Basic control design

In Chap. 18 we will define mathematically the sampling process, derive the z transforms of common functions (learn our German vocabulary) and develop transfer functions in the z domain. These fundamentals are then applied to basic controller design in Chap. 19 and to advanced controllers in Chap. 20. We will find that practically all the stability-analysis and controller-design techniques that we used in the Laplace and frequency domains can be directly applied in the z domain for sampled-data systems. 

The process flow diagram, or PP D. is a pictorial description of the process. It gives the basic processing scheme, the basic control concept, and the process information from which equipment can be specified and designed. It pror ides the basis for the der elopment of the P l diagram and also serves as a guide for the plant operator. The process flow diagram usiuilly includes... 

We now finally launch into the material on controllers. State space representation is more abstract and it helps to understand controllers in the classical sense first. We will come back to state space controller design later. Our introduction stays with the basics. Our primary focus is to learn how to design and tune a classical PID controller. Before that, we first need to know how to set up a problem and derive the closed-loop characteristic equation. 

This type of controller design has been around for many years. The pole-placcmcnt methods that are used in aerospace systems use the same basic idea the controller is designed so as to position the poles of the closedloop transfer function at the desired location in the s plane. This is exactly what we do when we specify the closedloop time constant in Eq. (11.63). 

The basic controller in the feedback loop is designed for load disturbances Ui) A precompensator is used on the setpoint signal. This element is designed so that the response to setpoint changes, with the compensator in service, is the desired one. The precompensator is defined as I>ss(z) ... 

Before focusing in the controller design, it is important to review some basic concepts of the geometric control theory. The control tools based in differential geometry are proposed for those nonlinear dynamical systems called affine systems. So, let s star by its definition. 

A fundamental element of fire prevention is the control of ignition sources. The process should be designed, installed, and operated to minimize or prevent the release or spill of flammable gases, liquids, or combustible dusts, as well as eliminate or control ignition sources. The basic controls for these unwanted ignition sources are ... 

For basic filter material development wall scale models especially the MicroFlowS approach can be applied. During early development of particulate emission control systems single channel models provide a fast and sufficient means for basic DPF design and sizing analysis. In addition, when applicable... 

In this chapter we outline the nine basic steps of a general heuristic plantwide control design procedure (Luyben et al., 1997). After some preliminary discussion of the fundamentals on which this procedure is based, we outline each step in general terms. We also summarize our justification for the sequence of steps. The method is illustrated in applications to four industrial process examples in Part 3. 

ODORS PROM MEAL DRYER AND OIL DEODORIZATION—Odor is a qualitative parameter from the standpoint of both measurement and control. Motivation for abatement usually arises out of complaints of citizens residing nearby a facility. Sources of odor can be meal driers and rehned oil deodorization. Acidulation has been an odor producer in some isolated instances however, is most often because of basic poor design and operation usually coincident with batch processing in open-topped kettles. 

The basic control scheme used for the perfect control analysis, a single inline feedback loop, gives 10 times the allowable concentration variation at the exit of the second tank for the predicted worst case. Including feedforward reagent addition would be insufficient by itself to give the tenfold improvement required, due to a 20% error in the estimated load (inferred from pH), so an additional in-line ratio feedback controller was added between the two tanks. As an additional actuator was therefore available at no extra cost, lead-lag feedforward from the load error at the first controller to the second controller actuator was added. To reduce feedforward dynamic mismatch, the lag was set to approximately the residence time of the first tank. The lead constant was added to the design parameters. 

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