Figure 2 - AN ASSESSMENT METHOD FOR THE CONTROL SYSTEMS QUALITY МЕТОД ОЦІНКИ ЯКОСТІ СИСТЕМ КЕРУВАННЯ

-Xcos-model In the upper part of the diagram, a model of a continuous-time PID controller is presented, in the lower part, a discrete one. Vectors of input and output values are transferred to the Scilab workspace. These data are processed according to formula (2) by the following Scilab-scenario: pid=abs(diff(Yd.values)); piX=abs(diff(X.values)); Sh = -sum(pid.*log2(pid))/sum(pid); Bo = -sum(pid.*log2(piX))/sum(pid); critd = 1-Sh/Bo; disp(critd) Discretization of the PID controller was performed by two methods: by Euler and by Tustin. For each of these options, the simulation was run and the amount of misinformation was calculated. The results in Table 1 show the better quality of the controller discretized by Tustin's method. Which corresponds to the theory. Table 1 -Research results Controller The amount of misinformation discretized by the Euler's method 0.0467428 discretized by Tustin's method 0.0565175 Conclusion. The suggested method of the control quality assessment, which is based on the application of information criterion, allows for a simple and effective evaluation of the accuracy and quality of technical control devices. The generalized criterion of control quality can be the information uncertainty of the control action, based on the use of Bongard's uncertainty. The uncertainty assessment criterion is defined as the ratio of the amount of misinformation introduced by the control device to the maximum possible amount.

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AN ASSESSMENT METHOD FOR THE CONTROL SYSTEMS QUALITY МЕТОД ОЦІНКИ ЯКОСТІ СИСТЕМ КЕРУВАННЯ - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/cos-model-In-the-upper-part-of-the-diagram-a-model-of-a-continuous-time-PID-controller_fig1_388753199 [accessed 26 Apr 2025]

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Figure 2 -Xcos-model In the upper part of the diagram, a model of a continuous-time PID controller is presented, in the lower part, a discrete one. Vectors of input and output values are transferred to the Scilab workspace. These data are processed according to formula (2) by the following Scilab-scenario: pid=abs(diff(Yd.values)); piX=abs(diff(X.values)); Sh = -sum(pid.*log2(pid))/sum(pid); Bo = -sum(pid.*log2(piX))/sum(pid); critd = 1-Sh/Bo; disp(critd) Discretization of the PID controller was performed by two methods: by Euler and by Tustin. For each of these options, the simulation was run and the amount of misinformation was calculated. The results in Table 1 show the better quality of the controller discretized by Tustin's method. Which corresponds to the theory. Table 1 -Research results Controller The amount of misinformation discretized by the Euler's method 0.0467428 discretized by Tustin's method 0.0565175 Conclusion. The suggested method of the control quality assessment, which is based on the application of information criterion, allows for a simple and effective evaluation of the accuracy and quality of technical control devices. The generalized criterion of control quality can be the information uncertainty of the control action, based on the use of Bongard's uncertainty. The uncertainty assessment criterion is defined as the ratio of the amount of misinformation introduced by the control device to the maximum possible amount.

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<a href="https://www.researchgate.net/figure/cos-model-In-the-upper-part-of-the-diagram-a-model-of-a-continuous-time-PID-controller_fig1_388753199"><img src="https://www.researchgate.net/profile/Gennadii_Manko/publication/388753199/figure/fig1/AS:11431281308199022@1738844334868/cos-model-In-the-upper-part-of-the-diagram-a-model-of-a-continuous-time-PID-controller.png" alt="-Xcos-model In the upper part of the diagram, a model of a continuous-time PID controller is presented, in the lower part, a discrete one. Vectors of input and output values are transferred to the Scilab workspace. These data are processed according to formula (2) by the following Scilab-scenario: pid=abs(diff(Yd.values)); piX=abs(diff(X.values)); Sh = -sum(pid.*log2(pid))/sum(pid); Bo = -sum(pid.*log2(piX))/sum(pid); critd = 1-Sh/Bo; disp(critd) Discretization of the PID controller was performed by two methods: by Euler and by Tustin. For each of these options, the simulation was run and the amount of misinformation was calculated. The results in Table 1 show the better quality of the controller discretized by Tustin's method. Which corresponds to the theory. Table 1 -Research results Controller The amount of misinformation discretized by the Euler's method 0.0467428 discretized by Tustin's method 0.0565175 Conclusion. The suggested method of the control quality assessment, which is based on the application of information criterion, allows for a simple and effective evaluation of the accuracy and quality of technical control devices. The generalized criterion of control quality can be the information uncertainty of the control action, based on the use of Bongard's uncertainty. The uncertainty assessment criterion is defined as the ratio of the amount of misinformation introduced by the control device to the maximum possible amount."/></a>