Thakur Chanda, Batish Navdeep, International Journal of Advance Research, Ideas and Innovations in Technology. © 2016, IJARIIT All Rights Reserved Page | 222 ISSN: 2454-132X Impact factor: 4.295 (Volume3, Issue1) Available online at: www.ijariit.com Convex Optimization Based Adaptive PID Controller in CSTR Plant Chanda Thakur Power System & I.K.Gujral, Punjab Technical University. Thakur_Chanda 15@yahoo.com Navdeep Batish Power System & Chandigarh University. Navdeepbatish@yahoo.co.in Abstract— The proposed PSO-PID and HU-PID controller is tested by using Mat-lab Simulink program and their performance is compared. It is clear from Table 5.1 that a HU-PID controller is best implemented. Also, the PID controller parameters obtained from HU algorithm gives better tuning result as compared to PSO-PID rule. The major impact of HU is on integral square error and peak overshooting. Both are minimized by HU-PID controller. HU-PID is a very simple concept and paradigms can be implemented in a few lines of computer code. Keywords- CSTR, PID, Control, Optimization. I. INTRODUCTION Process control has become increasingly important in the process industries as a consequence of global competition, rapidly changing economic conditions, and more stringent environmental and safety regulations. Process control is also a critical concern in the development of more flexible and more flexible and more complex processes for manufacturing high value added products. Any study of process control must begin by investigating the concept of a process. It is generally thought of as a place where materials and most often, energy come together to produce a desired product. From a control viewpoint the meaning is more specific. A process is identified as leaving one or more variables associated with it that are important enough for their values to be known and for them to be controlled. One of the complex and difficult in process control ids control tuning. Control tuning is the major key issue to operate the plant. Process tuning is a key role in ensuring that the plant performance satisfies the operating objectives. Controller tuning inevitably involves a trade-off between performance and robustness. The performance goals of excellent set-point tracking and disturbance rejection should be balanced against the robustness goal of stable operation over a wide range of conditions. The Process control system is the entity that is charged with the responsibility for monitoring outputs, making decisions about how best to manipulate inputs so as to obtain desired output behavior, and effectively implement such decisions on the process [1]. It is therefore convenient to break down the responsibility of the control system into the following three major tasks: • Monitoring process output variables by measurements • Making rational decisions regarding what corrective action is needed on the basis of the information about the past current and desired state of the process • Effectively implementing these decisions on the process Control Systems Control systems are classified into two general categories open loop and closed loop control systems. Open loop control systems are control systems in which the output has no effect upon the control action. In an open-loop control system, the output is neither measured nor fed back for comparison with the input. For example, in a washing machine, soaking, washing, and rinsing are operated on a time basis. The machine does not measure the output signal namely the cleanliness of clothes. In any open-loop control system the output is not compared with the reference input. Hence, for each reference input,