Research On Control Strategies Based On Advanced Identification And Their Application

In control system design and analysis, model, control and state estimation are the three main bodies.And in the classical control theoty, because the considered control objects are always single inputsingle output systems, then the transfer function is the most suitable model to describe the controlobject's law of motion. The main work of system identification is to develop some identificationalgorithms based on some point estimation theory such as least square algorithm, maximum likelihoodtechnique and curve fitting. The system identification theory is the main part in the whole controltheory, because it can provide the mdel for the control design. The most important is that the systemidentification theory can penetrate in the advanced control theory and directly design a controller basedon input-output measurement datas. Therefore, we consider three advanced control methods from thepoint of the system identification theory. For the precision servo control system and UAV's pathplanning, researches on system identification and advanced control theory are carried out in this paper.For the precision servo control system's typical product such an turnplate, the three kinds of transferfunctions exist in turnplate systems are identified and estimated using system identification methods.When considered the recursive identification of the turnplate veloocity loop's transfer function underopen loop condition, we introduce a realize form in the recursive identification methods based onsingular value decomposition. The proposed method can not only obtain good nunerical property butalso improve the precision in real time identify system parameters. When the observed input-outputdatas are all corrupted with the white noise, the nonlinear separable least square algorithm is adopted toobtain the consistent estimations about eh model parameters. When the output noise is modeled as thecoloured noise, we extend the biased compensated method and instrumental variable methos to get thebias compensaten insturmental variable method. When identified the turnplate's position closed loop,we combine the instrumental variable method in ARMA identification and subspace identification instate space model to propose a new closed loop subspace optimal instrumental variable method.For the problem of the controller designed about the unknown model in the precision servo controlsystem, we diccuss a model reference adaptive control-virtual reference feedback tuning controlVRFT only based on data deriven. This control design method can effectively solve how to design theparametric controller about the unknown object's model in closed loop system. It regulates th problemof designing controller into a procedure of parameters optimization. As the controllere's expression inthe nonlinear closed loop is a nonlinear function, by using the idea of the VRFT, we construct a linearaffine function of the output datas, based on the parameter estimation iterative method. Through mixmizing the approximation error, we can seek the adjunct weights in the linear affine function.When applied the VRFT into the turnplate position tracking loop, the dynamic property of the PIDcontroller which is given from the VRFT has been improved and the tracking loop has the ability oftracking different frequency signal. For the nonlinear friction moment, we can also model thenonlinear nonlinear friction moment as a linear affine function, so as to be benefit to control.For the problem of how to suppress the external disturbance, we study the model parametersrecursive identification for inteernal model control, When considering some uncertainty factors of theobject model in the closed loop. The optimal closed loop input signal for the internal model control isalso designed. Under the effect of the external disturbance, we introduce a internal model H infinitycontrol to suppress the disturbance. After analysing the turnplate's structure, the internal model Hinfinity control is applied to analyse the controller in the velocity loop. It shows that the method cannot only be used to design stable system and un stable system simulately but also attain the prescribedthe control performance index.For the target function in the receeding horizon control, the explict expression of the outputpredictions are necessary. Then we construct the future output predictions based on the pastandcurrent input-output datas. A novel subspace predictive control based on subspace identification isdiscussed for joint system identification and control design. This combination enables automaticallytuning the parameters in model predictive control and avoids many steps in the LQG-controller design.It is independent of any controller prior information. When considered the constrain conditions, anellipsoid optimization algorithm is proposed to generate a sequence of ellipsoids with decreasingvolume. An upper bound on the maximum number of possible iterates steps is derived. It is used inthe flutter active control. The receeding horizon control of the nonlinear system is also discussed toconsider its optimization solution. We analyse this optimization problem from two aspects: setconstraint and no set constraint. Furthermore, we derive the necessary and sufficient condition ofwhether it has global optimization solution using separable theorem from convex theory. For themathematic optimization problem in UAV's path planning, the optimal control input sequence is givenusing receeding horizon control and ellipsoid iterative optimization algorithm.Acomplishment of above researches will supply a novel method for solving variety advancedcontrol problems, and supply an effective technique combined with system identification andadvanced control methods for precision servo control system and UAV's path planning, which willimprove control performance.