Based on our previous research results partially published in [1], [2], [3] and [4], the paper presents a survey on dedicated control solutions for driving systems working under continuously variable conditions: variable reference input (speed), variable moment of inertia and variable load disturbance. The solutions were validated using numerical simulation and tested on a laboratory equipment [5]. The structures employ the switching between different ModelBased (MB) control algorithms; due on the simplicity in adaptation, different fuzzified Takagi-Sugeno control solutions are offered. A hybrid Takagi-Sugeno PI-neurofuzzy controller is presented. The solutions are based on a classical cascade control structure with an inner current controller and an external speed control loop with bumpless switching between the control algorithms. Our solutions are representative for mechatronics applications.
I. INTRODUCTIONThe paper synthesizes results concerning the development of control solutions with variable parameters dedicated for driving systems working in continuously variable conditions (c.v.c.) variable reference, variable parameters (mainly variable moment of inertia, VMI) and variable load disturbance, which depends on the plant evolution, reported by the authors in [1]- [4]. Similar applications are also treated in other papers in the literature [6]- [9]. For such applications, the variable control solution offers better control system performance: better variable reference control and better operating in extreme regimes.Based on the fact that a relatively good model of the plant can be available, Section II is focused on the plant modeling: the nonlinear model and, derived from it, the linearized benchmark mathematical models (MMs) which are efficiently usable in the design step [10]. Section III presents the basic control structures: the PI case, the T-S PI-fuzzy controller, the PI quasi-relay sliding mode controller and finally, the neuro-fuzzy controller. Case studies related to the tuning are treated in Section IV. The main conclusions are discussed in Section V.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.