A stabilization algorithm for a class of uncertain linear systems

This paper presents an algorithm for the stabilization of a class of uncertain linear systems. The uncertain systems under consideration are described by state equations which depend on time-varying unknown-but-bounded uncertain parameters. The construction of the stabilizing controller involves solving a certain algebraic Riccati equation. Furthermore, the solution to this Riccati equation defines a quadratic Lyapunov function which is used to establish the stability of the closed-loop system. This leads to a notion of ‘quadratic stabilizability’. It is shown that the stabilization procedure will succeed if and only if the given uncertain linear system is quadratically stabilizable.The paper also deals with a notion of ‘overbounding’ for uncertain linear systems. This procedure enables the stabilization algorithm to be applied to a larger class of uncertain linear systems. Also included in the paper are results which indicate the degree of conservativeness introduced by this overbounding process.     

A precompensator of minimal order for decoupling a linear multi-variable system†

A theorem is proved which gives the minimal order of a precompensator which together with state feedback decouples a given linear time-invariant multi-variable system provided the system is invertible. In addition a design procedure is described by which the parameters of the precompensator are determined by solving a set of linear equations.     

Design of performance robustness for uncertain linear systems withstate and control delays

The linear systems considered in this paper are subject to uncertain perturbations of norm-bounded time-varying parameters and multiple time delays in system state and control. The time delays are uncertain, independent of each other, and allowed to be time-varying. The integral quadratic cost criterion is employed to measure system performance. Using solutions of Lyapunov and Riccati equations, a linear state feedback control law is proposed to stabilize the perturbed system and to guarantee an upper bound of system performance, which is applicable to arbitrary time delays     

Robust stability and performance of systems with structured and bounded uncertainties: an extension of the guaranteed cost control approach

A method is presented for designing a full state feedback linear control law that will ensure the robust stability and performance of a given linear uncertain system. The systems under consideration are described by state equations that depend on uncertain parameters. These uncertain parameters may be time varying. Their values are constrained to lie within known compact bounding sets. The method is based on the guaranteed cost control concept of Chang and Peng (1972). The controller gains result from the solution of a Riccati equation in which the weighting matrices depend on the uncertainty bounds. Sufficient conditions for the existence of a solution arise from the standard LQG control theory.     

Robust global stabilization of a class of uncertain feedforward nonlinear systems

The problem of global asymptotically stabilizing a certain class of uncertain feedforward nonlinear systems is considered. The control law is obtained by nesting saturation functions whose amplitude can be rendered arbitrarily small. With respect to previous works on the subject the design procedure is able to deal with uncertain (possibly time-varying) parameters ranging within the prescribed compact sets which can affect also the linear approximation of the system. The small gain theorem for nonlinear systems which are input to state stable “with restrictions” is shown to be a key tool for designing a state feedback saturated control law.     

Pitch Angle Control of Unmanned Air Vehicle with Uncertain System Parameters

In this paper a new algorithm of trajectory tracking based on closest radius solution of the interval equations system is proposed. The design procedure is given and applied to the pitch angle control of unmanned testing rocket with uncertain parameters. The proposed algorithm gives a framework to design a control for a wide range of different linear time-invariant processes with uncertain parameters and can be implemented also in the case of non-convex problems. The algorithm gives the analytical way of finding the nearly optimal solution of model reference trajectory tracking in the case of general time-invariant systems with uncertain parameters and can be used when optimization method fails due to the complexity of the problem.     

鲁棒渐近跟踪控制器设计的新方法

对于线性不确定系统,本文基于Riccati方程的正定解提出一种设计鲁棒渐近跟踪控制器的新方法.所设计的控制器,对于所有允许的系统参数变化,均使系统输出渐近跟踪某一参考输入.这种方法的特点是设计简单、实现方便.     

一类不确定动态时滞系统的无记忆鲁棒镇定控制

针对状态和控制均存在滞后,同时具有未知且有界的一类时变不确定线性时滞系统,提出了一种无记忆鲁棒镇定控制器设计算法.给出了闭环系统二次稳定的充分条件,并利用一等价线性时不变系统的H∞标准问题综合方法来构造出所需的线性状态反馈控制律,即可通过求解一代数Riccati型方程来求得控制律静态增益阵,从而保证了解的存在性和可解性.     

