Active vibration control of an elastically connected double-string continuous system

The paper deals with the optimal control of a distributed host structure consisting of two elastically connected complex continuous double-string system and subjected to certain excitation load. Investigation of the behavior of such system is of great theoretical and practical importance. A technique is proposed to actively damp out the undesired vibrations in the structures by a combination of applied actuators and displacement feedback gains. Two performance measures, involving energies at the terminal time as well as applied and feedback control efforts, are introduced. The optimality conditions of the applied actuators are derived by using the method of eigenfunction expansion and calculus of variations. The feedback parameters are numerically determined from the solution of a minimization problem. The proposed approach is illustrated by a numerical example involving a system which consists of two strings subjected to a continuous load.     

开关磁阻电动机的非线性模型预测控制

将非线性预测控制应用于ＳＲＭ传动系统,建立了非线性参数预测模型,并在此基础上优化、校正,设计了ＳＲＭ的非线性速度预测控制器。该控制器具有实时预测、实时优化、实时校正的特点,很好地补偿了ＳＲＭ的非线性特性。与传统ＰＩ控制器相比,非线性模型预测控制器能提供更好的动态、静态特性,转矩脉动大为减小。（仿真结果表明,该控制策略不但正确、有效,而且使ＳＲＭ传动系统性能得到改善。     

具有二次性能指标的最优输出反馈的一个必要条件

本文用矩阵的秩这个工具考察了有限维线性系统具有二次性能指标的最优输出反馈问题，得到了一个必要条件。特殊情形下，这一条件可以演化为最优输出反馈增益与观测矩阵的乘积即为状态反馈增益这个相当清晰的关系。     

Optimal actuator switching synthesis of observer-based event-triggered state feedback control for distributed parameter systems

The study aims to explore the optimal actuator switching scheme of observer-based event-triggered state feedback control for distributed parameter systems. The performance of distributed parameter systems is improved through the observer-based event-triggered control, in which the state feedback is updated only when a triggered event happens. In such an event-triggered mechanism, the event-based closed-loop system and minimum time interval between consecutive events are bounded. Based on finite horizon linear quadratic regulator (LQR) optimal control, the optimal switching algorithm is proposed based on the event-triggered mechanism during an unfixed time interval. Finally, the proposed scheme is verified through a simulation case.     

Robust suboptimal feedback control for a fed-batch nonlinear time-delayed switched system

The optimal control strategy constructed in the form of a state feedback is effective for small state perturbations caused by changes in modeling uncertainty. In this paper, we investigate a robust suboptimal feedback control (RSPFC) problem governed by a nonlinear time-delayed switched system with uncertain time delay arising in a 1,3-propanediol (1,3-PD) microbial fed-batch process. The feedback control strategy is designed based on the radial basis function to balance the two (possibly competing) objectives: (i) the system performance (concentration of 1,3-PD at the terminal time of the fermentation) is to be optimal; and (ii) the system sensitivity (the system performance with respect to the uncertainty of the time-delay) is to be minimized. The RSPFC problem is subject to the continuous state inequality constraints. An exact penalty method and a novel time scaling transformation approach are used to transform the RSPFC problem into the one subject only to box constraints. The resulting problem is solved by a hybrid optimization algorithm based on a filled function method and a gradient-based algorithm. Numerical results are given to verify the effectiveness of the developed hybrid optimization algorithm.     

