Structured squaring down and zero assignment

The problem of zero assignment by squaring down is considered for a system of p-inputs, n-outputs and n-states (m > p), where not all outputs are free variables for design. We consider the case where a k-subset of outputs is preserved in the new output set, and the rest are recombined to produce a total new set of p-outputs. New invariants for the problem are introduced which include a new class of fixed zeros and the methodology of the global linearization, developed originally for the output feedback pole assignment problem, is applied to this restricted form of the squaring down problem. It is shown that the problem can be solved generically if (p − k)(m − p) > δ*, where k (k < p) is the number of fixed outputs and δ* is a system and compensation scheme invariant, which is defined as the restricted Forney degree

Approximate Zero Polynomials of Polynomial Matrices and Linear Systems

The aim of this paper is to extend recent results on the approximate GCD of polynomials [1] and approximate zeros to the case of a polynomial matrices within the framework of exterior algebra [2]. The results provide the means to introduce a new characterization of approximate decoupling zeros and measures for approximate controllability and observability for the case of linear systems

Solution of the determinantal assignment problem using the Grassmann matrices

The paper provides a direct solution to the determinantal assignment problem (DAP) which unifies all frequency assignment problems of the linear control theory. The current approach is based on the solvability of the exterior equation (Formula presented.) where (Formula presented.) is an n −dimensional vector space over (Formula presented.) which is an integral part of the solution of DAP. New criteria for existence of solution and their computation based on the properties of structured matrices are referred to as Grassmann matrices. The solvability of this exterior equation is referred to as decomposability of (Formula presented.), and it is in turn characterised by the set of quadratic Plücker relations (QPRs) describing the Grassmann variety of the corresponding projective space. Alternative new tests for decomposability of the multi-vector (Formula presented.) are given in terms of the rank properties of the Grassmann matrix, (Formula presented.) of the vector (Formula presented.), which is constructed by the coordinates of (Formula presented.). It is shown that the exterior equation is solvable ((Formula presented.) is decomposable), if and only if (Formula presented.) where (Formula presented.); the solution space for a decomposable (Formula presented.), is the space (Formula presented.). This provides an alternative linear algebra characterisation of the decomposability problem and of the Grassmann variety to that defined by the QPRs. Further properties of the Grassmann matrices are explored by defining the Hodge–Grassmann matrix as the dual of the Grassmann matrix. The connections of the Hodge–Grassmann matrix to the solution of exterior equations are examined, and an alternative new characterisation of decomposability is given in terms of the dimension of its image space. The framework based on the Grassmann matrices provides the means for the development of a new computational method for the solutions of the exact DAP (when such solutions exist), as well as computing approximate solutions, when exact solutions do not exist

Structure evolving systems and control in integrated design

Existing methods in Systems and Control deal predominantly with Fixed Systems, that have been designed in the past, and for which the control design has to be performed. The new paradigm of Structure Evolving Systems (SES), expresses a new form of system complexity where the components, interconnection topology, measurement-actuation schemes may not be fixed, the control scheme also may vary within the system-lifecycle and different views of the system of varying complexity may be required by the designer. Such systems emerge in many application domains and in the engineering context in problems such as integrated system design, integrated operations, re-engineering, lifecycle design issues, networks, etc. The paper focuses on the Integrated Engineering Design (IED), which is revealed as a typical structure evolution process that is strongly linked to Control Theory and Design type problems. It is shown, that the formation of the system, which is finally used for control design evolves during the earlier design stages and that process synthesis and overall instrumentation are critical stages of this evolutionary process that shapes the final system structure and thus the potential for control design. The paper aims at revealing the control theory context of the evolutionary mechanism in overall system design by defining a number of generic clusters of system structure evolution problems and by establishing links with existing areas of control theory. Different aspects of model evolution during the overall design are identified which include cases such as: (i) Time-dependent evolution of system models from “early” to “late” stages of design. (ii) Design stage-dependent evolution from conceptualisation to process synthesis and to overall instrumentation. (iii) Redesign of given systems and constrained system evolution. Within each cluster a number of well defined new Control Theory problems are introduced, which may be studied within the structural methodologies framework of Linear Systems. The problems posed have a general systems character, but the emphasis here is on Linear Systems; an overview of relevant results is given and links with existing research topics are established. The paper defines the Structural Control Theoretic context of an important family of complex systems emerging in engineering design and defines a new research agenda for structural methods of Control Theory

