H2-optimal sampled-data control

The H₂-optimal control of continuous-time linear time-invariant systems by sampled-data controllers is discussed. Two different solutions, state space and operator theoretic, are given. In both cases, the H₂ sampled-data problem is shown to be equivalent to a certain discrete-time H₂ problem. Other topics discussed include input-output stability of sampled-data systems, performance recovery in digital implementation of analog controllers, and sampled-data control of systems with the possibility of multiple-time delays     

Adaptive control based on explicit model of robot manipulator

Adaptive and nonadaptive control algorithms, which make use of a fundamental mathematical property concerning positive definite matrices and Lyapunov stability theory, are proposed for the control of robot manipulators. Using the fact that the matrix dD(q)/dt-2C(q, dq/ dt) is skew symmetric, nonadaptive controllers which have a simplified structure with less computational burden are proposed. Using the dynamic equations for robot manipulators, parameter adaptation rules are developed for updating the controller's partially or totally unknown parameters, generalizing them to model reference adaptive controllers. To further take advantage of the simplified structure of the proposed adaptive controllers, a method for deriving the dynamic model of a robot manipulator which is linear in terms of its parameters is given. This dynamic model is also suitable for the pure identification of the parameters of links and payload of the manipulator     

H∞ control and filtering for sampled-datasystems

H_∞ control and filtering problems for sampled-data systems are studied. Necessary and sufficient conditions are obtained for the existence of controllers and filters that satisfy a specified H_∞ performance bound. When these conditions hold, explicit formulas for a controller and a filter satisfying the H_∞ performance bound are also given     

Cost translation and a lifting approach to the multirate LQGproblem

It is shown how to translate an instance of a multirate sampled-data LQG problem into an equivalent, modified, single-rate, shift-invariant problem via a lifting isomorphism approach. Using this approach, one can solve the multirate LQG problem without using periodic system theory or solving periodic Riccati equations and without suffering any increases in state dimension. This translation procedure shows the correct way to translate RMS noise specification to the lifted domain for a multirate Q-design computer-aided-design package     

Simultaneous controller design for linear time-invariant systems

The use of generalized sampled-data hold functions (GSHF) in the problem of simultaneous controller design for linear time-invariant plants is discussed. This problem can be stated as follows: given plants P₁, P₂, . . ., P_N , find a controller C which achieves not only simultaneous stability, but also simultaneous optimal performance in the N given systems. By this, it is meant that C must optimize an overall cost function reflecting the closed-loop performance of each plant when it is regulated by C. The problem is solved in three aspects: simultaneous stabilization, simultaneous optimal quadratic performance, and simultaneous pole assignment in combination with simultaneous intersampling performance     

A smoothly parameterized family of stabilizable, observable linearsystems containing realizations of all transfer functions of McMillandegree not exceeding n

It is shown that there is a continuously parameterized family F of n-dimensional single-input single-output (SISO) stabilizable detectable linear system Σ(p) which contains at least one realization of each reduced, strictly proper transfer function of McMillan degree not exceeding n. The parameterization map p→Σ(p) is a polynomial function in 2n indeterminates from an open convex polyhedron in R²ⁿ to the linear space of all SISO n-dimensional linear systems     

Rational approximation of L1 optimalcontrollers for SISO systems

The L₁ optimal control problem with rational controllers for continuous-time systems is considered in which it is shown that the optimal L₁ performance index with rational controllers is equal to that of irrational controllers. A sequence of rational controllers that approximates the optimal index is constructed. Convergence properties of such a sequence are studied. That the corresponding sequence of objective transfer functions is shown to converge in weak-* topology in BV(R₊) in the time domain and uniformly in a wider sense in the frequency domain     

Quantizer effects on steady-state error specifications of digitalfeedback control systems

Suppose that for a linear, time-invariant, single-input single-output (SISO) plant a digital dynamic controller has been designed so that the corresponding discrete-time linear feedback control system will satisfy certain specified steady-state error criteria (e.g., the output v˜(kT) will follow the input r (kT) within a certain given error bound). Corresponding to this idealized linear system, the digital implementation of the dynamic controller will result in a nonlinear feedback control system. To what extent the resulting nonlinear digital feedback control system satisfies the steady-state-error criteria of the original idealized linear prototype feedback control system is investigated. Digital controller implementations which use fixed-point arithmetic or floating-point arithmetic are considered. Designs which are well scaled are assumed, i.e., overflow nonlinearities in digital controllers are not addressed     

An improved covariance assignment theory for discrete systems

For discrete systems, the set of all state covariances X which can be assigned to the closed-loop system via a dynamic controller is characterized explicitly. For any assignable state covariance X , the set of all controllers that assign this X to the closed-loop system is parameterized with an arbitrary orthonormal matrix U of proper dimension     

Minimization of the L∞-induced norm forsampled-data systems

It is shown that given any degree of accuracy, there exists a standard discrete-time l¹ problem that can be determined a priori whose solution yields a controller that is almost optimal in terms of the hybrid L^∞-induced norm. This is accomplished by first converting the hybrid system into an equivalent infinite-dimensional discrete-time system using the lifting technique in continuous time, and then approximating the infinite-dimensional parts of the system which model the intersample dynamics. A thorough analysis of the approximation procedure is presented, and it is shown that it is convergent at the rate of 1/n . Explicit bounds that are independent of the controller are obtained to characterize the approximation. It is also shown that the geometry of the induced norm for the sampled-data problem is different from that of the standard l¹ norm, and hence there might not exist a linear isometry that maps the sampled-data problem exactly to a standard discrete-time problem     