基于观测器的时滞系统鲁棒控制器的设计

研究了一类不确定时滞系统基于观测器的鲁棒镇定问题,系统的不确定性时变未知且范数有界,目的是设计状态观测器和线性无记忆观测状态反馈控制器,使其能够镇定一类状态和控制输入不确定性时滞系统。基于Lyapunov稳定性理论,采用线形矩阵不等式这一有效工具,给出了系统基于观测状态反馈鲁棒镇定的充分条件,并且利用线形矩阵不等式的解构造了使得系统鲁棒稳定的基于观测状态反馈控制器,所得结果与时滞相关,从而相对减弱了控制器设计的保守性。数值算例表明了所提出的设计方法的有效性。     

Control of uncertain and parameter-variant piecewise linear systems

This paper introduces a method for controller design of uncertain and parameter-variant piecewise linear systems. The idea is to specify a desired performance, which is represented by a nominal system. Around this nominal system a compact set of systems is obtained which will be robustly stable against switching among members of this set: such a set of systems is then called the stable switched set. The paper shows that obtaining the stable switched set is a signomial program. It is shown that upper bounds on signomial programs can be easily obtained, which are used to compute the stable switched set. A sufficient condition is given for the existence of a common state feedback controller that stabilizes a number of uncertain and parameter-variant linear systems on a stable switched set. The paper proposes a synthesis procedure in terms of a constrained convex optimization problem that places the uncertain and parameter-variant systems optimally close to the desired nominal system, using one common state feedback controller. An extension is shown for the case that there exists no common state feedback controller. The synthesis framework is then applied to a simple example to demonstrate the procedure. It is shown that real systems, like active suspension of a car, transform natural into uncertain and parameter-variant piecewise linear systems.     

Robust energy-to-peak filter design for stochastic time-delay systems

This paper considers the robust energy-to-peak filtering problem for uncertain stochastic time-delay systems. The stochastic uncertainties appear in both the dynamic and the measurement equations and the state delay is assumed to be time-varying. Attention is focused on the design of full-order and reduced-order filters guaranteeing a prescribed energy-to-peak performance for the filtering error system. Sufficient conditions are formulated in terms of linear matrix inequalities (LMIs), and the corresponding filter design is cast into a convex optimization problem which can be efficiently handled by using standard numerical algorithms. In addition, the results obtained are further extended to more general cases where the system matrices also contain uncertain parameters. The most frequently used ways of dealing with parameter uncertainties, including polytopic and norm-bounded characterizations, have been taken into consideration, with convex optimization problems obtained for the design of desired robust energy-to-peak filters.     

Eigenvalue assignment via uncertain state feedback controllers

In this paper, we propose a method for eigenvalue assignment using linear control systems containing uncertain elements. Uncertain systems are systems described by state equations which depend on uncertain parameters. In this paper, uncertainty is modeled with interval numbers. The proposed method assigns prescribed eigenvalues to a state feedback control system. Also, we introduce two interval operations to be used in our method use them. Some numerical experiments are presented to illustrate the effectiveness of the proposed method.     

Quadratic stabilizability of linear systems with structuralindependent time-varying uncertainties

The author investigates the problem of designing a linear state feedback control to stabilize a class of single-input uncertain linear dynamical systems. The systems under consideration contain time-varying uncertain parameters whose values are unknown but bounded in given compact sets. The method used to establish asymptotical stability of the closed-loop system (obtained when the feedback control is applied) involves the use of a quadratic Lyapunov function. The author first shows that to ensure a stabilizable system some entries of the system matrices must be sign invariant. He then derives necessary and sufficient conditions under which a system can be quadratically stabilized by a linear control for all admissible variations of uncertainties. The conditions show that all uncertainties can only enter the system matrices in such a way as to form a particular geometrical pattern called an antisymmetric stepwise configuration. For the systems satisfying the stabilizability conditions, a computational control design procedure is also provided and illustrated via an example     

