Adaptive control of nonlinear systems with nonlinear parameterization

An adaptive feedback regulation scheme is proposed for a class of single input nonlinear systems, with nonlinear parameterizations. A proof of local regulation is given. The results are validated through a simulation study.     

SolvingN+m nonlinear equations with onlym nonlinear variables

We derive a method for solvingN+m nonlinear algebraic equations inN+m unknownsy≠R ^m andz≠R ^N of the formA(y)z+b(y)=0, where the(N+m) × N matrixA(y) and vectorb(y) are continuously differentiable functions ofy alone. By exploiting properties of an orthonormal basis for null(A ^T (y)) the problem is reduced to solvingm nonlinear equations iny only. These equations are solved by Newton's method inm variables. Details of computational implementation and results are provided.     

Output regulation of uncertain nonlinear systems with nonlinear exosystems

An adaptive control algorithm is proposed for output regulation of uncertain nonlinear systems in output feedback form under disturbances generated from nonlinear exosystems. A new nonlinear internal model is proposed to generate the desired input term for suppression of the disturbances. The proposed internal model design is based on boundedness of the disturbance, high gain design and saturation. It is capable to tackle disturbances in any specified initial conditions. Some uncertainties in the systems are allowed, provided that they do not affect the desired feedforward control term, and they are tackled by using nonlinear dominant functions and an adaptive control coefficient. The proposed control algorithm ensures the global convergence of the state variables to the invariant manifold, which implies that the measurement or the tracking error approaches to zero asymptotically.     

Backstepping control for output-constrained nonlinear systems based on nonlinear mapping

In this paper, nonlinear mapping (NM)-based backstepping control design is presented for a class of strict-feedback nonlinear systems with output constraint. By mapping output value set onto the set of all real numbers, the constrained system is transformed into a new strict-feedback unconstrained system to employ the traditional backstepping control while simultaneously preventing the constraint from being violated. It is proved that the original system has the similar convergence and bounded properties with the new one. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Furthermore, the comparison with barrier Lyapunov function-based algorithm reveals the advantages of NM algorithm. The closed-loop system is guaranteed to be stable in the sense that all signals involved remain bounded, and the tracking error converges to zero asymptotically. Simulation studies illustrate the performance of the proposed control.     

Truncation nonlinear filters for state estimation with nonlinear inequality constraints

The paper focuses on the state estimation problem of nonlinear non-Gaussian systems with state subject to a nonlinear inequality constraint. Taking into account the available additional information about the state given by the constraint increases the estimate quality compared to classical state estimation methods which cannot utilize the information. Considering the constraint in the form of an inequality involving a nonlinear function of the state makes the state estimation problem difficult and hence treated only marginally. In this paper, a generic local filter for the inequality constrained estimation problem is proposed. It covers the extended Kalman filter, unscented Kalman filter, and divided difference filter as special cases and enforces the constraint by truncating the conditional density of the state. The truncation is computationally cheap, yet it provides high estimate quality of the constrained estimate. The same idea is then utilized in a truncation Gaussian mixture filter which is also proposed in the paper to increase the estimate quality further by providing a global constrained estimate. Superior estimate quality and computational efficiency of the proposed filters are illustrated in two numerical examples.     

Adaptive output tracking of inherently nonlinear systems with nonlinear parameterization

We address the problem of output tracking for a class of nonlinearly parameterized systems with unstabilizable linearization. To achieve practical output tracking globally in the case when both the bound of reference signals and the bound of unknown time-varying parameters are not known a priori, we present a robust adaptive control method that is based on the idea of universal control combined with the new adaptive feedback design method developed recently for controlling uncertain systems with nonlinear parameterization. Continuous adaptive tracking controllers are explicitly constructed in this paper. The proposed adaptive tracking controllers use only the information of a prescribed reference signal but not its derivatives, nor its bound.     

Regularity for solutions of nonlinear evolution equations with nonlinear perturbations

The approximate controllability for the nonlinear control system with nonlinear monotone hemicontinuous and the nonlinear perturbations is studied. The existence, uniqueness, and a variation of solutions of the system are also given.     

