多输入多输出单边逻辑函数补集算法的研究

介绍一种多输入多输出单边逻辑函数补集算法,该算法通过对多输入多输出逻辑函数的分离,形成多输入单输出的分支逻辑函数,对多输入单输出分支逻辑函数求出其特征矩阵和状态矢量,根据特征矩阵的特性进行最小列覆盖的选取形成多输入单输出分支逻辑函数补集覆盖的特征矩阵、状态矢量和补集矩阵,最后对多输入单输出分支逻辑函数的补集矩阵进行合并形成多输入多输出逻辑函数的补集,通过测试结果表明性能良好.     

超大变量多值单边逻辑函数优化算法的研究

单边多值逻辑函数是逻辑函数的一种特例,对于超大变量的逻辑函数优化,存储开销对输入变量呈2幂次方增长.针对多输入多输出单边逻辑函数的特性,通过引入特征矩阵和状态矢量的描述,求解多输出单边逻辑函数补集,以积项扩展为基础,完成多输出单边逻辑函数无冗余覆盖.通过编程实现了多输入多输出单边函数逻辑优化的算法,对影响单边函数逻辑优化效率的因素进行了分析,软件系统在奔腾1.8GHz,512MB RAM的计算机上通过了正确性验证与测试,测试结果表明性能良好,有效降低了系统的存储空间和时间开销.在相同输出变量数、积项数和无关项因子的情况下,随输入变量数的增长,优化效率随之下降;在相同输入变量数、输出变量数和积项数的情况下,随无关项因子值的增长,优化效率随之下降;在相同输入变量数、输出变量数、和无关项因子的情况下,随积项数的增长优化效率随之提高.     

用二值逻辑对多值逻辑进行优化

提出以二值多输出逻辑优化软件OPLG为基础，对多值逻辑函数进行逻辑优化的方法．通过对多值变量、多值函数的二进制矢量描述，将多值多维体转换为布尔表达式积项形式，从多值多维体的多值最小项出发，给出计算基本无关集的方法。对多值逻辑函数的优化通过调用二值逻辑优化软件OPLG(允许的最大输入、输出变量之和为300)来实现，二值逻辑优化的结果最终再转换为多值多维体的表示形式。     

积项集合的补集算法

在逻辑综合的领域内,经常使用求给定积项集合补集的过程。本文提出一个单边逻辑函数积项集合的求补算法,求补操作是通过选取函数矩阵的列覆盖进行的。与传统求补算法相比,该算法大大节省了计算机时间和内存空间。     

积项集合的补集算法

在逻辑综合的领域内，经常使用求给定积项集合补集的过程。本文提出一个单边逻辑函数积项集合的求补算法，求补操作是通过选取函数矩阵的列覆盖进行的。与传统求补算法相比，该算法大大节省了计算机时间和内存空间。     

大变量多输出逻辑函数实质项识别算法

在对Espresso算法进行分析改进的基础上，提出了一种基于全域识别的多输入多输出逻辑函数实质本源项、完全冗余项和相对冗余项生成算法，该算法通过对基于积项表示的多输入多输出逻辑函数的余因子计算来进行全域判断，根据全域判断结果来识别实质本源项、完全冗余项和相对冗余项，从而构成实质本源项集合、完全冗余项集合和相对冗余项集合。对基于二级SOP型的多输入多输出逻辑函数设计了多输入多输出逻辑函数优化识别软件系统，允许的最大输入变量数为128、最大输出变量数为256、最大输入输出变量总和为300、最大输入积项数为20 000。软件系统在Pentium 1.8GHz、512MB内存的计算机上通过了Benchmark例题的测试。     

大变量多输出逻辑函数实质项识别算法

在对Espresso算法进行分析改进的基础上,提出了一种基于全域识别的多输入多输出逻辑函数实质本源项、完全冗余项和相对冗余项生成算法,该算法通过对基于积项表示的多输入多输出逻辑函数的余因子计算来进行全域判断,根据全域判断结果来识别实质本源项、完全冗余项和相对冗余项,从而构成实质本源项集合、完全冗余项集合和相对冗余项集合.对基于二级SOP型的多输入多输出逻辑函数设计了多输入多输出逻辑函数优化识别软件系统,允许的最大输入变量数为128、最大输出变量数为256、最大输入输出变量总和为300、最大输入积项数为20 000.软件系统在Pentium 1.8GHz、512MB内存的计算机上通过了Benchmark例题的测试.     

非线性系统的多模型DMC解耦设计

针对工业生产过程大多为多输入多输出非线性系统,干扰因素多,耦合作用强,常规控制方法难以获得满意控制效果的特.提出一种基于动态矩阵控制(DMC)的多模型控制方法,采用误差指标切换函数作为切换准则,根据其最小值来选择与实际最接近模型,并将基于此模型的控制器切换为当前控制器.结合目标函数解耦方法,在模型中考虑其他通道输入对当...     

不平衡工况矩阵变换器前馈补偿闭环控制

研究优化供电系统质量,为保证电网电压非正常工况下矩阵变换器(MC)的安全稳定运行,为了补偿输入不平衡和抑制谐波,提出一种带前馈补偿的双空间矢量闭环控制策略.通过检测虚拟直流电压值的变化实时调节空间矢量调制系数实现前馈补偿;将实际输出电压和期望输出电压的偏差作为负反馈加到下一个采样周期的开关调整函数矩阵中,实现输出电压负反馈闭环控制.仿真结果表明:具有前馈补偿方案的闭环控制策略,可以有效抑制矩阵变换器在电网电压非正常工况下输出电压及输入、输出电流波形的畸变,谐波含量明显减少.从而验证了控制方案的正确性.     

