Perancangan Sistem Pengendalian Level Berbasis MRAC pada Deaerator Unit 101-U di PT. Petrokimia Gresik

Pengendalian level air pada deaerator sangatlah penting karena akan berpengaruh pada banyaknya gas-gas terlarut yang dapat dihilangkan dalam air upan boiler. Apabila gas-gas terlarut masih banyak yang tertinggal dalam air, maka akan dapat menyebabkan korosi pada dinding-dinding boiler dan komponen-komponen yang dilewati oleh air keluaran deaerator. Banyaknya variabel yang mempengaruhi kestabilan proses yang terjadi didalam deaerator sehingga kenonlinieritasan dalam deaerator tidak akan teratasi jika skema kontrol PID biasa diterapkan. Pada Tugas Akhir ini diakukan perancangan Model Reference Adaptiv Control yang merupakan skema sistem kontrol adaptif yang memiliki mekanisme pengaturan terhadap parameter kontroler sehingga sistem akan mampu beradaptasi. Langkah awal yang dilakukan adalah memodelkan proses yang terjadi pada deaerator. Selanjutnya dilakukan perancangan algoritma pengaturan dengan menerapkan teori kestabilan Lyapunov. Karakteristik respon model reference yang dihasilkan adalah maximum overshoot 7,7%, rise time 12s, dan error steady state 0%. Pengujian tracking set point naik, turun, kombinasi naik turun serta noise dilakukan dengan nilai masing-masing RSME yang dihasilkan respon plant terhadap model reference adalah 2,582×〖10〗^(-3), 2,52×〖10〗^(-3), 2,462×〖10〗^(-3), dan 5,42×〖10〗^(-3). Pada pengujian gangguan yang diberikan, sistem MRAC yang dirancang mampu mengatasi gangguan lebih cepat dari pada kontrol PI dengan 375s. ==================================================================== Water level control in the deaerator is important because it affects the amount of dissolved gases that can be removed in boiler water. If many dissolved gases are left in the water, they can cause corrosion of the boiler walls and the components passed by the deaerator output water. The number of variables that affect the stability of processes that occur within the deaerator so that nonlinearity in the deaerator will not be resolved if the usual PID control scheme is applied. In this Final Project is designed the Model Reference Adaptive Control which is an adaptive control system scheme that has a regulatory mechanism to controller parameters so that the system will be able to adapt. The first step is to model the process that occurs in the deaerator. Furthermore, the design of the arrangement algorithm by applying Lyapunov stability theory. Characteristics of the resulting reference model response are maximum overshoot 7.7%, rise time 12s, and 0% steady state error. The test of tracking set point up, down, up and down combination and noise were done with each RSME value generated by plant response to the reference model is2,582×〖10〗^(-3), 2,52×〖10〗^(-3), 2,462×〖10〗^(-3), dan 5,42×〖10〗^(-3). In tests of disturbances provided, the designed MRAC system is able to overcome the interference faster than the PI control with 375

Tube model reference adaptive control

By using the concept of on-line goal adaptation, we develop a new paradigm of performance shaping in MRAC. The general idea is to replace the single reference model generated trajectory in classical adaptive design with a tube reference model. Two alternative adaptive control schemes that lead to tractable design formulations are developed in which the performance is adapted on-line to satisfy a new specification in addition to maintaining the usual stability and robustness properties. For this purpose an additional optimization problem is formulated within the MRAC framework to find a correction control term at each instant of time. The proposed approach provides a convenient intuitive interpretation of the design problem, while retaining the fundamental ideas on which model reference adaptive control is based. The system performance is found to be as desired by simulation

Fractional Order Tube Model Reference Adaptive Control for a Class of Fractional Order Linear Systems

We introduce a novel fractional order adaptive control design based on the tube model reference adaptive control (TMRAC) scheme for a class of fractional order linear systems. By considering an adaptive state feedback control configuration, the main idea is to replace the classical reference model with a single predetermined trajectory by a fractional order performance tube guidance model allowing a set of admissible trajectories. Besides, an optimization problem is formulated to compute an on-line correction control signal within specified bounds in order to update the system performance while minimizing a control cost criterion. The asymptotic stability of the closed loop fractional order control system is demonstrated using an extension of the Lyapunov direct method. The dynamical performance of the fractional order tube model reference adaptive control (FOTMRAC) is compared with the standard fractional order model reference adaptive control (FOMRAC) strategy, and the simulation results show the effectiveness of the proposed control method

Fractional order tube model reference adaptive control for a class of fractional order linear systems

We introduce a novel fractional order adaptive control design based on the tube model reference adaptive control (TMRAC) scheme for a class of fractional order linear systems. By considering an adaptive state feedback control configuration, the main idea is to replace the classical reference model with a single predetermined trajectory by a fractional order performance tube guidance model allowing a set of admissible trajectories. Besides, an optimization problem is formulated to compute an on-line correction control signal within specified bounds in order to update the system performance while minimizing a control cost criterion. The asymptotic stability of the closed loop fractional order control system is demonstrated using an extension of the Lyapunov direct method. The dynamical performance of the fractional order tube model reference adaptive control (FOTMRAC) is compared with the standard fractional order model reference adaptive control (FOMRAC) strategy, and the simulation results show the effectiveness of the proposed control method