Overdamped nonlinear systems

Overdamped solutions toddot{z} + KF(z, dot{z}) = 0, z(0) = z_{0}, dot{z}(0) = dot{z}_{0}, are defined to be those that are asymptotically stable to the origin and which are zero at most once for0 < t < x. The main result is a lower bound on the positive constantKto ensure that solutions to the equation are overdamped.     

On nonlinear observers

In this note we make some remarks about the general observer problem for nonlinear systems. We show how the existence of a partial observer without stability requirements is locally equivalent to the existence of a conditioned invariant distribution. We argue that by considering not only identity observers we can put the stability issue in a broader perspective.     

Parsing nonlinear languages

The diagrammatic approach to user interfaces for computer-aided software development toolkits, visual query systems, and visual programming environments, is based on the use of diagrams and charts traditionally drawn on paper. In particular, the VLG system (Visual Language Generator) has been proposed to generate icon-oriented visual languages customized for given applications. The syntactical model underlying the interpretation of a visual language in VLG has been designed to describe icon-oriented visual languages. In order to enable the VLG system to apply to any kind of graphical languages, like diagrammatic ones, it is necessary to find a more general syntactical model able to support both their generation and interpretation. This paper addresses the comprehension of the features that a grammatical formalism for nonlinear languages must have to match any requirement for an efficient parsing. To this aim, relation grammars support an easy implementation of a general parsing algorithm for multidimensional languages, parametric with respect to the rewriting rules of the grammar. We compare the expressive power of relation grammars to grammatical formalisms for graph grammars     

Well-posed problem of nonlinear singular distributed parameter systems and nonlinear GE-semigroup

According to the well-posed problem of nonlinear singular distributed parameter systems, first of all, the nonlinear GE-semigroup induced by a continuous （possibly nonlinear） operator is introduced in Banach space, which is a generalization of GE-semigroup （i.e., generalized operator semigroup）, and the properties of nonlinear GE-semigroup are discussed; and then the existence, uniqueness and constructive expression for the strong solution of nonlinear singular distributed parameter system are discussed by nonlinear GE-semigroup; at last, the exponential stability of nonlinear singular distributed parameter system is studied by using nonlinear GE-semigroup, functional analysis and operator theory in Banach space.     

New nonlinear residual feedback observer for fault diagnosis in nonlinear systems

The increased complexity of plants and the development of sophisticated control systems have necessitated the parallel development of efficient Fault Detection and Isolation (FDI) systems. This paper discusses a model based technique, viz., observers for detecting and isolating parametric and sensor faults. In this paper, a novel diagonal nonlinear residual feedback observer is proposed which is valid for a certain class of nonlinear systems where, subject to other conditions, the state depends nonlinearly on the fault. A number of typical chemical engineering systems can be represented by models of this form. The structure of the observer ensures that the residuals are diagonally affected by the faults. Conditions for exact decoupling of residuals are presented and convergence of the observer in the presence of step faults is proved using Lyapunov like analysis. Multiple observers and a decision logic module are used for FDI when there are un-monitored faults. Results are presented from numerical simulations of an illustrative example and a typical chemical engineering system: a counter-current heat exchanger.     

Inference of disjoint linear and nonlinear sub-domains of a nonlinear mapping

This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of general nonlinear mappings is established and necessary and sufficient conditions determining these sub-spaces are derived. The importance of these invariants in an identification context is that they provide a tractable framework for minimising the dimensionality of the nonlinear modelling task. Specifically, once the linear/nonlinear sub-spaces are known, by definition the explanatory variables may be transformed to form two disjoint sub-sets spanning, respectively, the linear and nonlinear sub-spaces. The nonlinear modelling task is confined to the latter sub-set, which will typically have a smaller number of elements than the original set of explanatory variables. Constructive algorithms are proposed for inferring the linear and nonlinear sub-spaces from noisy data.     

