Antiwindup design with guaranteed regions of stability: an LMI-based approach

This note addresses the design of antiwindup gains for obtaining larger regions of stability for linear systems with saturating inputs. Considering that a linear dynamic output feedback has been designed to stabilize the linear system (without saturation), a method is proposed for designing an antiwindup gain that maximizes an estimate of the basin of attraction of the closed-loop system. It is shown that the closed-loop system obtained from the controller plus the antiwindup gain can be modeled by a linear system with a deadzone nonlinearity. A modified sector condition is then used to obtain stability conditions based on quadratic Lyapunov functions. Differently from previous works these conditions are directly in linear matrix inequality form. Some numerical examples illustrate the effectiveness of the proposed design technique when compared with the previous ones.     

Antiwindup for stable linear systems with input saturation: an LMI-based synthesis

This paper considers closed-loop quadratic stability and L/sub 2/ performance properties of linear control systems subject to input saturation. More specifically, these properties are examined within the context of the popular linear antiwindup augmentation paradigm. Linear antiwindup augmentation refers to designing a linear filter to augment a linear control system subject to a local specification, called the "unconstrained closed-loop behavior." Building on known results on H/sub /spl infin// and LPV synthesis, the fixed order linear antiwindup synthesis feasibility problem is cast as a nonconvex matrix optimization problem, which has an attractive system theoretic interpretation: the lower bound on the achievable L/sub 2/ performance is the maximum of the open and unconstrained closed-loop L/sub 2/ gains. In the special cases of zero-order (static) and plant-order antiwindup compensation, the feasibility conditions become (convex) linear matrix inequalities. It is shown that, if (and only if) the plant is asymptotically stable, plant-order linear antiwindup compensation is always feasible for large enough L/sub 2/ gain and that static antiwindup compensation is feasible provided a quasi-common Lyapunov function, between the open-loop and unconstrained closed-loop, exists. Using the solutions to the matrix feasibility problems, the synthesis of the antiwindup augmentation achieving the desired level of L/sub 2/ performance is then accomplished by solving an additional LMI.     

On the convergence properties of adaptive pole-placementcontrollers with antiwindup compensators

To avoid the windup problem in adaptive pole-placement controllers in the presence of a saturating input, an antiwindup compensator based on a generalization to the conditioning technique is introduced to the controller. This modification to the controller also provides a unified approach to investigate the asymptotic properties of the adaptive controllers with a class of antiwindup compensators, at least, when applied to stable processes     

Solving a system of linear equations: From centralized to distributed algorithms

For a wide range of control engineering applications, the problem of solving a system of linear equations is often encountered and has been well studied. Traditionally, this problem has been mainly solved in a centralized manner. However, for applications related to large-scale complex networked systems, centralized algorithms are often subjected to some practical issues due to limited computational power and communication bandwidth. As a promising and viable alternative, distributed algorithms can effectively address the issues associated with centralized algorithms by solving the problem efficiently in a multi-agent setting that accords with the distributed nature of networked systems. Distributed algorithms decompose the entire problem into many sub-problems that are solved by individual agents in a cooperative manner. In this survey paper, we provide a detailed overview of the state of the art relevant to distributed algorithms for solving a system of linear equations. We will first review basic distributed algorithms including both discrete-time and continuous-time algorithms. Then we will discuss the extended algorithms to achieve communication efficiency. Furthermore, we will also introduce distributed algorithms to obtain the minimum-norm solution for a system of linear equations with multiple solutions, as well as the least-squares solution when there is no solution. Finally, the relationship of distributed algorithms for solving a system of linear equations to the existing distributed optimization algorithms is discussed.     

Robust pole assignment for systems with parameters

In this paper we investigate issues related to the control of linear multivariate systems which contain structured, parametric-type uncertainties. The objective is to construct parameter-independent proper compensators that provide ‘robust control’. Specifically, we consider the question of robust pole assignment. Systems are described by matrix fraction representations which involve a structured parametric form of uncertainty. We suggest conditions for robust pole assignability and demonstrate how to construct the required proper compensators. For the problem considered, we show that the class of systems which satisfy these conditions is quite large and we include results on generic solvability. The method is demonstrated by a physical example.     

An Architecture for Design and Analysis of High-Performance Robust Antiwindup Compensators

In this note, a general framework for the design and analysis of high-performance robust antiwindup (AW) compensators is presented. The proposed framework combines the Weston-Postlethwaite AW scheme with ideas from residual generation and from robust control architectures based on high-performance nominal controllers. It is shown that the framework is well connected to the Youla controller parameterization and to fault tolerant/detection schemes. Furthermore, the proposed framework provides a transparent analysis of the interactions between the different design parameters which allows for a clearer design tradeoff between robust stability and robust performance for the saturated and unsaturated closed loops.     

