This paper presents a computer-aided control engineering (CACE) environment for synthesis of nonlinear and time-varying PID controllers for use with systems that have highly nonlinear plants. The implemented CACE technique is based on a four-step systematic procedure. The nonlinear PID controller design methodology and the associated software allow the user to synthesize for robust nonlinear closed-loop feedback systems whose dynamic and static behaviours would satisfy a set of user-defined performance measures with as little sensitivity to the amplitude level of the excitation command as possible. The CACE environment performs a complete cycle of steps starting from plant description to timedomain modelling, linear system identification, controller synthesis, and design validation via digital simulation.
computer-aided engineering, nonlinear systems, PID controllers
As the control of dynamic systems in the areas of consumer products, manufacturing systems, and defence systems is becoming increasingly important, it is desirable for dynamic systems to perform better (higher performance specifications, lower costs to produce, maintain, and support) 1. A need exists for systematic controller design methodologies that would be applicable to real-life dynamic systems. Such systems are inherently not linear. Therefore, the need exists for systematic controller design techniques that are capable of compensating for soft (polynomial type) as well as hard (stiction) nonlinearities. Consider an industrial robot with multiple degrees of freedom. In this case, gravity, disturbances, and interaction among the links add to the complexity of the control problem. Hence, design of linear controllers for robot arms which are required to operate in a number of different regimes may not be adequate. Therefore, a nonlinear controller design technique, which would be applicable to a fairly small but important class of nonlinear systems, is developed. The class of nonlinear systems considered here are representable in standard state-variable differential