Distributed model predictive control for continuous‐time nonlinear systems based on suboptimal ADMM

This paper presents a distributed model predictive control (DMPC) scheme for continuous‐time nonlinear systems based on the alternating direction method of multipliers (ADMM). A stopping criterion in the ADMM algorithm limits the iterations and therefore the required communication effort during the DMPC solution at the expense of a suboptimal solution. Stability results are presented for the suboptimal DMPC scheme under two different ADMM convergence assumptions. In particular, it is shown that the required iterations in each ADMM step are bounded, which is also confirmed in simulation studies.     

Adaptive continuous‐time model predictive controller for implantable insulin delivery system in Type I diabetic patient

This paper presents a physiological model of glucose–insulin (GI) interaction and design of a Continuous‐time Model Predictive Controller (CMPC) to regulate the blood glucose (BG) level in Type I diabetes mellitus (TIDM) patients. For the designing of the CMPC, a nonlinear physiological model of TIDM patient is linearized as a ninth‐order state‐space model with an implanted insulin delivery device. A novel control approach based on Continuous‐time Model Predictive technique is proposed for the BG regulation with rejection of periodic or random meal and exercise disturbances in the process. To justify its efficacy a comparative analysis with Linear Quadratic Gaussian (LQG) control, and recently published control techniques like Proportional‐Integral‐Derivative (PID), Linear Quadratic Regulator with Loop Transfer Recovery (LQR/LTR) and H‐infinity has been established. The efficiency of the controller with respect to accuracy and robustness has been verified via simulation. The proposed controller performances are assessed in terms of ability to track a normoglycaemic set point of 81 mg/dl (4.5 mmol/l) in the presence of Gaussian and stochastic noise. Copyright © 2016 John Wiley & Sons, Ltd.     

Finite‐time convergence results in robust model predictive control

Robust asymptotic stability (asymptotic attractivity and ?‐δ stability) of equilibrium regions under robust model predictive control (MPC) strategies was extensively studied in the last decades making use of Lyapunov theory in most cases. However, in spite of its potential application benefits, the problem of finite‐time convergence under fixed prediction horizon has not received, with some few exceptions, much attention in the literature. Considering the importance in several applications of having finite‐time convergence results in the context of fixed horizon MPC controllers and the lack of studies on this matter, this work presents a new set‐based robust MPC (RMPC) for which, in addition to traditional stability guarantees, finite‐time convergence to a target set is proved, and moreover, an upper bound on the time necessary to reach that set is provided. It is remarkable that the results apply to general nonlinear systems and only require some weak assumptions on the model, cost function, and target set.     

Time‐delay dependent H∞ model simplification for singular systems with Markovian jumping parameters

The problem of H_∞ model simplification for singular systems with Markovian jumping parameters and time‐delay is investigated. For a given stochastic stable system, our attention is focused on the construction of reduced‐order models which guarantee the corresponding error system to be admissible and have a prescribed H_∞ error performance. A robust admissibility condition and a robust bounded real lemma are developed based on which, sufficient conditions for the existence of desired reduced‐order models are proposed. Desired reduced‐order model can be constructed when the proposed conditions are satisfied. The effectiveness of the proposed model reduction method is illustrated via a numerical example. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust continuous‐time controller design via structural Youla–Kučera parameterization with application to predictive control

This paper addresses the continuous‐time control of uncertain linear SISO plants and its nominal and robust stability and nominal and robust performance objectives. A specific application of the Youla–Ku?era (Q) parameterization concept leads to a new development of observer‐like controller structures. This method is combined with a nominal design of continuous‐time generalized predictive control suitable for both minimum‐phase and non‐minimum‐phase plants. The subsequent design procedure consists of two steps. Firstly, the nominal stability and nominal performance of the control system are established by using an analytical design methodology, based on a collection of closed‐loop prototype characteristics with definite time‐domain specifications. And secondly, a generic structure of the controller is enhanced by suitable Q‐parameters guaranteeing that the control system has the required robustness properties. The proposed structural (reduced‐order) Q‐parameterization relies on an observer structure of controllers, which can be easily enhanced with certain filters necessary for control robustification. To reduce the complexity of the resulting robust controllers, we suggest using a structural factorization, which allows for simple forms of robustifying (phase‐lag) correctors of low order, easy for implementation, and convenient for optimization and tuning. Two numerical examples are given to illustrate the composed technique and its practical consequences. Copyright © 2004 John Wiley & Sons, Ltd.     

