Sufficient optimality conditions for discrete automaton-type systems

A discrete system that models the operation of a dynamic automaton with memory is considered. In distinction from the ordinary models of discrete systems, in which the states are changed (switched) at prescribed instants of time, automaton-type systems may change their states at arbitrary instants. Furthermore, the choice of the instants when the automaton “fires” is a control resource and it is subject to optimization. Sufficient optimality conditions for such systems under a limited or unlimited number of switchings are proved. Equations for the synthesis of the optimal closed-loop control are derived. Application of the optimality conditions is illustrated by examples.     

Suboptimal control of logical-dynamic systems under parametric uncertainty conditions

Sufficient optimality conditions of logical-dynamic systems are obtained, the logical portion of which models the operation of a memory-equipped automaton. Equations are derived for the definition of the optimal programmed control and full feedback control. Optimal processes with multiple switchings of the logical (automaton) portion at fixed instants of time are investigated. On the basis of sufficient conditions, algorithms are suggested for the development of the suboptimal control of logical-dynamic systems under parametric uncertainty conditions. The use of optimality and suboptimality conditions is illustrated by examples.     

Necessary and sufficient optimality conditions for discrete time-invariant automaton-type systems

The optimal control of deterministic discrete time-invariant automaton-type systems is considered. Changes in the system’s state are governed by a recurrence equation. The switching times and their order are not specified in advance. They are found by optimizing a functional that takes into account the cost of each switching. This problem is a generalization of the classical optimal control problem for discrete time-invariant systems. It is proved that, in the time-invariant case, switchings of the optimal trajectory (may be multiple instantaneous switchings) are possible only at the initial and (or) terminal points in time. This fact is used in the derivation of equations for finding the value (Hamilton–Jacobi–Bellman) function and its generators. The necessary and sufficient optimality conditions are proved. It is shown that the generators of the value function in linear–quadratic problems are quadratic, and the value function itself is piecewise quadratic. Algorithms for the synthesis of the optimal closed-loop control are developed. The application of the optimality conditions is demonstrated by examples.     

切换非线性系统的输出反馈周期事件触发控制

本文针对一类在任意切换信号作用下的切换非线性系统, 研究了其输出反馈周期事件触发控制问题. 所考 虑的非线性系统采用非严格反馈形式且含有未知时变控制系数. 在本文中, 仅利用采样时刻的系统输出. 为了估计 系统的不可量测的状态, 基于采样的系统输出构造了降维状态观测器. 为了减少通信资源的利用, 提出了一种新的 输出反馈周期事件触发策略, 该策略包含仅利用事件触发时刻的信息构造的输出反馈事件触发控制器以及仅在采 样时刻间歇性监测的离散事件触发机制. 通过选取可容许的采样周期及合适的公共Lyapunov函数, 证明了闭环系统 在任意切换下全局渐近稳定. 最后, 通过将本文中所给出的控制方案应用到数值算例中验证了其有效性.     

多模式网络化控制系统稳定性分析

网络传输引起的时滞在网络化控制系统中经常出现．针对存在多个运动模式的网络化控制系统,建立了时滞混杂自动机模型,分析了系统平衡点的稳定性,给出了平衡点保持稳定的充分条件在于构造的与离散状态相关的Lyapunov泛函在离散状态的切换时刻是非增的．当时滞混杂自动机中连续性子系统为线性时不变时滞系统时,可以利用线性矩阵不等式方法来寻找系统的公共Lyapunov泛函,并求解使系统平衡点保持稳定的时滞上界．最后,给出了一个例子说明了分析结果．     

Synthesis of optimal switched systems

A dynamical system simulating the operation of a switching device (switch) is considered. When functioning, the system changes its state a finite number of times. The change in the state (switching) is described by a recurrent activation when the switch is represented as a dynamic automaton with memory and instantaneous multiple switchings. The times at which switchings occur and their number are not prescribed. These values are determined from the optimization of a functional that calculates the number and cost of switchings. We have proved the sufficient conditions of the optimality of these systems and developed a method for synthesizing optimum switches. This method builds a family of auxiliary functions (conditional cost functions and conditional positional controls) that serve to form a cost function (a Hamilton—Jacobi—Bellman function) and an optimal scheme of the switch. The application of this method is illustrated by some examples.

     

Synthesis of logical-dynamical systems on the basis of sufficient optimality conditions

A dynamical system controlled by an automaton with memory is considered. A continuous part of the systems is described by differential equations, and a logical (automaton) part, by recurrence equations. Moments when the states of the automaton part are changed are a priori not known and determined in the course of optimization. Modes with multiple instantaneous switchings of the automaton part are assumed to be possible. Based on sufficient optimality conditions, a technique for synthesizing suboptimal positional control is developed. The use of this technique is illustrated by an example.     

