Reduced order controller design for discrete time systems

Robust discrete control system design techniques and model reduction are discussed. A new linear quadratic guussian/loop transfer recovery procedure for discrete time systems is presented. In this technique, a full-state feedback or an output injection feedback is designed which has the desired loop shape, and then recovered by a realizable linear quadratic gaussian controller. To do this, results that show the effects of the weighting matrices (noise intensities) on linear quadratic regulator (Kalman-Bucy filter) return difference and inverse-return difference arc derived and a procedure to recover the linear quadratic regulator loop transfer function is described. The complexity of the resulting controller is then reduced without causing closed-loop instability. Two methods for model reduction are considered. The first is the discrete balanced realization and the second is P frequency weighting technique where it is possible to vary the approximation accuracy with frequency. The controller design and reduction techniques are illustrated by designing a reduced order controller for an 8th order lumped inertia flexible mechanical system.     

Matrix criterion robust linear quadratic control problem

This paper studies a robust linear quadratic (LQ) control problem with multiple quadratic performance indices. Specifically, a linear model is assumed to be available for each of a prespecified set of operating points of a system. A vector-valued quadratic control performance index is given at each operating point. It is then desired to find the constant feedback gains of a linear controller to obtain satisfactory control performance over all the operating points. This is a realistic case involving the minimization of a vector criterion of vector criteria, i.e. a matrix-valued criterion. The matrix-valued criterion gives insight into standard robust LQ design, and leads to several related vector minimization problems, and to natural procedures for computing a satisfactory non-inferior solution to the matrix-valued minimization problem.     

Stabilization of Markov jump linear systems using quantized state feedback

This paper addresses the stabilization problem for single-input Markov jump linear systems via mode-dependent quantized state feedback. Given a measure of quantization coarseness, a mode-dependent logarithmic quantizer and a mode-dependent linear state feedback law can achieve optimal coarseness for mean square quadratic stabilization of a Markov jump linear system, similar to existing results for linear time-invariant systems. The sector bound approach is shown to be non-conservative in investigating the corresponding quantized state feedback problem, and then a method of optimal quantizer/controller design in terms of linear matrix inequalities is presented. Moreover, when the mode process is not observed by the controller and quantizer, a mode estimation algorithm obtained by maximizing a certain probability criterion is given. Finally, an application to networked control systems further demonstrates the usefulness of the results.     

线性离散时滞系统的输出反馈耗散控制

考虑线性离散时滞系统的二次型耗散控制问题,设计动态输出反馈使闭环系统渐近稳定且严格二次型耗散.先将系统严格二次型耗散性转化为线性矩阵不等式的可解性,得到了系统渐近稳定且严格二次型耗散的条件.然后讨论输出反馈耗散控制问题,给出了控制器的存在条件,总结出了控制器的综合方法、步骤.所得结果可为离散时滞系统的无源控制和H∞控制提供统一框架,也为离散时滞系统的分析和设计提供了一种更灵活、保守性更小的方法.     

Optimal control of Takagi–Sugeno fuzzy-model-based systems representing dynamic ship positioning systems

Orthogonal function approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA) are used to solve quadratic finite-horizon optimal controller design problems in both a fuzzy parallel distributed compensation (PDC) controller and a non-PDC controller (linear state feedback controller) for Takagi–Sugeno (TS) fuzzy-model-based control systems for dynamic ship positioning systems (TS-DSPS). Based on the OFA, an algorithm requiring only algebraic computation is used to solve dynamic equations for TS-fuzzy-model-based feedback and is then integrated with HTGA to design quadratic finite-horizon optimal controllers for TS-DSPS under the criterion of minimizing a quadratic finite-horizon integral performance index, which is also converted to algebraic form by the OFA. Integration of OFA and HTGA in the proposed approach enables use of simple algebraic computation and is well adapted to the computer implementation. Therefore, it facilitates design tasks of quadratic finite-horizon optimal controllers for the TS-DSPS. The applicability of the proposed approach is demonstrated in the example of a moored tanker designed using quadratic finite-horizon optimal controllers.     

