustness and adaptivity when the design complexity of mode-independent and mode-dependent MPC is considered. It is revealed that the SMPC can deal with MJDSs with both time varying and time invariant jump rates and cover the mode-independent MPC as a special cease. Second, the feasibility of the SMPC scheme and the mean square stability of the closed-loop MJDS are discussed by using the stochastic invariance of the ellipsoid set over each sampling period. A numerical example is given to illustrate the main results.

Robust ILC design with application to stroke rehabilitation

Iterative learning control (ILC) is a design technique which can achieve accurate tracking by learning over repeated task attempts. However, long-term stability remains a critical limitation to widespread application, and to-date robustness analysis has overwhelmingly considered structured uncertainties. This paper substantially expands the scope of existing ILC robustness analysis by addressing unstructured uncertainties, a widely used ILC update class, the presence of a feedback controller, and a general task description that incorporates the most recent expansions in the ILC tracking objective. Gap metric based analysis is applied to ILC by reformulating the finite horizon trial-to-trial feedforward dynamics into an equivalent along-the-trial feedback system, as well as deriving relationships to link their respective gap metric values. The results are used to generate a comprehensive design framework for robust control design of the interacting feedback and ILC loops. This is illustrated via application to rehabilitation engineering, an area where they meet an urgent need for high performance in the presence of significant modeling uncertainty.

Decentralized minimal‐time planar formation control of multi‐agent system

SummaryIn this paper, the problems of decentralized minimal‐time planar formation control are investigated for both static and dynamic cases. For the static one, the discrete‐time dynamics of multi‐agent system in which each agent exchanges information according to a complex weighted network is studied. On the basis of a minimal polynomial, a decentralized minimal‐time static formation method is proposed to compute the final formation positions of the agents in the minimal number of steps without global coordinates. The proposed method allows an arbitrarily chosen agent in the network to compute its final formation position. For the dynamic one in a leader–follower framework, the path information of the agents satisfies linear regression equations that are determined by interaction topology and input signals. In order to obtain the coefficients of such linear regression equations, a Kronecker‐theorem‐based algorithm is presented. Similar to the results for the static case, any agent is allowed to use the minimum number of successive history state values to compute the future dynamic formation track. The minimal number of steps can be computed by checking the rank condition of the Hankel matrix constructed in terms of the path information. Meanwhile, the simulation examples are given to demonstrate the validity of the proposed minimal‐time planar formation control methods. The results in the paper combine the matrix polynomial analysis into the framework of formation control design and show how to predict the motion of the agents in a decentralized manner. Copyright © 2017 John Wiley & Sons, Ltd.

Robust Control Strategy for a Conduction–Convection System Based on the Scenario Optimization

This paper deals with the robust control of an uncertain conduction–convection system in the framework of probabilistic control design based on both the geometric control and the scenario optimization approach. Thus, a robust control strategy that copes with parameter uncertainties is proposed for a heated rod taken as an application example of a conduction–convection system. The design approach consists in two steps. In the first step, assuming a nominal model, a state feedback that yields a stable linear lumped parameter system, of first order, in closed loop is designed by means of geometric control theory. The stability of the resulting closed-loop system is demonstrated based on the perturbation theorem from semigroup theory. The second step consists in defining the input reference of the designed state feedback by a structured robust controller. The parameter tuning of the structured controller is formulated as a semi-infinite (or robust) optimization problem which is, then, relaxed using the scenario approach leading to a standard finite optimization problem. The solution of this scenario optimization problem is achieved using a genetic algorithm. The proposed control strategy is adopted to cope with parameter uncertainties in the problem of heating a steel rod. The effectiveness of the proposed robust control strategy is demonstrated by simulation.

Stability Analysis of a Set of Uncertain Large-Scale Dynamical Models With Saturations: Application to an Aircraft System

From a sparse set of large-scale linear time-invariant dynamical models, a methodology to generate a low-order parameter-dependent and uncertain model, with guaranteed bounds on the approximation error, is first obtained using advanced approximation and interpolation techniques. Second, the stability of the aforementioned model, represented as a linear fractional representation and subject to actuator saturation and dynamical uncertainties, is addressed through the use of an irrational multiplier-based integral quadratic constraint approach. The effectiveness of the approach is assessed on a complex set of aeroservoelastic aircraft models used in an industrial framework for control design and validation purposes.

