Orbital feedback linearization for multi‐input control systems

A nonlinear control system is said to be orbital feedback linearizable if there exist an invertible static feedback and a change of time scale (depending on the state) which transform the system into a linear system. We give geometric necessary and sufficient conditions describing multi‐input control‐affine systems that are orbital feedback linearizable out of equilibria and in the case of equal controllability indices. We also describe a construction of the time rescaling needed to orbitally linearize the system. Moreover, we analyze close relations between orbital feedback linearizable control‐affine systems and control‐linear systems that are feedback equivalent to a multi‐chained form comparing geometric structures corresponding to both problems. We illustrate our results by two examples, one being a rigid bar moving in .Copyright © 2014 John Wiley & Sons, Ltd.     

Stabilization of strict‐feedback nonlinear systems with input delay using closed‐loop predictors

In this paper, we consider the control problem of strict‐feedback nonlinear systems with time‐varying input and output delays. The approach is based on the usual observer/predictor/feedback approach, but the novelty is the use of the closed‐loop dynamics in the predictor. This approach allows to develop two designs, an instantaneous predictor and a delay differential equation‐based predictor, that both attain the same performance in terms of system trajectories and input signal as in the case with no delays. The design based on delay differential equations allows to build a cascade of predictors to deal with arbitrarily large delay bounds. The resulting controller is much simpler to implement than classical infinite‐dimensional predictors, and it is robust with respect to actuation and measurement disturbances. We illustrate the approach with an application to the control of a chaotic system with input delay. Copyright © 2016 John Wiley & Sons, Ltd.     

Dual observer‐based compensators for nonlinear systems

In this article, the concept of dual observer‐based compensators is extended from linear to nonlinear systems. It is shown that a dual observer‐based compensator achieves stabilization by rendering an invariant manifold attractive in which desired dynamics can be assigned. The design of these compensators for nonlinear systems is considerably simple if a flat output of the system to be controlled is known which is illustrated by means of a simple example. Copyright © 2012 John Wiley & Sons, Ltd.     

On singularities of flat affine systems with n states and n−1 controls

We study the set of intrinsic singularities of flat affine systems with n?1 controls and n states using the notion of Lie‐Bäcklund atlas, previously introduced by the authors. For this purpose, we prove two easily computable sufficient conditions to construct flat outputs as a set of independent first integrals of distributions of vector fields: the first one in a generic case, namely, in a neighborhood of a point where the n?1 control vector fields are independent and the second one at a degenerate point where p?1 control vector fields are dependent of the n?p others, with p>1. After introducing the Γ‐accessibility rank condition, we show that the set of intrinsic singularities includes the set of points where the system does not satisfy this rank condition and is included in the set where a distribution of vector fields introduced in the generic case is singular. We conclude this analysis by three examples of apparent singularities of flat systems in generic and nongeneric degenerate cases.     

On static output‐feedback stabilization for multi‐input multi‐output positive systems

This paper revisits the static output‐feedback stabilization problem for positive systems. We first point out that for a class of positive systems whose output matrix has a particular row echelon form, this problem can be completely solved via linear programming. By duality, the result is also valid when the column echelon form of the input matrix has a particular structure. Along this line, by augmenting the output matrix as well as the feedback gain matrix, an iterative convex optimization algorithm is developed for the more general case. Finally, we show that the proposed method has advantages over existing works via several numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.     

Output feedback tracking control for lower‐triangular nonlinear time‐delay systems with asymmetric input saturation

In this paper, the problem of output feedback tracking control is investigated for lower‐triangular nonlinear time‐delay systems in the presence of asymmetric input saturation. A novel design program based on a dynamic high gain design approach is proposed to construct an output feedback tracking controller. The innovation here is that the problem of constructing tracking controller can be transformed into the problem of constructing two dynamic equations, with one being utilized to deal with the nonlinear terms and the other one being applied to analyze the influence of asymmetric input saturation. It is proved by an appropriate Lyapunov‐Krasovskii functional that the proposed tracking controller subject to saturation can ensure that all the signals of the closed‐loop system are globally bounded and the tracking error is prescribed sufficiently small when time is long enough. A practical example is given to illustrate the effectiveness of the proposed method.     

QFT design of multi‐loop nonlinear control systems

In control practice, one of the fundamental limitations of feedback is given by the sensor noise effect. This problem is still more important in uncertain nonlinear control systems. This work extends the previous multi‐loop QFT technique, specifically designed to accommodate bandwidth limitation, to the nonlinear case. Copyright © 2000 John Wiley & Sons, Ltd.     