LMI-based cooperative distributed model predictive control for Lipschitz nonlinear systems

In this paper, a distributed model predictive control is proposed to control Lipschitz nonlinear systems. The cooperative distributed scheme is considered where a global infinite horizon objective function is optimized for each subsystem, exploiting the state and input information of other subsystems. Thus, each control law is obtained separately as a state feedback of all system's states by solving a set of linear matrix inequalities. Due to convexity of the design, convergence properties at each iteration are established. Additionally, the proposed algorithm is modified to optimize only one control input at a time, which leads to a further reduction in the computation load. Finally, two application cases are studied to show the effectiveness of the proposed method.     

A framework of robust fault estimation observer design for continuous‐time/discrete‐time systems

A design framework of the observer‐based robust fault estimation for continuous‐time/discrete‐time systems is presented in this paper. Firstly, a multiconstrained fault estimation observer under the H_∞ performance specification with the regional pole constraint is proposed to achieve robust fault estimation. Then, the existence conditions for both continuous‐time/discrete‐time systems are derived explicitly. Furthermore, by introducing slack variables, improved results on the multiconstrained fault estimation observer design are obtained such that different Lyapunov functions can be separately designed for each constraint. Finally, simulation results of a vertical takeoff and landing aircraft are presented to illustrate our contributions. Copyright © 2012 John Wiley & Sons, Ltd.     

Receding horizon control for discrete‐time multiple input delay systems

This paper is concerned with stabilization problem for discrete‐time systems with multiple input delay. By defining a new cost function, the stabilization condition is derived based on monotonically nonincreasing of the optimal cost. It is shown that if the 2 weighting matrices in the cost function satisfy the given linear matrix inequality, receding horizon controller can stabilize the input delay systems. Moreover, the explicit stabilization controller with the new cost function is obtained by solving a finite horizon optimal control problem. A numerical example illustrates the effectiveness of the proposed method.     

Simultaneous fault detection and control design for switched linear systems based on dynamic observer

The problem of simultaneous fault detection and control (SFDC) for linear continuous‐time switched systems is addressed in this paper. An H _∞ formulation of the SFDC problem using dynamic observer is presented. In essence, a single unit called detector/controller depending on the system modes is designed, where the detector is a dynamic observer, and the controller is a state feedback controller based on the dynamic observer. It is shown that the dynamic observer can be used effectively to tackle the drawbacks of the existing methods of SFDC design. Extended linear matrix inequalities (LMIs) characterization is used to reduce the conservativeness by introducing additional matrix variables, so as to eliminate the coupling of Lyapunov matrices with the system matrices. Indeed, the idea presented in this paper is based on average dwell time and conservatism reduction approaches and applying the advantages of dynamic observers, which leads to some sufficient conditions for solvability of the SFDC problem in terms of LMI feasibility conditions. Simulation results illustrate the effectiveness of the proposed design methodology. Copyright © 2011 John Wiley & Sons, Ltd.     

A 2D‐based approach to guaranteed cost repetitive control for uncertain discrete‐time systems

This paper presents a two‐dimensional (2 D)‐based approach to the problem of guaranteed cost repetitive control for uncertain discrete‐time systems. The objective is to design a control law such that the closed‐loop repetitive control system is robustly stable and a certain bound of performance criteria is guaranteed for all admissible uncertainties. It is shown first how the proposed repetitive control scheme can be equivalently formulated in the form of a distinct class of 2 D system. Then, sufficient conditions for the existence of guaranteed cost control law are derived in terms of linear matrix inequality (LMI), and the control law matrices are characterized by the feasible solutions to this LMI. Moreover, an optimization problem is introduced to efficiently solve the optimal guaranteed cost control law by minimizing the upper bound of the cost function. The proposed approach is applicable not only to SISO systems, but also to MIMO systems. Two numerical examples are provided to demonstrate the effectiveness of the proposed controller design procedures. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimation and synthesis of reachable set for discrete‐time periodic systems