A modal H∞-norm-based performance requirement for damage-tolerant active controller design

Damage-tolerant active control (DTAC) is a recent research area that encompasses control design methodologies resulting from the application of fault-tolerant control methods to vibration control of structures subject to damage. The possibility of damage occurrence is not usually considered in the active vibration control design requirements. Damage changes the structure dynamics, which may produce unexpected modal behavior of the closed-loop system, usually not anticipated by the controller design approaches. A modal H∞ norm and a respective robust controller design framework were recently introduced, and this method is here extended to face a new DTAC strategy implementation. Considering that damage affects each vibration mode differently, this paper adopts the modal H∞ norm to include damage as a design requirement. The basic idea is to create an appropriate energy distribution over the frequency range of interest and respective vibration modes, guaranteeing robustness, damage tolerance, and adequate overall performance, taking into account that it is common to have previous knowledge of the structure regions where damage may occur during its operational life. For this purpose, a structural health monitoring technique is applied to evaluate modal modifications caused by damage. This information is used to create modal weighing matrices, conducting to the modal H∞ controller design. Finite element models are adopted for a case study structure, including different damage severities, in order to validate the proposed control strategy. Results show the effectiveness of the proposed methodology with respect to damage tolerance.

H2−H∞ control of continuous-time nonlinear systems using the state-dependent Riccati equation approach

ABSTRACTThis paper presents a novel state-dependent Riccati equation (SDRE) control approach with the purpose of providing a more effective control design framework for continuous-time nonlinear systems to achieve a mixed nonlinear quadratic regulator and H∞ control performance criteria. By solving the generalized SDRE, the optimal control solution is found to achieve mixed performance objectives guaranteeing nonlinear quadratic optimality with inherent stability property in combination with H∞ type of disturbance reduction. An efficient computational algorithm is given to find the solution to the SDRE. The efficacy of the proposed technique is used to design the control system for inverted pendulum, an under-actuated nonlinear mechanical system.

Improved control performance of the 3‐DoF aeroelastic wing section: a TP model based 2D parametric control performance optimization

AbstractBased on the most recent Tensor Product model transformation solutions, the paper presents an improved control performance for the most recent version of the three Degree of Freedom aeroelastic wing section model including Stribeck friction, according to signals pitch, plunge, trailing edge and control value, based on practical engineering criteria such as overshoot, undershoot, signal end values and settling time. This is achieved through proposing a novel two dimensional parametric convex hull manipulation based method for Tensor Product model transformation based Control Design Frameworks. The approach provides two TP model representations for the different requirements of the controller and observer of a given model, opening the possibility to utilize the TP model transformation's convex hull manipulation potential in control performance optimization for a separate optimization of the two TP model representations. Numerical simulation results are provided to illustrate the control performance improvements of the aeroelastic wing section model through the proposed 2D parametric convex hull manipulation based design method.

Global stabilisation for a class of uncertain non-linear systems: a novel non-recursive design framework

In this paper, a novel global non-recursive stabilisation design framework is addressed for a class of inherent non-linear systems with the presence of system uncertainties and external nonvanishing disturbances. By virtue of the facility that the weighted homogeneity brings into the system synthesis procedure, a non-recursive design method is proposed to yield a globally effectiveness robust controller with its expression following a quasi-linear manner. By proceeding with a rigorous non-recursive stability analysis framework, which covers both global asymptotical and finite-time convergence cases, the common recursively treated derivative items in backstepping-based methods are totally avoided. Inspired by the homogeneous domination technique, a scaling gain performed as a bandwidth factor is introduced into the original system and hence the robustness of the controlled system can be adjusted to meet the practical performance requirements. A numerical example and its control performance simulations are given to illustrate the effectiveness and simplicity of the proposed controller design framework.