ADAPTIVE CONTROL OF TECHNOLOGICAL PROCESSES WITH DELAY IN CONTROL

A method for the synthesis of adaptive systems by technological objects with control delay is proposed in the presence of a significant uncertainty in the setting of the delay value and time-variable coefficients of the linear inertia part model, which ensures the robustness of the system with respect to the delay. Adaptive identification-type systems and direct adaptive control systems without predictor are considered. The system with roughness in relation to the change in the delay value is used as the main contour

Augmentation of Fixed Gain Controlled Infinite Dimensional Systems With Direct Adaptive Control

Linear infinite dimensional systems are described by a closed, densely defined linear operator that generates a continuous semigroup of bounded operators on a general Hilbert space of states and are controlled via a finite number of actuators and sensors. Many distributed applications are included in this formulation, such as large flexible aerospace structures, adaptive optics, diffusion reactions, smart electric power grids, and quantum information systems. In this paper, we focus on infinite dimensional linear systems for which a fixed gain linear infinite or finite dimensional controller is already in place. We augment this controller with a direct adaptive controller that will maintain stability of the full closed loop system even when the fixed gain controller fails to do so. We prove that the transmission zeros of the combined system are the original open loop transmission zeros, and the point spectrum of the controller alone. Therefore, the combined plant plus controller is Almost Strictly Dissipative (ASD) if and only if the original open loop system is minimum phase, and the fixed gain controller alone is exponentially stable. This result is true whether the fixed gain controller is finite or infinite dimensional. In particular this guarantees that a controller for an infinite dimensional plant based on a reduced -order approximation can be stabilized by augmentation with direct adaptive control to mitigate risks. These results are illustrated by application to direct adaptive control of general linear diffusion systems on a Hilbert space that are described by self-adjoint operators with compact resolvent.

Hybrid fuzzy direct/indirect adaptive controller for uncertain nonlinear systems

This paper describes a new approach to adaptive control of uncertain nonlinear systems. A fuzzy logic controller is used to combine both direct and indirect methods. Based on the fuzzy neural networks, the plant unknown nonlinear functions are estimated, and then combined to form the indirect control law. In parallel, another fuzzy neural network approximates the direct adaptive control. According to the modelling error and its derivatives, the fuzzy logic controller modulates between direct and indirect adaptive controllers. The global stability of the overall system is shown by constructing a Lyapunov function. The simulation results show that within this scheme, the control objectives can be achieved with a fast convergence and optimal control for different dynamic regimes.

Robust Adaptive Depth Control of Hybrid Underwater Glider in Vertical Plane

Hybrid underwater glider (HUG) is an advanced autonomous underwater vehicle with propellers capable of sustainable operations for many months. Under the underwater disturbances and parameter uncertainties, it is difficult that the HUG coordinates with the desired depth in a robust manner. In this study, a robust adaptive control algorithm for the HUG is proposed. In the descend and ascend periods, the pitch control is designed using backstepping technique and direct adaptive control. When the vehicle approaches the target depth, the surge speed control using adaptive control combined with the pitch control is used to keep the vehicle at the desired depth with a constant cruising speed in the presence of the disturbances. The stability of the proposed controller is verified by using the Lyapunov theorem. Finally, the computer simulation using the numerical method is conducted to show the effectiveness of the proposed controller for a hybrid underwater glider system.

Model Direct Adaptive Control of Buck Converter by using MRAC

DC-DC converters are commonly implemented in effective packages. One of the regular varieties of DC-DC converters is dollar converter. The flexible controller techniques can decorate framework reaction not just like PID controller with steady parameter isn't hearty enough. The temporary reaction of PID controller exhibitions is multiplied depending on versatile issue. That lets in you to determine excellent placing for the control parameters underneath a few circumstance, a bendy element relying on MIT popular is carried out. Direct MRAC has a simple shape and wonderful execution in a few scenario. The proposed framework is regular and geared up to reach on the reaction of model reference superbly. Be that as it is able to, the react of the framework has straight away overshoot and pursue again the reaction of model reference. The ascent time, settling time, overshoot, and unfaltering country for step response are some destinations that decide if the adjustment additions art work as it should be. The confinement of bendy manage is the choice of the adjustment profits. The adjustment additions of the controller parameters are gotten with the aid of experimental increases.

Model Predictive Control and Controller Parameter Optimisation of Combustion Instabilities

In this paper the application of model predictive control (MPC) to a two-mode model of the dynamics of the combustion process is considered. It is shown that the MPC by itself does not stabilize the combustor and the control gains obtained by applying the MPC algorithms need to be optimized further to ensure that the phase difference between the two modes is also stable. The results of applying the algorithm are compared with the open loop model amplitude responses and to the closed loop responses obtained by the application of a direct adaptive control algorithm. It is shown that the MPC coupled with the cost parameter optimisation proposed in the paper, always guarantees the closed loop stability, a feature that may not always be possible with an adaptive implementations.