Multi-Objective Optimisation of PID and H ∞ Fin/Rudder Roll Controllers

Multi-Objective Optimisation of Restricted Complexity Controllers

Restricted complexity controller design for the active suspension benchmark problem [1] is considered. The control design specifications of the benchmark is firstly recast into a mixed H∞/l1 optimisation problem, which is solved via a convex optimisation approach. A globally optimal Pareto curve is produced via the optimisation. It presents the limits of performance and is served as a reference...

Multi-Objective Particle Swarm Optimization Design of PID Controllers

A new multi-objective particle swarm optimization algorithm is presented. The proposed multi-objective particle swarm optimization algorithm is based on a MaxiMin technique previously proposed for a multi-objective genetic algorithm. The technique is applied to optimize a benchmark function set and to the design of PID controllers regarding the objectives of set-point tracking and output distur...

Multi criteria H∞ optimal PID controllers from an undergraduate perspective

A simple design method for robust PID controllers is presented. It is based on a multi criteria H∞ optimal control formulation, which is shown to be easily solved by a few lines of MATLAB code. This optimal solution for PID controllers including low pass filtering, is complemented by a simple paper and pen solution that can be used to obtain nearly optimal solutions. The presented approach is s...

MPC vs. PID Controllers in Multi-CPU Multi-Objective Real-Time Scheduling Systems

This paper provides an empirical investigation between multiple control-theoretic approaches in real-time scheduling systems. These approaches include proportional-integralderivative (PID) and model predictive control. The former is a widely adopted controller due to its simplicity in design and implementation. The latter is considered a sophisticated one in the control community with respect t...

Multi-objective Binary Search Optimisation