Data-Driven Retrospective Cost Adaptive Control

This dissertation develops data-driven retrospective cost adaptive control (DDRCAC) and applies it to flight control. DDRCAC combines retrospective cost adaptive control (RCAC), a direct adaptive control technique for sampled-data systems, with online system identification based on recursive least squares (RLS) with variable-rate forgetting (VRF). DDRCAC uses elements of the identified model to construct the target model, which defines the retrospective performance variable. Using RLS-VRF, optimization of the retrospective performance variable updates the controller coefficients. This dissertation investigates the ability of RLS-VRF to provide the modeling information needed to construct the target model, especially nonminimum-phase (NMP) zeros, which are needed to prevent NMP-zero cancellation. A decomposition of the retrospective performance variable is derived and used to assess target-model matching and closed-loop performance. These results are illustrated by single-input, single-output (SISO) and multiple-input, multiple-output (MIMO) examples with a priori unknown dynamics. Finally, DDRCAC is applied to several simulated flight control problems, including an aircraft that transitions from minimum-phase to NMP lateral dynamics, an aircraft with flexible modes, aeroelastic wing flutter, and a nonlinear planar missile.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169972/1/aseemisl_1.pd

Structured squaring down and zero assignment

The problem of zero assignment by squaring down is considered for a system of p-inputs, n-outputs and n-states (m &amp;gt; p), where not all outputs are free variables for design. We consider the case where a k-subset of outputs is preserved in the new output set, and the rest are recombined to produce a total new set of p-outputs. New invariants for the problem are introduced which include a new class of fixed zeros and the methodology of the global linearization, developed originally for the output feedback pole assignment problem, is applied to this restricted form of the squaring down problem. It is shown that the problem can be solved generically if (p - k)(m - p) Λ*, where k (k &amp;lt; p) is the number of fixed outputs and Λ* is a system and compensation scheme invariant, which is defined as the restricted Forney degree

Determination of Design of Optimal Actuator Location Based on Control Energy

The thesis deals with the selection of the sets of inputs and outputs using the energy properties of the controllability and observability of a system and aims to define input and output structures which require minimization of the energy for control and state reconstruction. Such a study explores the energy dimension of the properties of controllability and observability, develops computations for the controllability and observability Gramians for stable and unstable systems and examines measures of the degree of controllability and observability properties using SVD (Singular Value Decomposition) of Gramians to compute the maximal and minimal energy requirements. These characterize the relative degree of controllability and observability under conditions where the available energy is constrained. The notion of energy surfaces in the state space is introduced and this enables the characterization of restricted notions of controllability and observability when the available energy is bounded. The maximal and minimal energy requirements for different input vectors is demonstrated and this provides the basis for the development of strategies and methodologies for selection of systems of inputs and outputs to minimize the energy required for control, respectively state reconstruction. These results enable the development of input, output structure selection methodology using a novel optimization method. This thesis contributes in the further development of the area of systems, or global instrumentation, developed so far based on the assignment of structural characteristics by incorporating the role of energy requirements. The research provides energy based tools for the selection of input and outputs schemes with a main criterion the minimization of the energy required for control and observation and thus provide an alternative approach based on quantitative system properties in characterizing control and state observation as functions of given sets of inputs and output sets. The methodologies developed may be used as design tools where apart from energy requirements other design criteria may be also incorporated for the selection of inputs and outputs. The methodology that is used is based on linear systems theory and tools from numerical linear algebra. The solution to the problems considered here is an integral part of the effort to develop an integrated approach to control and global process instrumentation