Tools

 
Matlab Toolsets and Functions left.jpg (982 bytes)
Matlab functions for the calculation of characteristic areas from the parametric process model

numden2areas.m  calculates areas from the given numerator, denominator and time delay of the process

zp2areas.m calculates areas from the given location of process poles and zeros

tc2areas.m calculates areas from the given time constants of the numerator and denominator 

The above functions are zipped in the following file: Functions2Areas.zip 

Matlab functions for the calculation of controller parameters from the characteristic areas

Area2P calculates proportional (P) controller gain from the characteristic areas

Area2I calculates integral (I) controller gain from the characteristic area

Area2PI calculates PI controller parameters from the characteristic areas (for tracking)

Area2PID calculates PID controller parameters from the characteristic areas (for tracking)

Area2PI_dist calculates PI controller parameters for optimised disturbance-rejection from the characteristic areas

Area2PID_dist calculates simlified PID controller parameters for disturbance-rejection from the characteristic areas 

The above functions are zipped in the following file: Areas2Controllers.zip 

 

Matlab Files: Papers and Conferences
Matlab Toolset for Cascade systems (ASCC 2002). This toolset contains matlab files (*.m) required for the calculation of the primary and the secondary controller. The *.mat files (containing all the relevant variables for different cases) and simulink model file are given HERE.
Matlab Toolset for Multivariable (TITO) systems (ASCC 2002). This toolset contains matlab files (*.m) required for the calculation of the primary and the secondary controller. The *.mat files (containing all the relevant variables for different cases) and simulink model file are given HERE.
Matlab Toolset for Disturbance Rejection Controller (PID) (ASCC 2002). This toolset contains matlab files (*.m) required for the calculation of the PID controller parameters for optimal disturbance rejection.
Matlab Toolset for Simplified Disturbance Rejection Controller (PID) (ASCC 2004). This toolset contains matlab files (*.m) required for the simplified calculation of the PID controller parameters for  disturbance rejection.
Matlab Toolset for Reduced MO Tuning Method (PID, PI, I) (ASCC 2004). This toolset contains matlab files (*.m) required for the calculation of the PID, PI and I controller parameters for disturbance rejection according to some given stability and perfomance criteria.
Matlab Toolset for "Improving Performance/Activity Ratio for PID Controllers" (International Conference on Control and Automation, Budapest, 2005). This toolset contains matlab and simulink files (*.m, *.mdl) - for Matlab 5.3
Matlab file for "Testing of performance criteria by time multipliers" (ASCC 2006). The file OL2Ellipse.m is written in Matlab 5.3
Matlab and Simulink files (including measurements) for "Equalisation tuning approach" (Manchester, UKACC CONTROL 2008) in zipped file. Unzip all the files into the same directory. The files are written in Matlab 5.3, but they work on later versions as well. Testing processes can be achieved by runing testing_proc.m, testing noise behaviour by running testing_noise.m and calculation from the real-time measurements on hydraulic plant by running testing_rt.m
Matlab and Simulink files (including measurements) for "MOMI method for Integral Processes" (Vila Real, CONTROLO 2008) in zipped file. Unzip all the files into the same directory. The files are written in Matlab 5.3, but they should work on later versions as well. Testing processes can be achieved by runing test_integral_process_models.m, and calculation from the real-time measurements on hydraulic plant by running meas_integral_process.m
Matlab and Simulink files for "Improving disturbance rejection of PID controllers by means of the magnitude optimum method" (Submitted paper) in zipped file. Unzip all the files into the same directory. The files are written in Matlab 5.3, but they should work on later versions as well. Run drmo_calculations.m, and drmo_comparison.m. All the calculations will be executed and Figures done.
Matlab and Simulink files (including measurements) for "Equalisation Tuning Method for PID controllers" (submitted paper) in zipped file. Unzip all the files into the same directory. Testing processes can be achieved by running comparison_weighted.m, comparison to other methods with comparison_methods.m, testing noise behaviour by running testing_noise.m and calculation from the real-time measurements on hydraulic plant by running testing_rt.m
Matlab and Simulink files for "Design of feedback control for unstable processes with time delay" (submitted paper - ASCC) in zipped file. Unzip all the files into the same directory. The files are written in Matlab 5.3, but they should work on later versions as well (if it doesn't, please, let me know). Testing processes can be achieved by running test_illustrative.m, and/or test_unstab_denf.m.
Matlab and Simulink files for "Parametric and non-parametric PI controller tuning method for integrating processes based on Magnitude Optimum" (submitted paper ) in zipped file . Unzip all the files into the same directory. Testing processes can be achieved by running test_illustrative_other.m, test_integral_proc_allbeta.m, test_integral_b_comparison.m and/or meas_integral_process.m.
Matlab file for fast-filtering: "A Novel Fast-Filtering Method for Rotational Speed of the BLDC Motor Drive Applied to Valve Actuator" (paper for EIC, Transactions on Mechatronics) in zipped form . Unzip  the file and execute with Matlab. The file contains whole algorithm for fast-filtering of jittered rotational speed.
Matlab file for "The Magnitude Optimum Tuning of the PID Controller – Improving Load Disturbance Rejection by Extending the Controller" in zipped form. Unzip  the file and execute with Matlab. The file contains whole tuning algorithm for the calculation of controller parameters with extension terms and filters.
Matlab and simulink files for "Optimizing disturbance rejection by using model-based compensator with user-defined high-frequency gains" in zipped form. Unzip  the file in some directory and execute Matlab programme "Test_model_disturbance_rejection_complete_Approx_2red_02.m". The file contains whole tuning algorithm for the calculation of controller parameters and compensator's parameters for the chosen process model.

Last update: 07.02.2020