Multiple robust H∞ controller design using the nonsmooth optimization method

This paper proposes a systematic technique to design multiple robust H_∞ controllers. The proposed technique achieves a desired robust performance objective, which is impossible to achieve with a single robust controller, by dividing the uncertainty set into several subsets and by designing a robust controller to each subset. To achieve this goal with a small number of divisions of the uncertainty set, an optimization problem is formulated. Since the cost function of this optimization problem is not a smooth function, a numerical nonsmooth optimization algorithm is proposed to solve this problem. This method avoids the use of Lyapunov variables, and therefore it leads to a moderate size optimization problem. A numerical example shows that the proposed multiple robust control method can improve the closed‐loop performance when a single robust controller cannot achieve satisfactory performance. Copyright © 2009 John Wiley & Sons, Ltd.     

Stability‐ and performance‐robustness tradeoffs: MIMO mixed‐µ vs complex‐µ design

We present a non‐trivial case study designed to highlight some of the practical issues that arise when using mixed‐µ or complex‐µ robust synthesis methodologies. By considering a multi‐input multi‐output three‐cart mass–spring–dashpot (MSD) with uncertain parameters and dynamics, it is demonstrated that optimized performance (disturbance‐rejection) is reduced as the level of uncertainty in one or two real parameters is increased. Comparisons are made (a) in the frequency domain, (b) by RMS values of key signals and (c) in time‐domain simulations. The mixed‐µ controllers designed are shown to yield superior performance as compared with the classical complex‐µ design. The singular value decomposition analysis shows the directionality changes resulting from different uncertainty levels and from the use of different frequency weights. The nominal and marginal stability regions of the closed‐loop system are studied and discussed, illustrating how stability margins can be extended at the cost of reducing performance. Copyright © 2008 John Wiley & Sons, Ltd.     

On the formulation and solution of robust performance problems

A new approach to robust performance problems is proposed in this paper. The approach involves the optimisation of the so-called performance weights subject to a constraint, formulated in terms of the structured singular value, which ensures the existence of a stabilising feedback compensator that achieves robust performance with respect to the optimised performance weights and an uncertain plant set. Optimising over the performance weights in this way gives rise to an algorithm for systematically trading-off desired performance against specified plant uncertainty and performance limitations due to plant dynamics. The algorithm also yields a robust controller. The designer is only required to specify the uncertain plant set and an optimisation directionality, which is used to reflect desired closed-loop performance over frequency in terms of a corresponding cost function. Design of this directionality appears to be simpler than designing the performance weights directly.     

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

An iterative algorithm for maximizing robust performance in loop‐shaping design

In this paper, an algorithm that gives the best achievable performance bound on a given control problem is proposed using the loop‐shaping design framework. In view of standard design requirements, the robust performance is maximized at low and high frequencies while keeping the robust stability margin above a specified level, and the robust stability margin is directly improved at mid frequencies (around crossover). The proposed frequency‐dependent optimization problem is cast in an LMI framework. The resulting solution algorithm simultaneously synthesizes loop‐shaping weights and a stabilizing controller that achieve the maximum performance for a given level of robust stability margin corresponding to sufficient gain and phase margins of the closed‐loop system. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust Performance Controller Synthesis Based on Discrete‐Time Noncausal Linear Periodically Time‐Varying Scaling

This paper is concerned with the technique called discrete‐time noncausal linear periodically time‐varying (LPTV) scaling for robust stability analysis and synthesis. It is defined through the lifting treatment of discrete‐time systems, and naturally leads to a sort of noncausal operation of signals. In the robust stability analysis of linear time‐invariant (LTI) systems, it has been shown that even static noncausal LPTV scaling induces some frequency‐dependent scaling when it is interpreted in the context of lifting‐free treatment. This paper first discusses in detail different aspects of the effectiveness of noncausal LPTV scaling, with the aim of showing its effectiveness in controller synthesis. More precisely, we study the robust performance controller synthesis problem, where we allow the controllers to be LPTV. As in the LTI robust performance controller synthesis problem, we tackle our problem with an iterative method without guaranteed convergence to a globally optimal controller. Despite such a design procedure, the closed‐loop H_∞ performance is expected to improve as the period of the controller is increased, and we discuss how the frequency‐domain properties of noncausal LPTV scaling could contribute to such improvement. We demonstrate with a numerical example that an effective LPTV controller can be designed for a class of uncertainties for which the well‐known μ‐synthesis fails to derive even a robust stabilization controller.     

Robust feedforward design in the presence of LTI/LTV uncertainties

A practical method is proposed for the convex design of robust feedforward controllers which ensures H_∞/L₂ performance in the face of LTI and arbitrarily time‐varying model uncertainties. A technique that computes the global minimum of this difficult infinite dimensional optimization problem is proposed, as well as a suboptimal but computationally less involved algorithm. Convergence is proved. An efficient way to analyse the robustness properties of a closed loop with or without feedforward controller is obtained as a subproblem. A missile example illustrates the efficiency of the scheme: a robust feedforward controller is designed either on the continuum of linearized time‐invariant models (corresponding to trim points) or on a quasi‐LPV model representing the non‐linear one. Copyright © 2007 John Wiley & Sons, Ltd.     

