This is to prove that the thesis titled, "Study of Software Interface for Adaptive Control System". This is the basic software interface of the personal computer in which two processes which is the fast system consisting of memory, computer, keyboard and the process which is the slow system are synchronized with the software interface. The results are stored in different routines which are designated as private and public depending on the data methods.
The integrated software developed here is intended to be a classroom model of a commercial system available in the industry. Adaptive control is a special type of nonlinear feedback control in which the process stages can be separated into two categories that can change at different rates. The slowly changing states are treated as a parameter with a fast time scale for conventional feedback and a slower time scale for updating the controller parameters.
One of the objectives of adaptive control is to compensate for parameter variations that may occur due to non-linear actuators, changes in the operating conditions of the process and non-stationary disturbances acting on the process. An adaptive controller is a controller that can change its behavior in response to changes in the dynamics of the process and the disturbances. Adaptive control can be considered a special type of nonlinear feedback control in which the stages of the process can be separated into two categories, which can change at different rates.
One of the objectives of adaptive control is to compensate for parameter variations, which may occur due to non-linear actuators, changes in the operating conditions of the process, and non-stationary disturbances acting on the process.
Controller
Plant Parameter
Theory of layered architecture
A layered architecture is designed as a hierarchy of client-server processes that minimizes interaction between layers. Each layer acts as a client to the module above it and serves as a server to the model below it in a layered architecture. Layered architecture has been used in database systems, operating systems, computer-to-computer communication systems, and layered control for robots. The supervisor layers provide the command language interpreter (CLI), which provides an interface between users and the inner layers of the operating system.
The kernel layer takes care of memory management, input/output, process and time management. This kind of layering is very restrictive to prevent users from tampering with kernel and other system functions. Other, less restrictive forms of stratification are possible and have been introduced. A recent and successful alternative to the VMS type of layered architecture has been developed by Brooks to organize control systems for intelligent mobile robots (Brooks, 1986).
BLOCK DIAGRAM OF LAYERED ARCHITECTURE
COMPUTE POINT LAYER
DATA MANAGEMENT LAYER TUNING LAYER
MATHEMATICAL MODEL OF ADAPTIVE CONTROL
From the error dynamics given in eqn above, we can observe that the tracking error will go to zero if bθ2=am-a and bθ1 = bm. Usually the Lyapunov function is quadratic in the tracking error and the controller parameter estimation error since it is expected that the adaptation mechanism will drive both the tracking error and the controller parameter estimation error to zero. This function is zero when e is zero and the controller parameters are equal to the correct values.
To ensure that the tracking error goes to zero, we calculate the second derivative of the Lyapunov function. Since all the parameters are bounded and y=e+ym is bounded, d²v/dt² is also bounded, which again implies that dV/dt is uniformly continuous.
Self tuning Control
Module 2
Chapter-3
- Numerical analysis of adaptive control algorithm
- Software modules developed with explanation
- Module 2:In this module the problem statement is same as in the previous module
- Concluding comment about the success of the project
- Probable industrial applications of the project
- Application in an autonomous underwater vehicle
- Application in batch chemical reactor
- Limitations of the existing technology
- Advantages of the adaptive control
The Model Reference Adaptive Controller (MRAC) for a first-order system is illustrated using the Lyapunov synthesis approach. From the simulation we see that the process installation follows the reference model and that the tracking error converges to zero. Although ROVs play an important role in the offshore industry, their operational effectiveness is limited by the tethered cable and the dependence and cost of some type of support platforms.
In a batch chemical reactor, the reactants are initially loaded into the reaction vessel of the batch reactor and are then stirred for a certain period of time to allow the reaction to take place. For a specific reaction, there is an optimum temperature profile according to which the temperature of the reactor mass must vary in order to obtain the best results. Impulse and step response models are known to be overparameterized. For example, the dynamics of the first-order process can be described by three numbers using a parametric response that typically requires from 30 to 120 coefficients to describe the same dynamics.
These difficulties can be overcome in the identification step by first identifying a low-order model and then computing the impulse coefficients, but the impulse response still requires more storage than necessary. A potentially more significant problem with the impulse and step response model is that they are restricted to a strictly steady process, while it is certainly possible to modify the algorithms to accommodate a pure integrator, these modifications can lead to other problems such as adding the derivative of a noisy output signal in the feedback bath. High-performance control systems can be implemented when the plant's dynamic characteristics are poorly known or when large and unpredictable variations occur.
An adaptive controller is proposed for the scalar device that does not require knowledge of the signs or limits of the high-frequency gain. Adaptive control compensates for parameter variations that may occur due to nonlinear actuators, changes in process operating conditions, and non-stationary disturbances acting on the process.