Necessary optimality conditions for switched systems

A dynamic system that models the operation of a switching device (switch) is considered. During the operation, the system changes its state a finite number of times. The change of state (switching) is described by a recurrent inclusion, which corresponds to the representation of the switch by a dynamic finite state machine with memory; instantaneous multiple switchings are admitted. The instants of time at which switchings are made and the number of switchings are not given in advance. They are found by optimizing a functional in which the number of switchings and the cost of each of them are taken into account. Necessary optimality conditions for such systems are proved. Different versions of the optimality conditions for different types of constraints are given. In particular, under additional convexity conditions, conditions that are similar to the maximum principle for discrete systems are obtained. The application of the optimality conditions is illustrated by examples.     

Analytical design of optimal controllers in the class of logic-dynamic (hybrid) systems

The classical problem of analytical design of the optimal controllers which was stated and solved by A.M. Letov for continuous linear systems was considered for the class of logicdynamic (hybrid) systems. Equations to determine the optimal feedback control were derived on basis of the sufficient optimality conditions. In distinction to classical case, the optimal positional control is realized by the piecewise-linear controller with the piecewise-quadratic Bellman function. In contrast to the continuous, discrete or discrete-continuous systems, the optimal processes of logic-dynamic systems, can have multiple switchings in the logic block, thus hindering the optimal control design. Therefore it was suggested to consider a simplified problem where the logic-dynamic system is replaced by a discrete-continuous system admitting instantaneous multiple switchings of the discrete part. The resulting control for the logic-dynamic system becomes suboptimal. Application of the optimality and suboptimality conditions was demonstrated by way of several examples.     

Sufficient optimality conditions for continuous-discrete systems with multiple instantaneous switchings of the discrete part

A continuous-discrete system in which the motion of the continuous part is described by differential equations and the behavior of the discrete part is described by recurrences is considered; multiple instantaneous switchings are allowed. Such systems are called hybrid, and they occupy an intermediate position between continuous-discrete systems with single switchings and logical-dynamical systems. Sufficient optimality conditions under constraints on the number of switchings of the discrete part are obtained. Equations for the synthesis of the optimal closed-loop control are derived. Application of the optimality conditions is illustrated by examples.     

Robust state‐feedback control of stochastic state‐multiplicative discrete‐time linear switched systems with dwell time

Linear discrete‐time switched stochastic systems are considered, where the problems of mean square stability, stochastic l₂‐gain and state‐feedback control design are treated and solved. Solutions are obtained for both nominal and polytopic‐type uncertain systems. In all these problems, the switching obeys a dwell time constraint. In our solution, to each subsystem of the switched system, a Lyapunov function is assigned that is nonincreasing at the switching instants. The latter function is allowed to vary piecewise linearly, starting at the end of the previous switch instant, and it becomes time invariant after the dwell. In order to guarantee asymptotic stability, we require the Lyapunov function to be negative between consecutive switchings. We thus obtain Linear Matrix Inequalities conditions. Based on the solution of the stochastic l₂‐gain problem, we derive a solution to the state‐feedback control design, where we treat a variety of special cases. Being affine in the system matrices, all the aforementioned solutions are extended to the uncertain polytopic case. The proposed theory is demonstrated by a practical example taken from the field of flight control. Copyright © 2015 John Wiley & Sons, Ltd.     

Some Problems of Analysis of Hybrid Automata

A class of 1-dimensional hybrid automata is defined in which the dynamics at each discrete state for different sets of initial values of a continuous state can be represented by different differential equations, and a finite duration of this dynamics, which can be different for different sets of initial values of such a continuous state, is specified. Algorithms are proposed to solve problems of eliminating contradictions in the objects that define a hybrid automaton, matching these objects with one another, finding the minimum number of switchings, and estimating the minimum time required to reach discrete states from a set of initial discrete states.     

Robust H ∞ control of stochastic linear switched systems with dwell time

The theory of H _∞ control of switched systems is extended to stochastic systems with state‐multiplicative noise. Sufficient conditions are obtained for the mean square stability of these systems where dwell time constraint is imposed on the switching. Both nominal and uncertain polytopic systems are considered. A Lyapunov function, in a quadratic form, is assigned to each subsystem that is nonincreasing at the switching instants. During the dwell time, this function varies piecewise linearly in time following the last switch, and it becomes time invariant afterwards. Asymptotic stochastic stability of the set of subsystems is thus ensured by requiring the expected value of the infinitesimal generator of this function to be negative between switchings, resulting in conditions for stability in the form of LMIs. These conditions are extended to the case where the subsystems encounter polytopic‐type parameter uncertainties. The method proposed is applied to the problem of finding an upper bound on the stochastic L₂‐gain of the system. A solution to the robust state‐feedback control problem is then derived, which is based on a modification of the L₂‐gain bound result. Two examples are given that demonstrate the applicability of the proposed theory. Copyright © 2013 John Wiley & Sons, Ltd.     