Robust nonlinear ship course‐keeping control by H∞ I/O linearization and μ‐synthesis

In this paper, the H_∞ input/output (I/O) linearization formulation is applied to design an inner‐loop nonlinear controller for a nonlinear ship course‐keeping control problem. Due to the ship motion dynamics are non‐minimum phase, it is impossible to use the ordinary feedback I/O linearization to resolve. Hence, the technique of H_∞ I/O linearization is proposed to obtain a nonlinear H_∞ controller such that the compensated nonlinear system approximates the linear reference model in I/O behaviour. Then a μ‐synthesis method is employed to design an outer‐loop robust controller to address tracking, regulation, and robustness issues. The time responses of the tracking signals for the closed‐loop system reveal that the overall robust nonlinear controller is able to provide robust stability and robust performance for the plant uncertainties and state measurement errors. Copyright © 2002 John Wiley & Sons, Ltd.     

On delay‐dependent LMI‐based guaranteed cost control of uncertain neutral systems with discrete and distributed time‐varying delays

In this paper, the problem of designing robust guaranteed cost control law for a class of uncertain neutral system with a given quadratic cost function is considered. Based on Lyapunov–Krasovskii functional theory, a delay‐dependent criterion for the existence of guaranteed cost controller is expressed in the form of two linear matrix inequalities (LMIs), which can be solved by using effective LMI toolbox. Moreover, a convex optimization problem satisfying some LMI constraints is formulated to solve a guaranteed cost controller which achieves the minimization of the closed‐loop guaranteed cost. An efficient approach is proposed to design the guaranteed cost control for uncertain neutral systems. Computer software Matlab can be used to solve all the proposed results. Finally, a numerical example is illustrated to show the usefulness of our obtained design method. Copyright © 2006 John Wiley & Sons, Ltd.     

Robust Constrained Model Predictive Control for Discrete‐Time Uncertain System in Takagi‐Sugeno's Form

In this paper, we investigate a robust constrained model predictive control synthesis approach for discrete‐time Takagi‐Sugeno's (T‐S) fuzzy system with structured uncertainty. The key idea is to determine, at each sampling time, a state feedback fuzzy predictive controller that minimizes the performance objective function in the infinite time horizon by solving a class of linear matrix inequalities (LMIs) optimization problem. To do this, the fuzzy predictive controller is designed on the basis of non‐parallel distributed compensation (non‐PDC) control law, relaxed stability conditions of the closed‐loop fuzzy system are developed by employing an extended nonquadratic Lyapunov function and introducing additional slack and collection matrices. In addition, the presented approach is capable of ensuring the robust asymptotic stability as well as the recursive feasibility of the closed‐loop fuzzy system. Simulations on a highly nonlinear continuous stirred tank reactor (CSTR) are eventually presented to demonstrate the effectiveness of the developed theoretical approach.     

Nonsmooth µ‐synthesis

We revisit robust complex‐ and mixed‐ µ‐synthesis problems based on upper bounds and show that they can be recast as specially structured controller design programs. The proposed reformulations suggest a streamlined handling of µ‐synthesis problems using recently developed (local) nonsmooth optimization methods, where both scalings or multipliers and a controller of given structure are obtained simultaneously. A first cut of the nonsmooth programming software for structured H_∞ synthesis is made available through the MATLAB R2010b Prerelease, Robust Control Toolbox Version 3.5 developed by The MathWorks, Inc. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust model predictive control for polytopic uncertain systems with state saturation nonlinearities under Round‐Robin protocol

This paper is concerned with the robust model predictive control (RMPC) problem for polytopic uncertain systems with state saturation nonlinearities under the Round‐Robin (RR) protocol. With respect to the practical application, one of the most commonly encountered obstacles that stem from the physical limitation of system components, ie, state saturation, is adequately taken into consideration. In order to reduce the network transmission burden and improve the utilization of the network from the controller nodes to the actuator node, a so‐called RR protocol is employed to orchestrate the data transmission order. At each transmission instant, only one controller node that obtains the priority is accessible to the shared communication network. Our aim of the underlying problem is to design a set of controllers in the framework of RMPC such that the closed‐loop system is asymptotically stable. By taking the influence of the RR protocol and the state saturation precisely into account, some sufficient criteria are established in terms of the token‐dependent Lyapunov‐like approach. Then, an online optimization problem subjected to some matrix inequality constraints is provided, and the desired controllers can be obtained by solving the certain upper bound of the objective addressed. Finally, a distillation process example is provided to illustrate the effectiveness of the proposed RMPC approach.     