Design of robust-optimal output feedback controllers for linear uncertain systems using LMI-based approach and genetic algorithm

This paper considers the robust-optimal design problems of output feedback controllers for linear systems with both time-varying elemental (structured) and norm-bounded (unstructured) parameter uncertainties. Two new sufficient conditions are proposed in terms of linear-matrix-inequalities (LMIs) for ensuring that the linear output feedback systems with both time-varying elemental and norm-bounded parameter uncertainties are asymptotically stable, where the mixed quadratically-coupled parameter uncertainties are directly considered in the problem formulation. A numerical example is given to show that the presented sufficient conditions are less conservative than existing ones reported recently. Then, by integrating the hybrid Taguchi-genetic algorithm (HTGA) and the proposed LMI-based sufficient conditions, a new integrative approach is presented to find the output feedback controllers of the linear systems with both time-varying elemental and norm-bounded parameter uncertainties such that the control objective of minimizing a quadratic integral performance criterion subject to the stability robustness constraint is achieved. A design example of the robust-optimal output feedback controller for the AFTI/F-16 aircraft control system with the time-varying elemental parameter uncertainties is given to demonstrate the applicability of the proposed new integrative approach.     

Systematic design of current control system for permanent magnet synchronous motors

This paper presents a systematic system design procedure of the current control system for permanent magnet synchronous machines (PMSM). Through the linear quadratic optimization design for the first order plus time delay plant controlled by a PI controller, a set of empirical formulas are found for the controller gains and the resulting closed-loop system characteristics. A systematic design procedure for the PMSM current control system is developed based on these empirical formulas, which results in a system design optimized for the chosen optimization criterion and yet with low hardware requirements including a low digital sampling rate and a low PWM update frequency.     

Output feedback controller design for uncertain piecewise linear systems

This paper proposes output feedback controller design methods for uncertain piecewise linear systems based on piecewise quadratic Lyapunov function. The α-stability of closed-loop systems is also considered. It is shown that the output feedback controller design procedure of uncertain piecewise linear systems with α-stability constraint can be cast as solving a set of bilinear matrix inequalities （BMIs）. The BMIs problem in this paper can be solved iteratively as a set of two convex optimization problems involving linear matrix inequalities （LMIs） which can be solved numerically efficiently. A numerical example shows the effectiveness of the proposed methods.     

Linear feedback control with prespecified performance measure

A novel procedure is presented to design a linear constant state feedback controller with a prespecified performance measure. The method is an iterative technique based on the sensitivity of a quadratic cost functional with respect to the feedback gains. At each iteration, a Riccati-type algebraic matrix equation is solved to compute the sensitivity expressions needed to update the feedback gains.     

Design of robust model predictive control with input constraints

This article addresses the problem of designing a robust output feedback model predictive control (MPC) with input constraints, which ensures a parameter-dependent quadratic stability and guaranteed cost for the case of linear polytopic systems. A new heuristic method is introduced to guarantee input constraints for the MPC. To reject disturbances and maintain the process at the optimal operating conditions or setpoints, the integrator is added to the controller design procedure. Finally, some numerical examples are given to illustrate the effectiveness of the proposed method.     

General quadratic performance analysis and synthesis of differential algebraic equation (DAE) systems

In this paper, control of linear differential-algebraic-equation systems, subject to general quadratic constraints, is considered. This setup, especially, includes the H_∞ control problem and the design for strict passivity. Based on linear matrix inequality (LMI) analysis conditions, LMI synthesis conditions for the existence of linear output feedback controllers are derived by means of a linearizing change of variables. This approach is constructive: a procedure for the determination of controller parameterizations is given on the basis of the solution of the LMI synthesis conditions. A discussion of the possible applications of the presented results concludes the paper.     

Double objective optimal multivariable ripple-free deadbeat control

This paper presents novel results on optimal multivariable deadbeat control. Given a discrete-time, stable, linear, time invariant plant model, we give a simple parameterization of all stabilizing ripple-free deadbeat controllers of a given order. The free parameter is then optimized in the sense that a quadratic index is kept minimal. The optimality criterion has the advantage of accounting for both tracking performance and magnitude of the control effort. The proposed design procedure is simple to use and allows the tuning of the controller with a scalar weighting factor. Simulation results are included to illustrate the effectiveness of the proposed design algorithm.     

