This chapter explores the development of deadbeat control and one-step-ahead control Deadbeat control and one-step-ahead control, each have a long history, the two were developed in separate research streams, and it was many years before these streams merged It compares and contrast deadbeat and one-step-ahead control strategies, to contribute to the unification of the two areas, and to clear up some possible points of confusion The chapter discusses that system identification, deadbeat control, and one-step-ahead control are possible because discrete-time systems are described by difference equations, which define an algebraic relation between the system inputs and outputs Such procedures cannot be applied to continuous-time systems, whose inputs and outputs are related by differential equations As a result, for example, deadbeat response in a continuous-time system cannot be achieved via linear time invariant feedback No matter how rapid the step response of a continuous-time control system is made, the exponentially decaying error vanishes only as time goes to infinity

Techniques in Deadbeat and One-step-ahead Control

This paper shows that the sensitivity of state feedback control systems can be re­ duced by additional state derivative feedback, for a fixed closed loop eigenstructure. The price of this sensitivity reduction is in general noise response amplification. Two indices which quantify stability robustness and response sensitivity are given for time invariant continuous time and discrete time systems, together with an index of response to disturbances and noise. Closed form expressions for the gradients of these indices are given. A two step design procedure is proposed which consists of first selecting a closed loop eigenstructure, then minimizing one of the sensitivity in­ dices under a magnitude constraint on the noise response. Examples are given to il­ lustrate this original design procedure.

Sensitivity reduction by state derivative feedback.

A connection between state-space and doubly coprime matrix-fraction descriptions of multivariable systems

In Chapters Two to Five we devote our attentions primarily to issues regarding parameter-sensitivity analysis. In spite of different uncertainties which may exist in a dynamical system, we expect that our controller will ultimately maintain qualitatively and/or quantitatively the overall system operation as desired. Or it will maintain this operation within a prespecified class of such operations which this is really the key issue in any robustness methodology. Therefore we must incorporate in control synthesis algorithm any information regarding possible discrepancies in system “output”, in order to generate new controllers that can stand against the consequences of some possible uncertainties. This incorporation is by no means a simple task, and before we let our expectations exceed our means, we examine some of our earlier assumptions and review the class of problems which currently can be analyzed.

Sensitivity Reduction and Robustness

A suboptimal output feedback approach for control of the pressurized water reactor (PWR) in the H.B. Robinson nuclear power plant is presented. Optimal state-feedback linear-quadratic-regulator (LQR) theory with pole-placement capability is extended to obtain a suboptimal projective controller for cases in which the entire state vector is inaccessible for measurement and feedback purposes. The appealing feature of the approach is that it is possible to select the weighting matrices in the quadratic cost functional so that the resulting control law nearly minimizes the cost and at the same time can assign a subspectrum of the closed-loop system to preassigned desired locations. The design algorithm is computationally very attractive, since regardless of the dimension of the PWR model the approach mainly involves low-order matrix computations. >

Suboptimal projective control of a pressurized water reactor

A method is proposed for the design of constant-gain feedback-control laws for linear multivariable discrete-time systems which reduce trajectory sensitivity to small system parameter variations and ensure the closed-loop eigenvalues at the origin The given quadratic index of performance including a sensitivity term is minimized in an average sense An efficient computational procedure based on direct cost optimization using gradient type algorithm is also reported An example is worked out to illustrate the proposed technique

On the design of a sensitivity-reducing optimal dead-beat controller

Application of optimal control theory to a boiling water nuclear reactor is the theme of this paper. The nonlinear model of the direct cycle 159 MW (th) Big Rock Point boiling water reactor derived on the basis of physicaL laws and empirical relations is linearized around an operating point and the model is verified against experimental results. The optimal control problem of the linearized model is treated as a regulator problem wherein the given quadratic index of performance includling a sensitivity term is minimized in an average sense over a set of feedback gain matrices which ensure prescribed closed-loop eigenvalues. An efficient computational procedure based on direct cost optimization using a gradient type algorithm is also reported. With the new optimal control strategy proposed in this paper, the stability and sensitivity characteristics of the system response can easily be manipulated.

A New Oftimal Control Strategy for a Nuclear Boiling Water Reactor


 Introduction:
 Mobile Stroke Treatment Units (MSTU) can reduce time to pre-arrival intravenous thrombolysis (IVtPA) and reversal for intracerebral hemorrhage (ICH). We are reporting our experience as a comprehensive stroke center (CSC) receiving MSTU patients.
 
 
 Methods:
 We retrospectively reviewed consecutive patients transported by MSTU to our academic CSC from May 2019-May 2021 for suspected stroke. The Columbus MSTU is owned by a separate health system, but is a collaborative venture with 3 CSCs and Columbus Division of Fire, operating daily from 7am-7pm. Data was abstracted on demographics, clinical presentation, last known normal (LKN) time, initial National Institutes of Health Stroke Scale (NIHSS), neuroimaging, and IVtPA administration.
 
 
 Results:
 Among 144 patients transported to our CSC by MSTU, mean age was 66 years (range, 21-99) and 84 (88%) were female. Mean initial NIHSS was 8.6 (range, 0 to 32) and 84 (58.2%) had a final diagnosis of stroke. IVtPA was administered in 26 (18.1%) with a mean LKN to IVtPA time of 109 minutes (range, 41 to 243). Among 26 patients treated with IVtPA, 18 (69.2%) received IVtPA in MSTU and 8 (30.8%) received rescue IVtPA in CSC Emergency Room (ER). 14 patients underwent thrombectomy with median door-to-groin time of 63.5 minutes (range, 28 to 129). We identified 10 (6.9%) cases that received rescue thrombolysis or reversal for ICH after arrival to the CSC ER. Dispatch data was available in 7 of these patients. The median dispatch to on-scene time was 7 minutes (range, 5 to 17). Median dispatch to CSC ER arrival was 53 minutes (range, 40 to 88). Among patients who received rescue therapy in CSC ER, 8 received IVtPA and 2 received reversal for ICH (prothrombin complex concentrate for warfarin and cryoprecipitate/transhexamic acid for IVtPA). Among the 8 MSTU patients who received IVtPA in the CSC ER, reasons included clinical worsening en route (1), new collateral information obtained at the CSC ER (4), and other (3).
 
 
 Conclusion:
 In our series of suspected stroke patients evaluated by MSTU, 6.9% of the overall cases received rescue stroke treatment after arrival to the CSC ER. Among MSTU patients who received IVtPA, 30% had thrombolytic treatment after arrival to the CSC ER. Further studies are warranted to assess limitations of MSTU care.


M. Gopal

Papers

On the design of a sensitivity-reducing optimal dead-beat controller

A New Oftimal Control Strategy for a Nuclear Boiling Water Reactor

Abstract TP50: Rescue Thrombolysis Or Hemorrhage Reversal In The Emergency Room After Transport By Mobile Stroke Treatment Unit