Control of interconnected nonlinear dynamical systems: the platoonproblem

The problem to be solved involves a highway automation project. The overall system consists of N vehicles (the platoon). Each vehicle is driven by the same input u and the state of the kth vehicle affects the dynamics of the (k+1)th vehicle. Furthermore, the dynamics of each vehicle is affected by its (local) state-feedback controller. Under very general conditions, it is shown that for sufficiently slowly varying inputs, decentralized controllers can be designed so that the platoon maintains its cohesion     

Optimal and robust controllers for periodic and multirate systems

The problem of optimal rejection of bounded persistent disturbances is solved in the case of linear discrete-time periodic systems. The solution consists of solving an equivalent time-invariant standard l¹ optimization problem subject to an additional constraint. This constraint assures the causality of the resulting periodic controller. By the duality theory, the problem is shown to be equivalent to a linear programming problem, which is no harder than the standard l¹ problem. Also, it is shown that the method of solution presented applies exactly to the problem of disturbance rejection in the case of multirate sampled data systems. Finally, the results are applied to the problem of robust stabilization of periodic and multirate systems     

Robust stability and performance via fixed-order dynamiccompensation: the discrete-time case

A discrete-time feedback-control-design problem involving parametric uncertainty is considered. A quadratic bound suggested by recent work on discrete-time state-space H_∞ theory is utilized in conjunction with the guaranteed cost approach to guarantee robust stability with a robust performance bound. The principal result involves sufficient conditions for characterizing robust full- and reduced-order controllers with a worst case H ₁ performance bound     

Direct state-space solution to the discrete-timeH∞ one-block problem

A general state-space representation is used to allow a complete formulation of the H_∞ optimization problem without any invertibility condition on the system matrix, unlike existing solutions. A straightforward approach is used to solve the one-block H_∞ optimization problem. The parameterization of all solutions to the discrete-time H_∞ suboptimal one-block problem is first given in transfer function form in terms of a set of functions in H _∞ that satisfy a norm bound. The parameterization of all solutions is also given as a linear fractional representation     

Mixed H2/H∞ control:a convex optimization approach

The problem of finding an internally stabilizing controller that minimizes a mixed H₂/H_∞ performance measure subject to an inequality constraint on the H_∞ norm of another closed-loop transfer function is considered. This problem can be interpreted and motivated as a problem of optimal nominal performance subject to a robust stability constraint. Both the state-feedback and output-feedback problems are considered. It is shown that in the state-feedback case one can come arbitrarily close to the optimal (even over full information controllers) mixed H₂/H_∞ performance measure using constant gain state feedback. Moreover, the state-feedback problem can be converted into a convex optimization problem over a bounded subset of (n×n and n ×q, where n and q are, respectively, the state and input dimensions) real matrices. Using the central H_∞ estimator, it is shown that the output feedback problem can be reduced to a state-feedback problem. In this case, the dimension of the resulting controller does not exceed the dimension of the generalized plant     

Block multirate input-output model for sampled-data control systems

A model for multirate sampled-data systems is presented. A detailed analysis of nonconventional sampled-data control systems (SDCS) is performed. The block multirate input-output model illustrates the control possibilities of multirate SDCS. It is obtained from either a transfer function matrix or a state variable representation. The model provides a direct way to represent, design, and understand either periodic or predictive controllers. A controller design methodology suitable for multivariable, multirate, nonsynchronous SDCS is also presented. The main feature is the freedom to achieve important objectives such as structure assignment, decoupling, and desired transient behavior, as well as reference matching, optimal control, or disturbance rejection     

An approach for pole assignment in singular systems

Pole assignment in a singular system Edx/dt=Ax+Bu is discussed. It is shown that the problem of assigning the roots of det(sE-(A +BF)) by applying a proportional feedback u=Fx+r in a given singular system is equivalent to the problem of pole assignment of an appropriate regular system. An immediate application of this result is that procedures and computational algorithms that were originally developed for assigning eigenvalues in regular systems become useful tools for pole assignment in singular systems. The approach provides a useful tool for the combined problem of eliminating impulsive behavior and stabilizing a singular system     

Generalized measures of fault tolerance in n-cube networks

It is shown that for a given p (1<p⩽n ), the n-cube network can tolerate up to p2^(n-p)-1 processor failures and remains connected provided that at most p neighbors of any nonfaulty processor are allowed to fail. This generalizes the result for p=n-1, obtained by A.-M Esfahanian (1989). It is also shown that the n-cube network with n⩾5 remains connected provided that at most two neighbors of any processor are allowed to fail     

The application of scheduled H∞controllers to a VSTOL aircraft

The authors apply H_∞-designed controllers to a generic VSTOL (vertical and short takeoff and landing) aircraft model GVAM. The design study motivates the use of H _∞ techniques, and addresses some of the implementation issues which arise for multivariable and H_∞-designed controllers. An approach for gain scheduling H_∞ controllers on the basis of the normalized comprime factor robust stabilization problem formulation used for the H_∞ design is developed. It utilizes the observer structure unique to this particular robustness optimization. A weighting selection procedure, has been developed for the associated loop-shaping technique used to specify performance. Multivariable controllers pose additional problems in the event of actuator saturations, and a desaturation scheme which accounts for this is applied to the GVAM. A comprehensive control law was developed and evaluated using the Royal Aerospace Establishment piloted simulation facility     

L1 analysis and design of sampled-data systems

The focus of this work is L₁-optimal control of sampled-data systems. A converging approximation procedure is derived to compute the L_∞-induced norm of closed-loop finite-dimensional linear time-invariant (LTI) sampled-data systems. An approximation method is developed to synthesize L₁-optimal sampled-data regulators. Finally, an example is provided that illustrates the L₁ analysis and design techniques presented