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Current generation of industrial MPC technology has two main disadvantages: 1) it is very costly to implement and to maintain an MPC system; 2) the performance in disturbance reduction is low. To solve these two problems, an adaptive MPC technology is introduced. It consists of three modules, a Control Module, an Identification Module and a Monitor Module. It can perform various steps of an MPC project...
Inverter control is to enable the inverter output sinusoidal voltage stability, dynamic response, robustness. Uses the current SPWM to control the inverter and design the closed-loop transfer function of system based on ITAE optimal model, get the controller parameters. To control the inverter with the optimized parameters, simulation results show the current inverter SPWM control system can adapt...
Has introduced a new model free adaptive control method, focusing on that the controlled objects of thermal power unit multi variable, strongly coupling, model parameters fiercely changes as the change of load, and presenting the transmission function model, structure graph and model free adaptive training method. It also does simulation study on a 300MW DC boiler of reheat steam turbine set, the...
Adaptive Inverse Control (AIC) based on Recursive Least Square (RLS) is applied in Control Loading System (CLS) of Flight Simulator (FS) .The algorithm was used to improve position tracking accuracy as an inner loop of CLS. This paper presents the implementation of a rapid prototyping control system based on RAT-LAB simulation environment, which involves the design of AIC and RLS algorithms using...
In order to solve the uncertainty problem of parameter variations and load disturbance which effect on the system performance, a nonlinear decoupling control based on disturbance suppression is presented for the induction motors drive system. The method combine adaptive control with nonlinear decoupling control, and the parameter variations and load disturbance are disturbance input. The state feedback...
Coordinated Control System(CCS) in thermal power plant is a system with big inertia, large time delay and slow parameter variance as well as the property of fast parameter variance while the unit load changes. Conventional PID controller and Direct Energy Balance(DEB) Strategy which is tuned at typical operating point can hardly work well at different unit load. By using the resource of Automatic...
The paper presents model predictive control solutions for a servosystem consisting of an electromagnetic actuator. Two solutions are proposed in this paper on the basis of one-step-ahead and multi-step-ahead quadratic objective functions. The simulation results support the development of solutions and offer conclusions concerning the advantages of the solutions.
Conventional PI regular is a simple control method that is widely applied in permanent magnet synchronous motor (PMSM) control systems. However, in most cases, it cannot meet the requirements of high performance control. In order to improve system robustness and response, this paper adopts sliding mode variable structure control strategy in the design of a double-loop controller (speed loop and current...
In this paper, the method of adaptive control with fractional order reference model was proposed. By introducing the fractional order calculus theory into control fields, it became much easier to promote the performance than integer order control system. Combining fractional order control theory and the traditional model reference adaptive theory, a new controller design was provided which added a...
An adaptive inverse control method based on support vector machine is studied in this paper. The initial inverse model of process is built based on least squares support vector machine, and the number of support vector is reduced by doing pruning algorithm. In this adaptive inverse control mechanism, the inverse model is updated through recursive least squares algorithm, and controller is adjusted...
It is very important for us to design an adaptive controller which could deal with larger parametric uncertainties for the post-boost vehicle. Here we design a multiple models adaptive controller according to the trait of the dynamic and kinematic models and the trait that the post-boost vehicle releases loads. By using the controller, the closed system is not only asymptotically stable, but also...
This work applies LMI control to a nonlinear switched mode power converter. The linearized model of the converter presents a non-minimum phase response. Nonlinearities and uncertainty are taken into account using a polytopic model. The LMI formulation permits to build a state-feedback controller to stabilize the plant with the maximum perturbation rejection and a certain pole placement constraint...
This paper is concerned with high performance control of three-phase UPS system. The basic requirements of a UPS control system are mentioned. Different control techniques are classified and their performance is briefly described. A hybrid learning-adaptive controller is proposed based on the performance of existing methods. For the learning part, a Repetitive Controller (RC) is used and a Model Reference...
To improve the regulatory performance of the adaptive inferential control system, a cautious on-line parameter estimation algorithm and an adaptive predictive model for unmeasured load disturbances are proposed. The cautious on-line parameter estimation algorithm is used to provide reliable model parameter values in the presence of frequent changes in unmeasured disturbances. Then, the future effect...
The Multi-Input Multi-Output One-Step-Ahead (MIMO O.S.A.) Adaptive Controller [1,2] is applied to a power plant boiler to control three outputs using three input variables. The power plant boiler is the same system to which a multivariable self-tuning controller was previously applied in [3]. This paper shows the improved performance of the MIMO O.S.A. adaptive controller over that of the multivariable...
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