Computer control of a double inverted pendulum

A double inverted pendulum is successfully stabilized at the upright position by using a computer control. The control system is designed based on the state space approach by using a computer aided design program named CADOS developed for this purpose. CADOS was used not only for the analysis and design, but also for the simulation to evaluate the designed system. The controller designed consists of the state variable feedback and the observer. The state variable feedback is determined based on either pol-locations or as the optimal control for the quadratic criterion function. As the observer, the minimal order state observer or a linear functional observer is employed, and it is theoretically proved that the linear functional observer for a multiple inverted pendulum can always be realized by the first order. The designed controller is implemented in the mini-computer used for CADOS and could work satisfactorily. The controller using a linear functional observer requires less computation time and controls the system in more stable way.     

On the design of stationary feedback regulators for linear discrete systems

A new approach to the problem of stationary feedback controller design for linear time-invariant systems in the discrete time domain is presented. A single-input single-output deterministic system is considered first and it is shown that the gain vector that defines a state feedback controller is conveniently computed if the design criterion corresponds to the specified values of n members of the output sequence, n being the order of the given system. Extension of the proposed method to the case of single-input single-output stochastic systems is studied next. Finally, the case of multi-input multi-output systems is dealt with by converting the given system into an equivalent single-input system. The results are illustrated through numerical examples.     

基于LMI的分布时滞系统输出动态反馈镇定

研究分布时滞系统的输出动态反馈镇定问题. 基于闭环系统的中立型变换及相应Lyapunov-Krasovskii泛函的构造与解析技巧, 建立了与时滞相关的控制器存在性判据. 在此基础上通过控制器参数化设计方法, 将控制器参数的求解归结为线性矩阵不等式解的形式. 仿真算例验证了方法的有效性     

利用最优输出反馈的鲁棒调节器设计方法

本文提出了在阶跃型及斜坡型参考输入及干扰下,鲁棒调节器的一种设计方法.这种方法 是将稳定补偿器的设计转化为输出反馈二次型调节器的设计.利用梯度矩阵的表达式,就可 以采用一般单参数寻优方法获得一个简单的调节器.对燃气轮机模型的仿真研究说明了这种 调节器的鲁棒性.最后对这一方法作了扼要讨论.     

具有时变不确定性的线性时滞系统的鲁棒H∞控制

研究具有一般形式的不确定线性时滞系统的鲁棒H∞状态反馈控制器设计问题.基 于二次H∞性能概念,首先证明了若存在鲁棒H∞动态状态反馈控制器,则必存在鲁棒H∞静 态状态反馈控制器,然后利用线性矩阵不等式给出了鲁棒H∞静态状态反馈控制器存在的充 分条件和构造方法,最后给出一个算例验证本文方法的有效性.     

一类不确定线性时滞系统的输出反馈鲁棒H∞ 控制

研究具有防射参数不确定性的线性时滞系统的鲁棒H∞输出反馈控制器设计问题,得到了一些二次矩阵不等式,证明了如果它们有解,则从它们的解可以构造全阶严格真动态输出反馈控制器,它能保证闭环系统二次稳定且具有H∞范数意义下的干扰抑制能力,进一步证明了在某些情况下,这些二次矩阵不等式可以化为线性矩阵不等式来求解。     

短时延广义网络控制系统的指数保性能控制

本文基于标称点方法,在短时变时延条件下,研究了广义网络控制系统的指数稳定保性能控制问题.基于李雅普诺夫稳定性判据和线性矩阵不等式技术,给出了使得系统能够指数稳定且满足二次型性能指标的状态反馈控制器存在的条件和设计方法.通过采用标称点方法,有效地解决了现有方法没有考虑网络诱导时延与系统保守性的关系且适用范围有限的问题,并通过算例验证了有效性.由于建模过程中充分考虑了系统的保守性,相比之下获得了更好的二次型性能指标值.     

Optimal LQ feedforward tracking with preview: Practical design for rigid body motion control

For reference-tracking motion control, preview-based linear quadratic (LQ) design methods provide an effective means to balance tracking performance with available actuation capacity. This paper considers a control structure for which the optimal feedforward controller is independent of the feedback controller. In this way, explicit implementation formulas for feedforward controllers are derived that can be applied to a range of rigid-body motion systems. Key aspects of the optimal LQ solutions are identified, particularly how the choice of design weightings affect steady-state error for polynomial tracking. A redesign procedure for finite preview-time is proposed that preserves exact polynomial tracking properties and control bandwidth of the optimal solutions. Comparative experimental results are presented for a motor-driven linear motion stage.