Stability analysis and antiwindup design of uncertain discrete-time switched linear systems subject to actuator saturation

This paper investigates the stability analysis and antiwindup design problem for a class of discrete-time switched linear systems with time-varying norm-bounded uncertainties and saturating actuators by using the switched Lyapunov function approach.Supposing that a set of linear dynamic output controllers have been designed to stabilize the switched system without considering its input saturation,we design antiwindup compensation gains in order to enlarge the domain of attraction of the closed-loop system in the presence of saturation.Then,in terms of a sector condition,the antiwindup compensation gains which aim to maximize the estimation of domain of attraction of the closed-loop system are presented by solving a convex optimization problem with linear matrix inequality(LMI)constraints.A numerical example is given to demonstrate the effectiveness of the proposed design method.     

Performance-Oriented Antiwindup for a Class of Linear Control Systems With Augmented Neural Network Controller

This paper presents a conditioning scheme for a linear control system which is enhanced by a neural network (NN) controller and subjected to a control signal amplitude limit. The NN controller improves the performance of the linear control system by directly estimating an actuator-matched, unmodeled, nonlinear disturbance, in closed-loop, and compensating for it. As disturbances are generally known to be bounded, the nominal NN-control element is modified to keep its output below the disturbance bound. The linear control element is conditioned by an antiwindup (AW) compensator which ensures performance close to the nominal controller and swift recovery from saturation. For this, the AW compensator proposed is of low order, designed using convex linear matrix inequalities (LMIs) optimization     

Linear time computation of feasible regions for robust compensators

We introduce an application of computational geometry, including figures of merit standard in the analysis of algorithms, to the design of robust control systems. With respect to system transfer function magnitude, we show how to compute feasible regions for compensators whose plant transfer function is the ratio of uncertain interval polynomials. Our solution sweeps the Minkowski quotient set of the corresponding Kharitonov rectangles. Enumerating the winding numbers of Minkowski sum convolution curves, we obtain optimal, linear time algorithms that eliminate three factors from the execution inefficiency of traditional gridding approaches. We illustrate with examples pertinent to quantitative feedback theory (QFT). Copyright © 2001 John Wiley & Sons, Ltd.     

Stability of discrete override and cascade-limiter single-loopcontrol systems

Nonlinear elements such as internal limits in cascade regulators or override loops are often added to standard linear regulators in order to keep an additional process output within the limits during startup or large load swings. These systems generally are designed intuitively and tuned by experiments on the plant. Stability analysis is not often feasible due to time constraints, but could improve both security and insight. The authors are engaged in the development of analytical tools for the design of such systems. Here, the equivalence of different discrete-time implementations is proved. Stability tests are prepared that are directly applicable in practical design work. The analysis is shown to cover also control saturation with antiwindup in discrete forms and all corresponding cases with continuous regulators. A numerical example is given to illustrate the design procedures     

Mathematica implementation of output-feedback pole assignment for uncertain systems via symbolic algebra

This paper presents the application of symbolic algebra techniques to the MATHEMATICA implementation of a set of output-feedback pole assignment algorithms for systems characterized by parametric uncertainty. For multivariable systems there may be more than one feedback matrix solution leading to the same closed-loop poles based on the same algorithm used. Thus over-parameterized solutions are sought by generalizing the existing algorithms with extra degrees of freedom retained in the symbolic variables. The general parametric form of output-feedback compensators is developed in terms of the uncertain parameters and symbols representing the extra degrees of freedom. The implementation of three output-feedback pole assignment techniques is presented, with the theory briefly introduced and examples illustrating the effectiveness of the algorithms described.     

Recursive algorithms for Bayes smoothing with uncertain observations

Recursive algorithms for the Bayes solution of fixed-interval, fixed-point, and fixed-lag smoothing under uncertain observations are presented. The Bayes smoothing algorithms are obtained for a Markovian system model with Markov uncertainty, a model more general than the one used in linear smoothing algorithms. The Bayes fixed-interval smoothing algorithm is applied to a Gauss-Markov example. The simulation results for this example indicate that the MSE performance of the Bayes smoother is significantly better than that of the linear smoother.     

Computer-aided design of P or PI plus rate feedback compensators for linear systems

A computer-aided solution for the gains of P or PI plus rate feedback compensators based on an exact model-matching criterion is developed. The corresponding Matlab functions are developed, and the software listings are given. Using the developed design tool, control engineers are able to obtain P or PI plus rate feedback gains much more quickly than traditional methods of design. Demonstration example problems for control of linear plants are presented, and results are compared with those obtained by other approaches reported in the open literature.     