基于最优搜索步长的封闭量子系统的控制

利用变分法导出量子力学系统中一类最优控制问题的方程组，并使用具有最优搜索步长的开关变尺度法对最优控制问题进行数值迭代求解，最后在自旋1/2粒子上进行了系统仿真实验，验证了本文方法的有效性，同时对性能指标中参数的不同选择对整个最优控制效果影响的一般规律进行了分析。     

Optimal switching with minimum dwell time constraint

The problem of optimal switching between different subsystems/configurations with minimum dwell time constraints is investigated in this study and a feedback solution, using the framework of approximate dynamic programming, is proposed. The method calls for a tuning stage in which parameters of a function approximator are tuned. Online control will then be conducted with a computational load as low as evaluating a few scalar-valued functions. Finite-horizon and infinite-horizon cost functions are investigated and convergence and stability are analyzed considering the presence of approximation errors. Moreover, the case of applying a full or partial constraint on the mode sequence, as well as having a mode-dependent minimum dwell time are investigated. Finally, performance of the scheme in handling different challenges is numerically evaluated through different examples.     

Optimal controller for uncertain stochastic polynomial systems

This paper presents the optimal quadratic-Gaussian controller for uncertain stochastic polynomial systems with linear control input and a quadratic criterion over linear observations. The optimal closed-form controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. As intermediate results, the paper gives closed-form solutions of the optimal regulator and controller problems for stochastic polynomial systems with linear control input and a quadratic criterion. Performance of the obtained optimal controller is verified in the illustrative example against the conventional quadratic-Gaussian controller that is optimal for stochastic polynomial systems with known parameters. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.     

Guaranteed-cost reliable control with regional pole placement of a power system

This paper deals with the simultaneous coordinated design of power system stabilizer (PSS) and the flexible ac transmission systems (FACTS) controller. The problem of guaranteed cost reliable control with regional pole constraint against actuator failures is investigated. The state feedback controllers are designed to guarantee the closed loop system satisfying the desired pole region, thus achieving satisfactory oscillation damping and settling time, and having the guaranteed cost performance simultaneously. The proposed controllers satisfy desired dynamic characteristics even in faults cases. The controller's parameters are obtained using the linear matrix inequalities (LMI) optimization. Simulation results validate the effectiveness of this approach.     

Optimal synchronization controller design for complex dynamical networks with unknown system dynamics

In this paper, the optimal synchronization controller design problem for complex dynamical networks with unknown system internal dynamics is studied. A necessary and sufficient condition on the existence of the optimal control minimizing a quadratic performance index is given. The optimal control law consists of a feedback control and a compensated feedforward control, and the feedback control gain can be obtained by solving the well-known Algebraic Riccati Equation (ARE). Especially, in the presence of unknown system dynamics, a novel adaptive iterative algorithm using the information of system states and inputs is proposed to solve the ARE to get the optimal feedback control gain. Finally, a simulation example shows the effectiveness of the theoretical results.     

Optimal and robust control for linear state-delay systems

This paper presents the optimal regulator for a linear system with state delay and a quadratic criterion. The optimal regulator equations are obtained using the maximum principle. Performance of the obtained optimal regulator is verified in the illustrative example against the best linear regulator available for linear systems without delays. Simulation graphs demonstrating better performance of the obtained optimal regulator are included. The paper then presents a robustification algorithm for the obtained optimal regulator based on integral sliding mode compensation of disturbances. The general principles of the integral sliding mode compensator design are modified to yield the basic control algorithm oriented to time-delay systems, which is then applied to robustify the optimal regulator. As a result, the sliding mode compensating control leading to suppression of the disturbances from the initial time moment is designed. The obtained robust control algorithm is verified by simulations in the illustrative example.     

Optimal control for linear systems with time delay in control input

This paper presents the optimal regulator for a linear system with time delay in control input and a quadratic cost function. The optimal regulator equations are obtained using the duality principle, which is applied to the optimal filter for linear systems with time delay in observations, and then proved using the maximum principle. Performance of the obtained optimal regulator is verified in the illustrative example against the best linear regulator available for linear systems without delays. Simulation graphs and comparison tables demonstrating better performance of the obtained optimal regulator are included.     