Modified bang‐bang controller for maximal and minimal time optimal control problems

Recently, there have been a series of results regarding two time optimal control problems for a class of linear and nonlinear systems ‐ one is to keep the system states within certain bound for the longest time during feedback disruption and the other is to derive the system states to near the origin as fast as possible after feedback recovery, both under bounded control inputs. These are called maximal and minimal time optimal control problems, respectively. In the existing results, a bang‐bang controller has been commonly suggested as the actual implementation of the optimal controller. In this paper, we suggest a modified version of the bang‐bang controller which can also serve as an approximate optimal controller. Our proposed controller provides the (near) optimal performance with (i) possible reduction of a number of switchings; (ii) possible reduction of control input magnitude.     

Optimally switched linear systems

In this paper we address the problem of optimal switching for switched linear systems. The uniqueness of our approach lies in describing the switching action by multiple control inputs. This allows us to embed the switched system in a larger family of systems and apply Pontryagin’s Minimum Principle for solving the optimal control problem. This approach imposes no restriction on the switching sequence or the number of switchings. This is in contrast to search based algorithms where a fixed number of switchings is set a priori. In our approach, the optimal solution can be determined by solving the ensuing two-point boundary value problem. Results of numerical simulations are provided to support the proposed method.     

A method to design multirate controllers for plants sampled at alow rate

Classical discrete control systems allow control of the output of a plant at sampling instants. If control of the output between sampling instants is required, a multirate controller can be used. An analytical procedure is developed that allows feedforward control of the output at multirate instants and feedback control at sampling instants. The method proposed is a practical approach to the model-matching problem and takes into account the intersampling dynamics of the system     

Suboptimal control of bunches of trajectories of discrete deterministic automaton time-invariant systems

The optimal control problem for discrete deterministic time-invariant automaton systems under parametric uncertainty is considered. The changes in the state (switching) of the system are described by a recurrence equation. The switching times and their number are not specified in advance—they are found by optimization. The initial state of the system is not known exactly. For this reason, the problems of finding the optimal on the average and the optimal guaranteeing (minimax) controls of bunches of trajectories are formulated. It is proposed to solve these problems using the separation principle, which assumes that the bunch is controlled using the control that is optimal for a specially chosen individual trajectory in the bunch. Generally, this control is suboptimal. Algorithms for the synthesis of suboptimal control of bunches are developed. It is proved that, in the linear-quadratic time-invariant problems, the suboptimal bunch control is optimal on the average or is the optimal minimax control, depending on the problem being solved.     

On the Hybrid Optimal Control Problem: Theory and Algorithms

A class of hybrid optimal control problems (HOCP) for systems with controlled and autonomous location transitions is formulated and a set of necessary conditions for hybrid system trajectory optimality is presented which together constitute generalizations of the standard Maximum Principle; these are given for the cases of open bounded control value sets and compact control value sets. The derivations in the paper employ: (i) classical variational and needle variation techniques; and (ii) a local controllability condition which is used to establish the adjoint and Hamiltonian jump conditions in the autonomous switching case. Employing the hybrid minimum principle (HMP) necessary conditions, a class of general HMP based algorithms for hybrid systems optimization are presented and analyzed for the autonomous switchings case and the controlled switchings case. Using results from the theory of penalty function methods and Ekeland's variational principle the convergence of these algorithms is established under reasonable assumptions. The efficacy of the proposed algorithms is illustrated via computational examples.     

A control synthesis approach for time discrete event systems

In this paper, we introduce a control synthesis method for discrete event systems whose behavior is dependent on explicit values of time. Our goal is to control the occurrence dates of the controllable events so that the functioning of the system respects given specifications. The system to be controlled is modeled by a time Petri net. In a previous work we proposed a systematic method to build the timed automaton which models the exact behavior of a time Petri net. Furthermore, the forbidden behaviors of the system are modeled by forbidden timed automaton locations. This paper focuses on the control synthesis method, which consists in computing new firing conditions for the timed automaton transitions so that the forbidden locations are no longer reachable.     

Optimum experimental designs for dynamic systems in the presence of correlated errors

The problem of determining an optimal measurement time schedule for identification of unknown parameters in multiresponse systems when correlations between observations occur is considered. The measurement process is performed by collecting data at discrete time instants from several outputs. An observation plan is proposed based on a scalar measure of the Fisher information matrix as the design criterion quantifying the accuracy of parameter estimators. A numerical procedure is proposed to determine approximations of optimum designs in the case of correlated measurement errors. The approach is illustrated with an example of the multi-output system of equations describing a chemical kinetic reaction.