A‐Orbital feedback linearization of multiinput control affine systems

This article deals with transformations of multiinput nonlinear control systems into linear controllable systems. For multiinput control affine systems, the notion of A‐orbital feedback linearizability is introduced which generalizes the notion of orbital feedback linearizability and is based on input‐dependent time scalings. A necessary and sufficient condition for A‐orbital feedback linearizability is derived for multiinput control affine systems. On the basis of this condition, an A‐orbital feedback linearization algorithm is developed. It is revealed that the proposed concept extends the existing approaches to orbital feedback linearization. More precisely, it is proved that if a system is A‐orbitally feedback linearizable in a neighborhood of some point, the dimension of the state is greater than that of the input by at least three, and the time scaling essentially depends on the input, then the system cannot be orbitally feedback linearized around that point.     

Bounded control of feedforward nonlinear systems subject to input time‐delay

This article is concerned with the global stabilization problem of a family of feedforward nonlinear time‐delay systems whose linearized system consists of multiple distinct oscillators. To fully utilize the delayed information and maintain the state decoupling property in the controller design, the considered nonlinear feedforward system is first transformed into a new system which contains time delays in both its input and states based on a novel model transformation containing time delays, and then the stabilizing saturated controller for the transformed system is designed based on the recursive design method. Meanwhile, explicit stability conditions are also provided. When the linearized system is a cascade of multiple oscillators and multiple integrators, a modified saturated feedback control utilizing not only the current state but also the delayed state is also established for the corresponding global stabilization problem. Two examples, including a practical one, are given to show the effectiveness and superiority of the proposed approaches.     

Adaptive finite‐time neural backstepping control for multi‐input and multi‐output state‐constrained nonlinear systems using tangent‐type nonlinear mapping

This article focuses on the problem of adaptive finite‐time neural backstepping control for multi‐input and multi‐output nonlinear systems with time‐varying full‐state constraints and uncertainties. A tan‐type nonlinear mapping function is first proposed to convert the strict‐feedback system into a new pure‐feedback one without constraints. Neural networks are utilized to cope with unknown functions. To improve learning performance, a composite adaptive law is designed using tracking error and approximate error. A finite‐time convergent differentiator is adopted to avoid the problem of “explosion of complexity.” By theoretical analysis, all the signals of system are proved to be bounded, the outputs can track the desired signals in a finite time, and full‐state constraints are not transgressed. Finally, comparative simulations are offered to confirm the validity of the proposed control scheme.     

On the multi‐input second‐order sliding mode control of nonlinear uncertain systems

This note addresses the multi‐input second‐order sliding mode control design for a class of nonlinear multivariable uncertain dynamics. Among the most important peculiarities of the considered control problem, the considered sliding vector variable has a uniform vector relative degree [2,2, … ,2] with respect to the vector control variable, and only the sign of the sliding vector and of its derivative are available for feedback. Additionally, the symmetric part of the state‐dependent control matrix is supposed to be positive definite. Under some further mild restrictions on the uncertain system's dynamics, a control algorithm that realizes a multi‐input version of the ‘twisting’ second‐order sliding mode control algorithm is suggested. Simple controller tuning conditions are derived by means of a constructive Lyapunov analysis, which demonstrates that the suggested control algorithm guarantees the semiglobal asymptotic convergence to the sliding manifold. Simulation results, which confirm the good performance of the proposed scheme and investigate the actual accuracy obtained under the discrete‐time implementation effects, are given. Copyright © 2011 John Wiley & Sons, Ltd.     

Continuous simultaneous stabilization of single‐input nonlinear stochastic systems

This paper investigates the simultaneous stabilization of a collection of continuous single‐input non‐linear stochastic systems, with coefficients that are not necessarily locally Lipschitz. A sufficient condition for the existence of a continuous simultaneously stabilizing feedback control is proposed — it is based on the generalized stochastic Lyapunov theorem and on the technique of stochastic control Lyapunov functions. This condition is also necessary, provided that the system's coefficients satisfy some regularity conditions. Moreover, the proposed feedback can be chosen to be bounded under the assumption that appropriate control Lyapunov functions are known. All the proposed simultaneously stabilizing state feedback controllers are explicitly constructed. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed approach.     

Second‐order consensus for nonlinear leader‐following multi‐agent systems via dynamic output feedback control

The second‐order consensus problem of nonlinear leader‐following multi‐agent systems is investigated in this paper. To solve the case that the velocities of all agents cannot be measured and the nonlinearity is unknown, an observer‐based dynamic output feedback controller is proposed based on a non‐separation principle method. Using the feedback domination technique, it is shown that the systems output can reach consensus by choosing appropriate gains. Two examples are given to verify the efficiency of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Feedback stabilization of multi‐DOF nonlinear stochastic Markovian jump systems

A feedback control strategy is designed to asymptotically stabilize a multi‐degree‐of‐freedom (DOF) nonlinear stochastic systems undergoing Markovian jumps. First, a class of hybrid nonlinear stochastic systems with Markovian jumps is reduced to a one‐dimensional averaged Itô stochastic differential equation for controlled total energy. Second, the optimal control law is deduced by applying the dynamical programming principle to the ergodic control problem of the averaged systems with an undetermined cost function. Third, the cost function is determined by the demand of stabilizing the averaged systems. A Lyapunov exponent is introduced to analyze approximately the asymptotic stability with probability one of the originally controlled systems. To illustrate the application of the present method, an example of stochastically excited two coupled nonlinear oscillators with Markovian jumps is worked out in detail.     