This paper is concerned with the problems of reachable set estimation and synthesis for discrete‐time periodic systems under bounded peak disturbances. For the reachable set estimation problem, the lifting approach and the pseudo‐periodic Lyapunov function approach are utilized to determine the bounding ellipsoids for the reachable set. By using the lifting approach, the periodic system is transformed into several time‐invariant systems; then, the bounding ellipsoids are determined through the transformed time‐invariant systems. By applying the pseudo‐periodic Lyapunov function approach, the bounding ellipsoids are determined through the original periodic system directly. Genetic algorithm is adopted in the pseudo‐periodic Lyapunov function approach to search for the optimal value of the decision variables. Moreover, based on the reachable set estimation results, state‐feedback controllers are designed for manipulating the reachable set. Finally, numerical examples are presented to verify the effectiveness of the theoretical findings. Copyright © 2015 John Wiley & Sons, Ltd.     

H2 filter design for discrete‐time Markov jump linear systems with partly unknown transition probabilities

The H₂ filter design problem for discrete‐time Markov jump linear systems with partly unknown transition probabilities is addressed in this paper. The so‐called partly unknown transition probabilities cover two cases: one is that some unknown elements have known lower and upper bounds, the other is that some unknown elements have no information available. By employing Finsler's lemma and linear matrix inequality (LMI) technique, sufficient conditions are developed in the LMI setting to design an H₂ filter such that the filtering error system is mean‐square stable and at the same time satisfies a prescribed H₂ performance index. Numerical examples are presented to illustrate the effectiveness of the developed theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Delay‐dependent H∞ control for singular Markovian jump systems with time delay

The problem of delay‐dependent H_∞ control is considered for singular Markovian jump systems with time delay. The aim of the problem is to design a state feedback controller, which guarantees that the resultant closed‐loop system is not only regular, impulse free and stochastically stable, but also satisfies a prescribed H_∞ performance level for all delays no larger than a given upper bound in terms of linear matrix inequality (LMI) approach. A strict LMI condition is developed to guarantee the existence of the desired state feedback controller. An explicit expression for the desired controller is also given. Numerical examples show the effectiveness of the proposed methods. Copyright © 2008 John Wiley & Sons, Ltd.     

Stochastic model predictive control for tracking linear systems

This note presents a stochastic formulation of the model predictive control for tracking (MPCT), based on the results of the work of Lorenzen et al. The proposed controller ensures constraints satisfaction in probability, and maintains the main features of the MPCT, that are feasibility for any changing setpoints and enlarged domain of attraction, even larger than the one delivered by Lorenzen et al, thanks to the use of artificial references and relaxed terminal constraints. The asymptotic stability (in probability) of the minimal robust positively invariant set centered on the desired setpoint is guaranteed. Simulations on a DC-DC converter show the benefits and the properties of the proposal.     

Delay‐dependent robust passive control for a class of nonlinear systems with time‐varying delays

In this paper, the problem of robust passive control for a class of nonlinear systems with time‐varying delays is considered. The uncertainties investigated in this paper are norm bounded and time varying, and they enter all system matrices. Based on the Lyapunov–Krasovskii functionals approach, a new robust passive control criterion is proposed in terms of linear matrix inequalities, which is dependent on the size of time delay. We also design a state feedback controller that guarantees a robust asymptotically stable and strictly passive closed‐loop system for all admissible uncertainties. Finally, two numerical examples are given to illustrate the effectiveness of the developed techniques. Copyright © 2007 John Wiley & Sons, Ltd.     

