Around ten million people in the world are affected by Parkinson's disease (PD), accounting for about less than 1% of the global population. The rising prevalence of PD draws attention to the growing individual and social cost, as well as the urgent need for efforts to enhance the quality of life of the patient. The automation of the conventional ambulatory Duodopa pump (ADP) is the most challenging aspect of dopamine therapy for PD due to a range of unanticipated external events. In this regard, the goal of this paper is to develop a robust control strategy specifically, a sliding mode controller (SMC) scheme for a newly designed ADP to ensure optimal drug therapy. The proposed ADP is modeled by cascading the mathematical model of linear electromechanical actuator (EMA), drug infusing syringe pump in tandem with the dose-effect relationship of Levodopa and continuous dopamine sensor (CDS). While traditional SMC is liable to induce numerical chattering, smooth SMC (SSMC) and an integral SMC (ISMC) are designed to minimize chattering by maintaining accuracy in set-point tracking of plasma dopamine concentration. The in-silico results described in this paper persuasively confirm that the SSMC and ISMC supersede the traditional one in numerous key ways: chattering in the control input is nearly non-existent, fast-tracking performance, and good transient response. A robust stability evaluation with ISMC reveals that it can accommodate only a small cohort with less inter-patient variability, but its overall performance in terms of chattering reduction and set-point tracking is superior to that of traditional SMC and SSMC.