Guoming Zhu

Optimal Redesign of Linear Systems

This paper proposes a redesign procedure for linear systems. We suppose that an initial satisfactory controller which yields the desired performance is given. Then both the plant and the controller are redesigned to minimize the required active control effort. Either the closed-loop system matrix or the closed-loop covariance matrix of the initial design can be preserved under the redesign. Convex quadratic programming solves this problem. In addition, an iterative approach for integrated plant and controller design is proposed, which uses the above optimal plant/controller redesign in each iterative step. The algorithm has guaranteed convergence and provides a sequence of designs with monotonically decreasing active control effort. Examples are included to illustrate the procedure.

A Convergent Algorithm for the Output Covariance Constraint Control Problem

This paper considers the optimal control problem of minimizing control effort subject to multiple performance constraints on output covariance matrices

Mixed L2 and L∞ problems by weight selection in quadratic optimal control

Y_i

Equivalent fuel consumption optimal control of a series hybrid electric vehicle

of the form

Stochastic limit control and its application to spark limit control using ionization feedback

Y_i \leq \overline{Y}_i

Upper and lower covariance bounds for perturbed linear systems

, where

MBT Timing Detection and its Closed-Loop Control Using In-Cylinder Pressure Signal

\overline{Y}_i

Covariance control design for Hubble Space Telescope

is given. The contributions of this paper are a set of conditions that characterize global optimality, and an iterative algorithm for finding a solution to the optimality conditions. This iterative algorithm is completely described up to a user-specified parameter. We show that, under suitable assumptions on problem data, the iterative algorithm converges to a solution of the optimality conditions, provided that this parameter is properly chosen. Both discrete- and continuous-time problems are considered.

Modeling and Inverse Compensation of Temperature-Dependent Ionic Polymer–Metal Composite Sensor Dynamics

In an attempt to achieve more realistic control objectives, the weighting matrices in the standard LQ1 problem are usually chosen by the designer in an ad hoc manner. This paper shows several optimal control design problems that minimize a quadratic function of the control vector subject to multiple inequality constraints on the output L 2 norms, L ∞ norms, covariance matrix, and the maximum singular value of the output covariance matrix. The solutions of all four of these problems reduce to standard LQI control problems with different choices of weights. This paper shows how to construct these different weights. The practical significance of these results is that many robustness properties relate directly to these four entities. Hence the given control design algorithm delivers a specified degree of robustness to both parameter errors and disturbances. The results are presented in the deterministic terms of the linear quadratic impulse (LQI)for continuous and discrete systems problem rather than the stoc...

Model-Based Estimation of Flow Characteristics Using an Ionic Polymer–Metal Composite Beam

Abstract Improvements in hybrid electric vehicle fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a series hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine and the power follower control strategy minimizes the battery charging and discharging operations which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.