Fixed‐structure controller design for polytopic systems via LMIs

In this paper, a new approach for fixed‐structure H₂ controller design in terms of solutions to a set of linear matrix inequalities are given. Both discrete‐time and continuous‐time SISO time‐invariant systems are considered. Then the results are extended to systems with polytopic uncertainty. The presented methods are based on an inner convex approximation of the non‐convex set of fixed‐structure H₂ controllers. The designed procedures are initialized either with a stable polynomial or with a stabilizing controller. An iterative procedure for robust controller design is given that converges to a suboptimal solution. The monotonic decreasing of the upper bound on the H₂ norm is established theoretically for both nominal and robust controller design. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust preview control for uncertain discrete‐time systems based on LMI

For a class of uncertain discrete‐time systems, a preview controller based on linear matrix inequality is proposed. A new method is derived to construct an augmented error system instead of taking the difference of the error signal and the system equation. The new approach avoids applying the difference operator to the time‐varying matrix and can simplify the augmented error system. For the augmented error system of the uncertain system, state feedback is introduced. The sufficient condition of asymptotic stability of the closed‐loop system is derived for the performance index by using the relevant theorems of robust control theory. The condition can be realised by solving a linear matrix inequality optimization problem. By incorporating the controller obtained into the original system, we obtain the preview controller. Moreover, introducing an integrator allows the closed‐loop system to robustly track the desired tracking signal without steady‐state error.     

Robust reliability method and reliability‐based performance optimization for non‐fragile robust control design of dynamic system with bounded parametric uncertainties

An efficient robust reliability method for non‐fragile robust control design of dynamic system with bounded parametric uncertainties is presented systematically, in which the uncertainties existing in the controlled plant and controller realization are taken into account simultaneously in an integrated framework. Reliability‐based design optimization of non‐fragile robust control for parametric uncertain systems is carried out by optimizing the H₂ and H_∞ performances of the closed‐loop system, with the constraints on robust reliabilities. The non‐fragile robust controller obtained by the presented method may possess a coordinated optimum performance satisfying the precondition that the system is robustly reliable with respect to the uncertainties existing in controlled plant and controller. Moreover, the robustness bounds of uncertain parameters can be provided. The presented formulations are within the framework of linear matrix inequality and thus can be carried out conveniently. It is demonstrated by a numerical example that the presented method is effective and feasible. Copyright © 2016 John Wiley & Sons, Ltd.     

Multiobjective predictive cruise control for connected vehicle systems on urban conditions with InPA‐SQP

The connected vehicle (CV) system is one of the most effective core technologies in intelligent transportation systems. In order to solve the optimal velocity prediction problem for a CV system on urban roads, a multiobjective predictive cruise controller (MOPCC) for vehicles in the CV system is proposed to coordinate multiple performances including safety, tracking ability, ride comfort, and fuel economy. Firstly, with the ad hoc wireless communication technology, the signal phase and timing information is obtained to calculate the feasible velocity range for improving mobility. Then, the optimal target velocity of vehicles is computed by minimizing the fuel economic polynomial models of the vehicle system. Secondly, in order to systematically cope with those multiple performances, the Utopia point method is applied to change the multiobjective optimization problem into Utopia tracking problem. Furthermore, the MOPCC problem is formulated and solved by a fast numerical algorithm, ie, integrated perturbation analysis and sequential quadratic programming. Finally, simulations are presented to demonstrate the effectiveness of the proposed method in terms of improved the multiple performances.     

Set‐valued observer‐based active fault‐tolerant model predictive control

This paper proposes an integrated actuator and sensor active fault‐tolerant model predictive control scheme. In this scheme, fault detection is implemented by using a set‐valued observer, fault isolation (FI) is performed by set manipulations, and fault‐tolerant control is carried out through the design of a robust model predictive control law. In this paper, a set‐valued observer is used to passively complete the fault detection task, while FI is actively performed by making use of the constraint‐handling capability of robust model predictive control. The set‐valued observer is chosen to implement fault detection and isolation (FDI) because of its simple mathematical structure that is not affected by the type of faults such as sensor, actuator, and system‐structural faults. This means that only one set‐valued observer is needed to monitor all considered actuator and sensor statuses (health and fault) and to carry out the fault detection and isolation task instead of using a bank of observers (each observer matching a health/fault status). Furthermore, in the proposed scheme, the advantage of robust model predictive control is that it can effectively deal with system constraints, disturbances, and noises and allow to implement an active FI strategy, which can improve FI sensitivity when compared with the passive FI methods. Finally, a case study based on the well‐known two‐tank system is used to illustrate the effectiveness of the proposed fault‐tolerant model predictive control scheme. Copyright © 2016 John Wiley & Sons, Ltd.