Robust output‐feedback control of state‐multiplicative noisy discrete‐time systems

Linear discrete‐time systems with stochastic and deterministic polytopic type uncertainties in their state‐space model are considered. A dynamic output‐feedback controller is obtained via a new approach that allows a derivation of a controller in spite of parameter uncertainty. In the proposed approach, the system is described via a difference equation and an augmented system is then used to obtain the output‐feedback controller parameters. The controller is obtained without assuming a specific structure to the quadratic Lyapunov function, and it is the first time that an output‐feedback controller is obtained for robust state‐multiplicative systems. The controller minimizes the stochastic L₂‐gain of the closed‐loop where a cost function is defined to be the expected value of the standard performance index with respect to the stochastic uncertainty. Two examples are given where the second of which demonstrates the applicability of our theory to a robot manipulator system. Copyright © 2016 John Wiley & Sons, Ltd.     

Iterative ‐conic controller synthesis

This paper proposes a method to synthesize controllers that minimize an upper bound on the closed‐loop ‐norm while imposing desired controller conic bounds. An initial conic controller is synthesized and iteratively improved. Conic sectors can be used to characterize a variety of input‐output properties, such as gain, phase, and minimum gain. If such plant properties hold robustly to uncertainty present, then closed‐loop stability can be ensured robustly via the Conic Sector Theorem by imposing desired controller conic bounds. Consequently, this paper provides a versatile optimal and robust controller synthesis method. Moreover, it relies only on the solution of convex optimization problems subject to linear matrix inequality constraints, making it readily implementable.     

Robust control of systems with sector nonlinearities via convex optimization: A data‐driven approach

In this paper, a new data‐driven method for designing robust controllers is proposed for systems with sector‐bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex constraints that guarantee the stability of the closed‐loop system. The main feature of the proposed approach is that only the frequency response data of the linear part of the system is used for guaranteeing the stability of the closed‐loop nonlinear system. Additionally, a convex optimization problem is formulated to ensure performance with respect to the fundamental component of a sector‐bounded nonlinearity. The case study illustrates how the proposed method can be used to control uncertain systems that are subject to sector‐bounded nonlinearities.     

H∞ Guaranteed Cost Control for LPV Systems Subject to The Gain Constraint

This paper deals with the problem of H_∞ guaranteed cost control for linear parameter varying (LPV) systems subject to the gain constraint. Specifically, our main goal is to design a controller such that the closed‐loop system is exponentially stable with the H_∞ performance index, the quadratic performance index, and the gain within the desired constraints over the entire parameter region. In order to achieve this goal, less conservative and more practical sufficient conditions for the existence of the state feedback controller are proposed by introducing the parameter dependent Lyapunov function and many extra freedom degrees in terms of linear matrix inequalities and a free parameter matrix. The parameter matrix aspecially can regulate the gain freely without the influence of the desired performance to meet the additional design criteria enhancing the practicability and the design flexibility. As a special case, relevant results are extended to design a static output feedback controller. One numerical example is used to show advantages of the proposed approach.     

Stabilization of Single‐Input LTI Systems by Proportional‐Derivative Feedback

This article presents an efficient solution to the stabilization pole placement problem for single‐input linear time‐invariant (LTI) systems by proportional‐derivative (PD) feedback. For a controllable system, any arbitrary closed‐loop poles can be placed in order to achieve the desired closed‐loop system performance. Its derivation is based on the transformation of linear system into Hessenberg form by a special coordinate transformation before solving the pole placement problem. The available degrees of freedom offered by PD feedback are utilized to obtain closed‐loop systems with small gains. So, the minimization problem for a suitably chosen cost function is formulated. Simulation results are included to show the effectiveness of the proposed approach.     

Observer‐based H ∞ output tracking control for networked control systems

This paper is concerned with observer‐based H _∞ output tracking control for networked control systems. An observer‐based controller is implemented through a communication network to drive the output of a controlled plant to track the output of a reference model. The inputs of the controlled plant and the observer‐based tracking controller are updated in an asynchronous way because of the effects of network‐induced delays and packet dropouts in the controller‐to‐actuator channel. Taking the asynchronous characteristic into consideration, the resulting closed‐loop system is modeled as a system with two interval time‐varying delays. A Lyapunov–Krasovskii functional, which makes use of information about the lower and upper bounds of the interval time‐varying delays, is constructed to derive a delay‐dependent criterion such that the closed‐loop system has a desired H _∞ tracking performance. Notice that a separation principle cannot be used to design an observer gain and a control gain due to the asynchronous inputs of the plant and the controller. Instead, a novel design algorithm is proposed by applying a particle swarm optimization technique with the feasibility of the stability criterion to search for the minimum H _∞ tracking performance and the corresponding gains. The effectiveness of the proposed method is illustrated by an example. Copyright © 2013 John Wiley & Sons, Ltd.     

An LMI approach to guaranteed cost control for uncertain linear neutral delay systems

This paper considers the problem of guaranteed cost control for uncertain neutral delay systems with a quadratic cost function. The system under consideration is subject to norm‐bounded time‐varying parametric uncertainty appearing in all the matrices of the state‐space model. The problem we address is the design of a state feedback controller such that the closed‐loop system is not only stable but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of guaranteed cost controllers is given in terms of a linear matrix inequality (LMI). When this condition is feasible, the desired state feedback controller gain matrices can be obtained via convex optimization. An illustrative example is provided to demonstrate the effectiveness of the proposed approach. Copyright © 2002 John Wiley & Sons, Ltd.