Randomized algorithms for probabilistic robustness with real andcomplex structured uncertainty

There has been a growing interest in developing randomized algorithms for probabilistic robustness of uncertain control systems. Unlike classical worst case methods, these algorithms provide probabilistic estimates assessing, for instance, if a certain design specification is met with a given probability. One of the advantages of this approach is that the robustness margins can be often increased by a considerable amount, at the expense of a small risk. In this sense, randomized algorithms may be used by the control engineer together with standard worst case methods to obtain additional useful information. The applicability of these probabilistic methods to robust control is presently limited by the fact that the sample generation is feasible only in very special cases which include systems affected by real parametric uncertainty bounded in rectangles or spheres. Sampling in more general uncertainty sets is generally performed through overbounding, at the expense of an exponential rejection rate. In the paper, randomized algorithms for stability and performance of linear time invariant uncertain systems described by a general M-Δ configuration are studied. In particular, efficient polynomial-time algorithms for uncertainty structures Δ consisting of an arbitrary number of full complex blocks and uncertain parameters are developed     

Output violation compensation for systems with output constraints

The problem of output constraints in linear systems is considered, and a new methodology which helps the closed loop respect these limits is described. The new methodology invokes ideas from the antiwindup literature in order to address the problem from a practical point of view. This leads to a design procedure very much like that found in antiwindup design. First, a linear controller ignoring output constraints is designed. Then, an additional compensation network which ensures that the output limits are, as far as possible, respected is added. As the constraints occur at the output, global results can be obtained for both stable and unstable plants.     

Output feedback control of linear two-time-scale systems

Output feedback control of linear time-invariant singularly perturbed systems is studied. The set of all compensators that stabilize a singularly perturbed system while preserving its two-time-scale structure is parameterized. The parameterization is used to show that any two-frequency-scale stabilizing compensator can be asymptotically approximated by a compensator designed via a sequential procedure. In this procedure, a fast (high-frequency) compensator is designed first to stabilize the fast model of the system. Then, a strictly proper slow (low-frequency) compensator is designed to stabilize a modified slow model. The parallel connection of the two compensators forms a two-frequency-scale stabilizing compensator for the singularly perturbed system.     

双层自适应快速super twisting控制算法

为提高super twising算法的收敛速度,解决现有算法存在的增益过估计问题,提出了两种自适应增益快速super twisting算法.分别通过快速终端滑模趋近律和增加线性项加快收敛速度.利用基于等效控制的双层自适应律调节增益,保证滑模存在条件的成立,同时使增益尽量的小.采用Lyapunov方法证明了新算法具有更优良的收敛特性,根据有界实引理和Schur补定理分别给出了两种算法的参数整定策略.仿真算例表明,在相同控制参数下,新算法的能耗与原算法接近,并具有更快的收敛速度和更强的鲁棒性.     

Deadtime compensation for nonlinear processes with disturbances

The control problem of time delay non-linear systems that are perturbed by disturbances is discussed. By coordinate transformations and feedback and prediction of the transformed states, we first linearize the perturbed non-linear systems into controllable quasi-linear systems with disturbances. Then, we can apply the well-developed linear control theory to stabilize the transformed systems. Thus, stable quasi-linear systems with time delay can be obtained. Furthermore, we may implement powerful deadtime compensation methods to study the performance of the proposed dynamic compensators, a Smith predictor and a new modified Smith predictor, for disturbance rejection. Finally, a typical non-linear chemical process, a continuous stirred tank reactor, is used as an example system to demonstrate the effectiveness of these deadtime compensators     

Synthesis of Stabilizing Antiwindup Controllers Using Piecewise Quadratic Lyapunov Functions

We consider the problem of antiwindup controller synthesis based on the general antiwindup framework presented in Kothare (Automatica, vol. 30, no. 12, pp. 1869-1883, 1994) applicable to linear time-invariant systems (LTI) subject to a saturating actuator. Our synthesis approach takes advantage of the fact that the antiwindup system is a piecewise affine system and thus, we can utilize piecewise quadratic Lyapunov function theory Johansson and Rantzer (IEEE Trans. Autom. Control, vol. 43, no. 4, pp. 555-559, Apr. 1998), Rantzer and Johansson (IEEE Trans. Autom. Control, vol. 45, no. 4, pp. 629-637, Apr. 2000), and Johansson (Proc. 14th World Congr., Beijing, China, 1999, pp. 521-5260) to determine a stabilizing antiwindup control law. The synthesis problem is expressed in terms of bilinear matrix inequalities (BMIs) and is solved using an iterative approach as well as using commercial software. The performance of the system is optimized by minimizing an upper bound on the induced gain of the system. The proposed approach is demonstrated using examples.