Normal forms and approximated feedback linearization in discrete time

The paper discusses approximated feedback linearization of nonlinear discrete-time dynamics which are controllable in first approximation and introduces two types of normal forms. The study is set in the context of differential/difference representations of discrete-time dynamics proposed in [Monaco, Normand-Cyrot, in: Normand-Cyrot (Ed.), Perspectives in Control, a Tribute to Ioan Doré Landau, Springer, Londres, 1998, pp. 191–205].     

Robust consensus tracking for a class of heterogeneous second‐order nonlinear multi‐agent systems

This paper deals with the robust consensus tracking problem for a class of heterogeneous second‐order nonlinear multi‐agent systems with bounded external disturbances. First, a distributed adaptive control law is proposed based on the relative position and velocity information. It is shown that for any connected undirected communication graph, the proposed control law solves the robust consensus tracking problem. Then, by introducing a novel distributed observer and employing backstepping design techniques, a distributed adaptive control law is constructed based only on the relative position information. Compared with the existing results, the proposed adaptive consensus protocols are in a distributed fashion, and the nonlinear functions are not required to satisfy any globally Lipschitz or Lipschitz‐like condition. Numerical examples are given to verify our proposed protocols. Copyright © 2014 John Wiley & Sons, Ltd.     

An improved non‐sequential multi‐input multi‐output quantitative feedback theory design methodology

This paper presents an improved non‐sequential multi‐input multi‐output (MIMO) Quantitative Feedback Theory (QFT) design methodology for uncertain systems. A non‐sequential MIMO QFT stability theorem is derived that serves as the basis for an improvement of the design methodology, whereby it can be successfully applied to non‐minimum phase systems, albeit with a degree of conservatism partially inherent in independent and decentralized design methodologies. The results reduce the conservatism in a non‐sequential MIMO QFT design and provide insight into the plant cases for which the methodology can be successfully applied. Copyright © 2006 John Wiley & Sons, Ltd.     

Two‐stage stability control for strict‐feedback systems with input delays and input nonlinear uncertainties

In this paper, a two‐stage control procedure is proposed for stabilization of a class of strict‐feedback systems with unknown constant time delays and nonlinear uncertainties in the input. A nominal controller is first designed to compensate input time delays without considering input nonlinear uncertainties. Extended from backstepping algorithm, input delay compensation is realized by means of predicted states that are computed through integration of cascaded system dynamics, making the nominal closed‐loop system asymptotically stable. Based on the nominal controller presented for the input delay system, a multi‐timescale system is subsequently developed to estimate the unknown input nonlinearity and make the estimate approach the nominal control input as fast as possible. It is proved that the proposed control scheme can make states of the strict‐feedback systems converge to zero and all the signals of the closed‐loop systems are guaranteed to be bounded in the presence of input time delays and nonlinear uncertainties. Simulation verification is carried out to illuminate the effectiveness of the proposed control approach.     

A dual‐observer design for global output feedback stabilization of nonlinear systems with low‐order and high‐order nonlinearities

This paper employs a dual‐observer design to solve the problem of global output feedback stabilization for a class of nonlinear systems whose nonlinearities are bounded by both low‐order and high‐order terms. We show that the dual‐observer comprised of two individual homogeneous observers, can be implemented together to estimate low‐order and high‐order states in parallel. The proposed dual observer, together with a state feedback controller, which has both low‐order and high‐order terms, will lead to a new result combining and generalizing two recent results (Li J, Qian C. Proceedings of the 2005 IEEE Conference on Decision and Control, 2005; 2652–2657) and (Qian C. Proceedings of the 2005 American Control Conference, June 2005; 4708–4715). Copyright © 2008 John Wiley & Sons, Ltd.     

Distributed containment control for nonlinear multiagent systems in pure‐feedback form

In this paper, the problem of distributed containment control for pure‐feedback nonlinear multiagent systems under a directed graph topology is investigated. The dynamics of each agent are molded by high‐order nonaffine pure‐feedback form. Neural networks are employed to identify unknown nonlinear functions, and dynamic surface control technique is used to avoid the problem of explosion of complexity inherent in backstepping design procedure. The Frobenius norm of the ideal neural network weighting matrices is estimated, which is helpful to reduce the number of the adaptive tuning law and alleviate the networked communication burden. The proposed distributed containment controllers guarantee that all signals in the closed‐loop systems are cooperatively semiglobally uniformly ultimately bounded, and the outputs of followers are driven into a convex hull spanned by the multiple dynamic leaders. Finally, the effectiveness of the developed method is demonstrated by simulation examples.