区间系数不确定性系统的鲁棒控制器设计

本文提出了一种方法用于设计区间系数不确定性系统的鲁棒镇定控制器，所考虑的区间系数可以是时变的，控制器的设计仅依赖于区间系数的上下界，而设计步骤具有迭代特征。虽然所提到的控制器是线性和确定性的，但能够承受所有容允不确定性。所提出的方法通过一个电力系统负荷频率控制例子加以说明。     

Guaranteed cost stabilization for a class of uncertain discrete-time systems

A technique to design stabilizing state feedback controllers is presented for a class of linear discrete-time systems subject to possibly time-varying uncertainties that affect the system and input matrices. The controller design procedure is based on the solution of one of three modified algebraic Riccati matrix equations. Stability considerations rely on the second method of Lyapunov. To evaluate the system's performance degradation due to uncertainly, an upper bound (guaranteed cost) is derived for the cost of the controlled uncertain system with respect to a designer-chosen quadratic cost function. An example adapted from the literature is used to illustrate the method.     

一类具有非线性饱和执行器的不确定时滞系统鲁棒控制

研究一类具有非线笥饱和执行器朱确定线性时滞系统的鲁棒性镇定问题。所考虑的不确定时滞系统具有时变未知且有界的不确定参数和状态时滞。提出了新的鲁棒可镇定判据和相应的鲁棒无记忆状态反馈控制器设计方法。数值仿真例子说明了所提出方法的有效性。     

On stabilization of uncertain linear systems with jump parameters

In this paper, we study the problem of robust stabilizability of the class of uncertain linear systems with Markovian jumping parameters. Under the assumption of complete access to the continuous state, the stochastic stabilizability of the nominal system and the boundedness of the system's uncertainties, sufficient conditions which guarantee the robust stability of the uncertain systems are presented, which are in terms of a set of coupled algebraic Riccati equations. A numerical example is given to illustrate the potential of the proposed technique.     

A high-gain scaling technique for adaptive output feedback control of feedforward systems

In this note, we propose an adaptive output feedback control design technique for feedforward systems based on our recent results on dynamic high-gain scaling techniques for controller design for strict-feedback systems. The system is allowed to contain uncertain functions of all the states and the input as long as the uncertainties satisfy certain bounds. Unknown parameters are allowed in the bounds assumed on the uncertain functions. If the uncertain functions involve the input, then the output-dependent functions in the bounds on the uncertain functions need to be polynomially bounded. It is also shown that if the uncertain functions can be bounded by a function independent of the input, then the polynomial boundedness requirement can be relaxed. The designed controllers have a very simple structure being essentially a linear feedback with state-dependent dynamic gains and do not involve any saturations or recursive computations. The observer utilized to estimate the unmeasured states is similar to a Luenberger observer with dynamic observer gains. The Lyapunov functions are quadratic in the state estimates, the observer errors, and the parameter estimation error. The stability analysis is based on our recent results on uniform solvability of coupled state-dependent Lyapunov equations. The controller design provides strong robustness properties both with respect to uncertain parameters in the system model and additive disturbances. This robustness is the key to the output feedback controller design. Global asymptotic results are obtained.     

Gain scheduled controllers for dynamic systems using sector nonlinearities

In this work we explore the use of gain scheduling for the control of nonlinear systems. The nonlinear system is represented locally by uncertain linear models using sector nonlinearities representation. The uncertain linear models are then used to design a family of robust controllers. We propose a gain scheduling procedure for the problem of guaranteed transition from an actual operating condition to a desired one by constructing a pre-specified path in the state space for the system operating points. As far as we know this problem has not been addressed before. The gain scheduling control procedure given is illustrated in the context of the regulator problem with state feedback.     

Optimal guaranteed cost filtering for uncertain discrete-time linear systems

This paper presents a result on the design of a steady-state robust state estimator for a class of uncertain discrete-time linear systems with normal bounded uncertainty. This result extends the steady state Kalman filter to the case in which the underlying system is uncertain. A procedure is given for the construction of a state estimator which minimizes a bound on the state error covariance. It is shown that this leads to a state estimator which is optimal with respect to a notion of quadratic guaranteed cost state estimation.