Transient response improvement of feedback control systems using hybrid reference control

By means of the internal model principle, an approach to improve the performance of a stabilised closed-loop continuous time linear system based on manipulation of the reference signal is developed. A change in the reference signal is equivalent to implementing an instantaneous change via the choice of a decision vector in the state of the reference signal model, and the analysis of the proposed approach called hybrid reference control (HRC) system is then shown to be equivalent to the analysis of a linear impulsive dynamical system. Conditions for asymptotic stability and convergence of the output tracking error for a HRC system are expressed in term of conditions on the decision vectors. Conditions are then derived which guarantee that the HRC system leads to an improved transient performance compared to a conventional closed-loop control system. In particular, it is shown how decision vectors are chosen so that a HRC system results in a deadbeat response.     

Finite horizon optimal hybrid reference control for improving transient response of feedback control systems

Hybrid reference control (HRC) has been known to improve transient response of a stabilised closed-loop continuous tracking system. In this paper, an optimal HRC strategy, which minimises a finite horizon quadratic performance index in the control and state error, is investigated based on the assumption that the full plant states are available for measurement. A special case of constrained optimisation problems leads to the optimal deadbeat control strategy. Conditions for asymptotic stability to default reference signal are also derived.     

Robust MIMO H∞ Integral-Backstepping PID Controller for Hovering Control of Unmanned Model Helicopter

The problem of stabilization of a model helicopter in a hover configuration subject to parametric uncertainty and external disturbances is addressed. Multiinput multioutput (MIMO) proportional-integral-derivative (PID) control law is reformulated into a full-state feedback control law to synthesize the controller by using robust H∞ control theory. In full-state feedback representation, PID control has implicit integral-backstepping structure. Therefore a new parameter, ρ, can be introduced that acts on the derivative of the control signal. The parameters of MIMO PID controller are then obtained with solving the algebraic Riccati equation with selecting the values of ρ and γ. Model helicopter simulation is carried out to verify the performance of the proposed controller to stabilize the uncertain helicopter model and to suppress external disturbances.