基于精确线性化的MIMO双线性系统预测函数控制

针对典型多输入多输出双线性系统, 提出了基于非线性过程精确反馈解耦线性化的预测函数控制方法这是一种分层的控制策略, 首先设计一个静态的非线性状态反馈, 使得闭环系统是输入输出解耦和线性的;然后设计一组单输入单输出预测函数控制器, 下层为上层预测函数控制提供一组单输入单输出模型, 而上层预测函数控制以其固有的鲁棒性来补偿参数变化和解耦线性化的近似性, 并以纸机加压网前箱为例进行了仿真实验, 结果是令人满意的.     

Simultaneous stabilization via static output feedback and statefeedback

In this paper, the simultaneous stabilization problem is considered using the matrix inequality approach. Some necessary and sufficient conditions for simultaneous stabilizability of strictly proper multi-input/multi-output (MIMO) plants via static output feedback and state feedback are obtained in the form of coupled algebraic Riccati inequalities. It is shown that any such stabilizing feedback gain is the solution of some coupled linear quadratic control problems where every cost functional has a suitable cross term. A heuristic iterative algorithm based on the linear matrix inequality technique is presented to solve the coupled matrix inequalities. The effectiveness of the approach is illustrated by numerical examples     

Direct adaptive fuzzy backstepping control for uncertain discrete-time nonlinear systems using noisy measurements

This paper presents a direct adaptive fuzzy backstepping control (AFBC) for multi-input multi-output uncertain discrete-time nonlinear systems. It is assumed that the systems are described by a discrete-time state equation with uncertainties to be viewed as the modelling errors and the unknown external disturbances, and the observation of the states is taken with independent measurement noises. The proposed direct AFBC is presented as follows. The proposed direct AFBC is assumed to be the fuzzy logic system by removing the explosion of complexity problem due to repeated computation of nonlinear functions at the first stage. Second, the number of the adjustable parameters is reduced by the fuzzy inference approach based on the extended single input rule modules. Third, the simplified weighted least squares estimator is constructed by reducing the computational burden of the estimation for the unmeasurable states and the adjustable parameters. The effectiveness of the proposed direct AFBC is illustrated through the simulation experiment of a simple numerical system.     

Creep in Thin Magnetic Films†

In this paper a method of testing and realization of two-realizable threshold functions have been suggested. It is shown that the two–realizable functions may be factored into three different forms, (i) sum of or (ii) product of or (iii) ‘ sum–of–product ’ of threshold functions. Since threshold functions are unate functions, a method of decomposition of Boolean functions into unate functions in the above three forms is suggested. The concept of minimal unate function and the cover table of the given Boolean function und its complement is utilized to obtain the above three factored forms.     

Adaptive sliding mode control for MIMO nonlinear systems based on fuzzy logic scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.     

Output feedback control for MIMO non-linear systems with unknown sign of the high frequency gain matrix

The paper presents a new output feedback adaptive control scheme for multi-input and multi-output (MIMO) non-linear systems whose non-linear terms depend only on the output variable based on the backstepping approach with vector form. The assumption on the prior knowledge of the high frequency gain matrix in existing results is reduced and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and makes the tracking error be arbitrary small. A simulation example is included to demonstrate the proposed algorithm.     

多输入-多输出系统的模型简化

用于大系统的模型最优简化的积分平方误差法,至今仅对输入向量的各分量相同时的少 数几种函数有效.本文指出,对各分量为不同类型函数的向量输入时,多输入-多输出系统的 模型同样可用积分平方误差法进行最优简化.     

Adaptive fuzzy control for multi-input multi-output nonlinear systems with unknown dead-zone inputs

This paper presents an adaptive fuzzy control scheme for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with the nonsymmetric control gain matrix and the unknown dead-zone inputs. In this scheme, fuzzy systems are used to approximate the unknown nonlinear functions and the estimated symmetric gain matrix is decomposed into a product of one diagonal matrix and two orthogonal matrices. Based on the decomposition results, a controller is developed, therefore, the possible controller singularity problem and the parameter initialization condition constraints problem are avoided. In addition, a dynamic robust controller is employed to compensate for the lumped errors. It is proved that all the signals in the proposed closed-loop system are bounded and that the tracking errors converge asymptotically to zero. A simulation example is used to demonstrate the effectiveness of the proposed scheme.     

Adaptive fuzzy control of MIMO nonlinear systems with fuzzy dead zones

In this paper, the problem of adaptive fuzzy tracking control is investigated for a class of multi-input multi-output nonlinear systems with fuzzy dead zones. The virtual control gain functions and uncertain functions considered in the studied system are all unknown. Fuzzy logic systems are employed to approximate the unknown functions. With the combination of adaptive backstepping design technique and dynamic surface control method, the problem caused by differentiating nonlinear functions repeatedly is avoided. Furthermore, only one adaptive parameter needs to be updated online for each subsystem, which reduces the computation burden considerably. The presented controller not only guarantees the desired control performance, but also guarantees the boundedness of all closed-loop signals. Simulation results are shown to demonstrate the effectiveness of the proposed algorithm.