Optimal nonlinear damping control of second-order systems

Novel nonlinear damping control is proposed for the second-order systems. The proportional output feedback is combined with the damping term which is quadratic to the output derivative and inverse to the set-point distance. The global asymptotic stability, passivity property, and convergence time and accuracy are demonstrated. Also the control saturation case is explicitly analyzed. The suggested nonlinear damping is denoted as optimal since requiring no additional design parameters and ensuring a fast convergence, without transient overshoots for a non-saturated and one transient overshoot for a saturated control configuration.     

Optimal control of linear delay systems via hybrid of block-pulse and Legendre polynomials

A method for finding the optimal control of a linear time varying delay system with quadratic performance index is discussed. The properties of the hybrid functions which consists of block-pulse functions plus Legendre polynomials are presented. The operational matrices of integration, delay and product are utilized to reduce the solution of optimal control to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.     

Hopf bifurcation control for delayed complex networks

In this paper, we consider the problem of Hopf bifurcation control for a complex network model with time delays. We know that for the system without control, as the positive gain parameter of the system passes a critical point, Hopf bifurcation occurs. To control the Hopf bifurcation, a time-delayed feedback controller is proposed to delay the onset of an inherent bifurcation when such bifurcation is undesired. Furthermore, we can also change the stability and direction of bifurcating periodic solutions by choosing appropriate control parameters. Numerical simulation results confirm that the new feedback controller using time delay is efficient in controlling Hopf bifurcation.     

Optimal boundary control of heat conduction problems on an infinite time domain by control parameterization

The present paper deals with an optimal boundary control problem in which the process of systems under consideration is governed by a linear parabolic partial differential equation over an infinite time interval. The objective of the paper is to determine the optimal boundary control that minimize a given energy-based performance measure. The performance measure is specified as a quadratic functional of displacement and a suitable penalty term involving the boundary controls. In order to determine the optimal boundary controls, the problem with boundary controls are converted into a problem with distributed controls. The modal space technique is then used to reduce the system into the optimal control of time invariant lumped parameter system. The associated system of uncoupled first order initial value problems is solved in terms of controllers. Next step deals with the computation of the control and trajectory of the linear time-invariant lumped parameter. For this we approximate the controllers by a finite number of orthogonal exponential zero-interpolants over the interval [0,∞). The resultant performance index after using the optimality condition leads to a system of linear algebraic equations. The suggested technique is easy to implement on digital computer. We provide a numerical example to demonstrate the applicability and efficiency of the proposed approach.     

Optimal adaptive reset control with guaranteed transient and steady state tracking error bounds

In this paper, a solution for improvement of transient performance in adaptive control of nonlinear systems is proposed. An optimal adaptive controller based on a reset mechanism and a prescribed performance bound is devised. The suggested controller has the structure of adaptive backstepping controller in which the estimated parameters are reset to an optimal value. The designed controller ensures both the transient bound and the asymptotical convergence of the states. It is shown that the tracking error satisfies the prescribed performance bound all the time, besides the speed of the convergence rate is increased by resetting the estimated parameters. The results have been proved through both the analytical and simulation studies. The proposed method is applied to an Augmented Quarter Car Model as a case study. Simulation results verify the established theoretical consequences that the prescribed performance bound based optimal adaptive reset controller can enhance the transient performance of the adaptive controller.     

A comparative study of optimal linear controllers for vibration suppression

The performance enhancement of dynamic systems is accomplished by the application of active control components. Control strategies are derived to accomplish the task. Among the various control strategies, those that are designed to minimize a specified cost function while satisfying the necessary system constraints are referred to as optimal controllers. An important constraint is the amount of power and energy consumed by the control device. In this paper, the effect of optimal control strategies on the power and energy requirement of control devices is investigated.     

Optimal LQG controller for linear stochastic systems with unknown parameters

This paper presents the optimal LQG controller for linear systems with unknown parameters. The optimal controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. Performance of the obtained optimal controller is verified in the illustrative example against the conventional LQG controller that is optimal for linear systems with known parameters. Simulation graphs verifying overall performance and computational accuracy of the designed optimal controller are included.