Composite nonlinear feedback control for strict-feedback nonlinear systems with input saturation

This paper focuses on composite nonlinear feedback (CNF) controller design for tracking control problem of strict-feedback nonlinear systems with input saturation to address the improvement of transient performance. First, without considering the input saturation, a stabilisation control law is designed by using standard backstepping technique for the nonlinear system, then a feedforward control law is added to the backstepping-based stabilisation control law to construct a tracking control law. The tracking control law is tuned to drive the output of the closed-loop system to track a command input with quick response. Then, an additional nonlinear feedback law is constructed and combined with the tracking control law to obtain a CNF control law. The role of this additional nonlinear feedback law is to smoothly change the damping ratio of the closed-loop system while the system output approaches the command input, and to reduce overshoot caused by the tracking control law. It is shown that the extra-adding nonlinear feedback part does not cause the loss of stability of the closed-loop system in its attractive basin.     

Vibrational control of a class of nonlinear systems by nonlinear multiplicative vibrations

Vibrational control is a nonclassical control principle which proposes a utilization of zero mean parametric excitation of a dynamical system for control purposes. This paper extends nonlinear vibrational control theory developed in [8], [9] to systems controlled by nonlinear multiplicative vibrations. Condition for partial vibrational stabilization with respect to a component of a steady-state vector, the choice of stabilizing vibrations, and the transient motions are discussed for a certain practically important class of nonlinear vibrationally controlled systems. The application of the results is demonstrated on the example of a catalytic reactor, using a combination of numerical and analytical techniques.     

不同维数非线性节点非线性耦合复杂动态网络渐近同步

针对具有不同维数非线性节点的非线性耦合复杂动态网络, 首先给出了它的模型和实现同步的假设; 然后基于不变流形给出了该类复杂网络同步的定义, 并设计了分散动态补偿控制器, 提出了同步方案; 最后运用Lyapunov 稳定性理论进行了理论证明, 并通过数值仿真验证了该同步方案的有效性.

     

Extended nonlinear observer normal forms for a class of nonlinear dynamical systems

Transforming a dynamical system by adding auxiliary dynamics is one of the most recent tools to design an observer. Dynamical systems that have the properties of admitting such transformation have been widely studied. Indeed, in the existing literature, several different types of geometrical and analytical characterizations of such dynamical systems have been established. However, one finds only a few examples on this topic. Therefore, the main focus of this paper is to characterize a class of single‐output dynamical systems that can be transformed by means of a change of coordinates into an extended nonlinear observer normal form. Furthermore, this class provides examples of systems that can be transformed adding to them more than one auxiliary dynamics. To our knowledge, examples on this last fact lack in the existing research literature on this topic. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive robust control of uncertain nonlinear systems with nonlinear delayed state perturbations

The problem of robust stabilization of uncertain nonlinear dynamical systems with multiple time delays is considered. In the paper, the upper bound of the nonlinearity and uncertainty, including delayed states, is assumed to be a linear function of some parameters which are still assumed to be unknown. Here, we do not require that the nonlinear terms including delayed states are linear norm-bounded in the states. An improved adaptation law with σ-modification is employed to estimate the unknown parameters, and a class of memoryless adaptive robust state feedback controllers is proposed. It is also shown that the proposed adaptive robust controllers can guarantee the uniform asymptotic stability of uncertain nonlinear time-delay systems. Finally, as a numerical example, an uncertain time-delay ecosystem with two competing species is given to demonstrate the validity of the results.     

Efficient multistep procedures for nonlinear parabolic problems with nonlinear Neumann boundary conditions

Efficient multistep procedures for time-stepping Galerkin methods for nonlinear parabolic partial differential equations with nonlinear Neumann boundary conditions are presented and analyzed. The procedures involve using a precoditioned iterative method for approximately solving the differet linear equations arising at each time step in a discrete time Galerkin method. Optimal order convergence rates are obtained for the iterative methods. Work estimates of almost optimal order are obtained. Sponsored by the United States Army under Contract Nos. DAAG29-75-C-0024 and DAAG29-78-G-0161. This material is based on work supported by National Science Foundation under Grant No. MCS78-09525.