Observer Design And Optimized Control Of High Throughput Screening Robots Based On Dioid

With the development of high-speed computer technology and the development of highly automated equipment,especially for robots,a new type of discrete event system—high throughput screening system has emerged.The system combines combinatorial chemistry,genomics Research,bioinformatics and automation instruments,robots and other advanced technologies have been organically combined to create a new program for screening compounds that screened the bioactivity of compounds to hundreds of thousands of samples per day,often referred to as "high-throughput screening robots".At present,a lot of work has been done on control of deterministic high throughput screening systems,in which the dioid model can efficiently describe and control the system from the time domain and the event domain,which improves the analysis and control efficiency of the system.However,during the actual operation of the high throughput screening system,it may be affected by uncertain factors such as interference and systems fault,or because of the lack of corresponding sensors,or because it is impossible to directly measure,it may be necessary to estimate the observation of some system states.Then,it is possible to optimize the control of this uncertainty system.Therefore,in the dioid model,the observer is first added to the uncertain high throughput screening system,and the optimal observer matrix is obtained based on the residuation theory to estimate the state of the system.Then the state feedback control is combined with the pre-compensation compensator to optimize the uncertainty system.The pre-compensator is used to solve the expected performance index construction requirements in the feedback control,and the effect of the optimization control is improved.Finally,an example is given to verify the effectiveness of this control method.